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C L I M A +:

An Early Design Natural Ventilation Prediction Method

by

Alpha Yacob Arsano

Bachelor of Science in Architecture

Ethiopian Institute of Architecture, Building Construction and City Development, 2013

Submitted to the Department of Architecture

in Partial Fulfillment of the Requirements for the Degree of

Master of Science in Architecture Studies

at the

Massachusetts Institute of Technology

June 2017

@ Massachusetts Institute of Technology.

All rights reserved.

Signature of Author: _______________________________________________________

Department of Architecture

May 25, 2016

Certified by: _____________________________________________________________

Christoph Reinhart

Associate Professor of Building Technology

Thesis Supervisor

Accepted by: ____________________________________________________________

Sheila Kennedy

Professor of Architecture

Chair of the Department Committee on Graduate Students

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Committee

Thesis Supervisor: Christoph Reinhart

Associate Professor of Building Technology

Thesis Readers: Brandon Clifford

Assistant Professor in Architecture

Erik Olson CEO, Transsolar Inc

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C L I M A +:

An Early Design Natural Ventilation Prediction Method by

Alpha Yacob Arsano

Submitted to the Department of Architecture on May 25, 2016

in Partial Fulfillment of the Requirements for the

Degree of Master of Science in Architecture Studies

Abstract

One of the most widely discussed passive building design strategies is using natural ventilation for

cooling. In addition to providing fresh air, which enhances occupant productivity and comfort,

strategic implementation of natural ventilation in buildings reduces the energy needed for cooling.

And this reduction in energy consumption significantly reduces carbon dioxide emissions. During

the initial design phase, designers routinely use climate-file based analysis to evaluate the potential

for comfort ventilation against other passive building strategies. Following this initial screening,

it is customary to conduct detailed simulations to further develop design ideas. At this point,

inconsistencies can arise between the early climate-file based analysis and later-stage simulations.

Major differences arise from limitations of climate-file based analysis to account for influences of

construction assemblies, building program, and occupant comfort preferences. This manuscript

presents a building performance-based climate analysis method where quick, single-zone

simulations are run in EnergyPlus. The ventilation cooling potential for a site and a building

program is calculated using a series of Python scripts.

Thesis Supervisor: Christoph Reinhart

Title: Associate Professor of Building Technology

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Acknowledgments

Thank you to Christoph Reinhart for your infectious excitement and uninterrupted support for the past two

years. You are indeed a wonderful mentor.

Thank you to Brandon Clifford and Erik Olsen for taking the time to share critical ideas during my research.

Thank you to Salmaan Craig, the learning from the lectures and the discussions in the Thermal Tectonics

course helped shape the effort in this work.

Thank you to Carlos Cerezo, you have been very inspiring with your meticulous and beautiful work. It is a

pleasure working with you.

A special thank you to Bradley Tran. You have always been by my side from the hectic work seasons to

the most crazy-fun nights. Thank you for editing this document with your precise and sharp eyes.

Thank you to Francesca, Renaud, and Pierre. You have made spending endless number of hours in the BT

lab enjoyable. I will never forget the special home cuisines and your culinary skills.

I am grateful to my Allston family, to Joan and Laura. I love you dearly. We will finally go for hiking after

a year of planning.

A very special thank you to Saba Moges and Yacob Arsano for nurturing me with your parental but friendly

advices in spite of the large geographical separation. I always feel your presence.

A very special gratitude to Lulit and Yosef for letting me make your home my home. The delicious Buna

with the hilarious Saturday late night chats ware the recipe for recuperation.

A special thank you to my sister Yodit for being my sunshine. Although your most missed voice comes

through the skype line only occasionally, you are always in my heart.

A special thank you to my brother Iskinder, also known as Isku the Great, for being a listener and an advisor

on multiple personal and academic endeavors. Thank you for offering your proficiency and love for writing

to groom this manuscript.

A special thank you to my sister Gelila, and to Nigus, for keeping me up to speed with Addis jocks. Thanks

a lot for always looking out for me big sister.

I am very grateful for the funding sources for this work: MIT-Portugal Program, and the Massachusetts

Institute of Technology.

Last, but by no means least, thank you for all students and faculty in the Building Technology lab. Thank

you to Kathleen Rose for always making resources accessible and getting us together in the events you

organize.

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Contents

Acknowledgements 5

List of Figures 9

Nomenclature 10

1. Introduction 12

1.1. Research Motivation and Objective 14

1.2. What Can Go Wrong in the Design Process of Naturally Ventilated Building? 15

2. Background 16

2.1. Thermal Comfort, Natural Ventilation, and Thermal Mass 18

2.2. Existing Tools, and Methods for Early Design Decision 27

3. C L I M A + 31

3.1. Method for Natural Ventilation Potential Prediction 32

3.1.1. Phase I- Using Climate Analysis 33

3.1.2. Phase II- Using Climate Box Simulation 40

3.2. User Interaction and Integration with Design Process 48

3.3. Results and Discussion 50

4. Mapping Natural Ventilation Globally 56

5. Concluding Remarks 58

5.1. Future Work 59

Appendix 61

A. Thermal Climate Zone Definition 61

B. Temporal Charts of the Selected 20 Climates 62

References 64

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List of Figures

Figure 1 A medium-sized reference commercial building ......................................................................... 14

Figure 2 Comparison of predictions on overheated hours ........................................................................ 15

Figure 3 Important dates in the development of thermal comfort guidelines and standards. ................. 17

Figure 4 Acceptable operative temperature ranges for naturally conditioned spaces ............................. 19

Figure 5 Increases in acceptable operative temperature limits ................................................................ 20

Figure 6 Applications of Natural ventilation ............................................................................................. 21

Figure 7 Coupling of building insulation and thermal mass ...................................................................... 22

Figure 8 Comparison of thermal mass buffering ....................................................................................... 23

Figure 9 Internal thermal mass ................................................................................................................. 24

Figure 10 Natural ventilation integration with climate .............................................................................. 25

Figure 11 Comparison of U-Values ............................................................................................................ 26

Figure 12 The description of thermal comfort models ............................................................................. 27

Figure 13 Climate Consultant’s Bioclimatic Chart ..................................................................................... 28

Figure 14 Components of the building bioclimatic chart of Climate Consultant ....................................... 28

Figure 15 CBE Thermal Comfort Tool. ....................................................................................................... 30

Figure 16 The effect of the rate of natural ventilation on thermal mass buffering ................................... 32

Figure 17 The components of CLIMA+ natural ventilation prediction method. ....................................... 33

Figure 18 The coupling of natural ventilation and thermal mass .............................................................. 34

Figure 19 Phase I study for Phoenix. ......................................................................................................... 36

Figure 20 Potential application of different natural ventilation methods in ............................................. 37

Figure 21 compared for 20 selected climates. .......................................................................................... 38

Figure 22 The components of CLIMA+ natural ventilation prediction method. ....................................... 40

Figure 23 The nine thermal climate zones defined by ASHRAE................................................................. 41

Figure 24 Single zone thermal zone .......................................................................................................... 42

Figure 25 CLIMA+ user inputs ................................................................................................................... 43

Figure 26 Occupancy schedules used for office and residence templates ................................................ 43

Figure 27 Thermal model settings............................................................................................................. 44

Figure 28 Building constructions ............................................................................................................... 44

Figure 29 Building and occupant preferences ........................................................................................... 45

Figure 30 Temporal chart for a residence in Phoenix ............................................................................... 46

Figure 32 CLIMA+ interface 1 .................................................................................................................... 47

Figure 31 CLIMA+ interface 2 .................................................................................................................... 47

Figure 33 Workflow of CLIMA+ with a 3D CAD design environment......................................................... 49

Figure 34 A comparison of predicted overheated hours .......................................................................... 50

Figure 35 Office and residence occupied hours ........................................................................................ 51

Figure 36 A comparison of number of discomfort hours .......................................................................... 52

Figure 37 Effect of thermal mass .............................................................................................................. 53

Figure 38 The comparisons of temporal graphs........................................................................................ 55

Figure 39 Global maps showing natural ventilation predictions ............................................................... 57

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Nomenclature

Adaptive Comfort Standard (ACS)

American Society of Heating and Air-Conditioning Engineers (ASHRAE)

Chartered Institution of Building Services Engineers (CIBSE)

Intermediate Data Format (IDF)

American Society of Heating and Ventilating Engineers (ASHVE)

EnergyPlus Weather Data (EPW)

The US Department of Energy (DOE)

Climate zone (CZ)

Thermal mass (TM)

Mean outdoor air temperature (Trm(out))

Temperature, Kelvin (K)

Temperature, Celsius (0C)

High ventilation- provides sufficient air change rates resulting in indoor air temperature following outdoor

air temperature. Thermal mass buffering of indoor air temperature is restricted.

Low ventilation- provides low air change rates sufficient for fresh air, but indoor air temperature will

remain higher than outdoor air temperature due to internal heat gains.

Climate or weather data- hourly, site-specific values of representative meteorological data, such as

temperature, wind direction and speed, solar radiation, and relative humidity. For locations where climate

data are not available, the designer shall select available weather or meteorological data that best represents

the climate at the building site (ASHRAE 55-2013).

Adaptive model- a model that relates indoor design temperatures or acceptable temperature ranges to

outdoor meteorological or climatological parameters. It is the method for determining acceptable thermal

conditions in occupant-controlled, naturally conditioned spaces (ASHRAE 55-2013).

Thermal comfort- condition of mind that expresses satisfaction with the thermal environment and is

assessed by subjective evaluation (ASHRAE 55-2013).

Acceptable thermal environment- a thermal environment that a substantial majority (more than 80%) of

the occupants find thermally acceptable (ASHRAE 55-2013).

Operative temperature- the uniform temperature of an imaginary black enclosure and the air within it in

which an occupant would exchange the same amount of heat by radiation and convection, as in the actual

nonuniform environment. It is calculated in accordance with Normative Appendix A of ASHRAE 55-2013.

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1 Introduction

1.1 Research Motivation and Objective

Thermal comfort is one of the fundamental aspects of indoor environmental quality that is strongly

related to occupant satisfaction and energy use in buildings (Schiavon et al 2014). Many building

science textbooks for designers and architects promote an hourly climate-file based analysis in

order to understand whether natural ventilation is a valid design strategy to enhance thermal

comfort. The analysis yields the number of comfort hours natural ventilation could add to a space

over the course of the year using bioclimatic charts. These methods were first developed during

the 1950s and have been implemented into digital design tools such as Climate Consultant and

Ecotect Weather Tool.

Victor Olgyay was an important pioneer of thermal comfort representations. He used the concept

of an Effective Temperature (ET) as the basis of his comfort diagram, the ‘Bioclimatic Chart’

(Schiavon et al 2014). This chart assumes the criterion that the perimeter of the comfort zone

outlines the conditions in which an average person will not experience discomfort and it applies to

moderate climate zones (Olgyay 1963). Givoni, author of ‘Building Bioclimatic Chart’, extended

Olgyay’s representation to the psychrometric chart and added rules about passive heating and

cooling strategies. The Building Bioclimatic Chart, which is implemented in Climate Consultant,

is a widely used climate-file based tool that uses two components: thermal comfort area and

‘boundaries of climatic conditions within which various building design strategies and natural

cooling systems can provide comfort’ (Givoni 1992).

Climate Consultant allows users to upload the standardized EPW format climate data, which are

made available online by the US Department of Energy (Climate Consultant 6.0 Documentation).

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All hours of the year are then plotted on the Building Bioclimatic Chart, where different design

strategies are compared. However, it does not allow users to adjust the level of air movement and

does not include Standard 55’s model for elevated air speed. The thermal comfort area reported in

the Bioclimatic Chart is not consistent with ASHRAE 55 thermal comfort areas (Schiavon et al

2014). Furthermore, the underlying principle for Climate Consultant’s comfort ventilation

calculates only for psychological cooling, and clearly states that ventilation does not reduce the

dry bulb temperature (Climate Consultant 6.0 Documentation). On the contrary, thermal

simulation tools such as EnergyPlus and CoolVent perform detailed building analysis to predict

zone temperatures and airflow rates in naturally ventilated buildings, but they neglect

psychological cooling effects due to indoor air movements.

Designers and their consultants interested in designing high-performance buildings tend to start

their conceptual design with a quick, climate-file based analysis. If the required know-how is

present within the team, they later switch to more detailed, whole-building simulation tools that

can further evaluate the hourly indoor thermal comfort conditions for a particular building design.

Based on the observations discussed above, this thesis carefully reviews the assumptions

underlying these two analysis steps, evaluates their applicability to a variety of building types and

climates, and proposes an improved workflow for design teams to use. The objective is to allow a

design team to easily transition between an early climate-file based analysis to a detailed building

design analysis without conflicting results.

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Figure 1 A medium-sized reference commercial building

selected for analysis among the 16 building types that represent approximately 70% of the commercial buildings in

the U.S., according to the report published by the National Renewable Energy Laboratory titled U.S. Department of

Energy Commercial Reference Building Models of the National Building Stock (Energy.Gov).

1.2 What Can Go Wrong in the Design Process of Naturally Ventilated Building?

An expert in an international climate-engineering firm shared a story about one particular

encounter with a client. The goal of the collaboration was to develop deeply integrated comfort

and energy concepts for a project located in New England. The climate engineer presented high-

performance building strategies that successfully eliminated mechanical cooling systems.

However, the client countered the climate engineer’s proposal about eliminating the active cooling

system by quoting the results from a building bioclimatic analysis method implemented in one of

the most widely used tools called Climate Consultant. This story illustrates how an inconsistency

between a quick climate-file based study and a thorough building performance analysis could arise

and consequently result in design process challenges.

The authors repeated the steps discussed in the story of the climate engineer using a medium-sized

office reference building by the US Department of Energy (DOE) located in Phoenix. The DOE,

in conjunction with three of its national laboratories, developed commercial reference buildings,

formerly known as commercial building benchmark models. These modules provide a consistent

baseline of comparison and improve the value of computer energy simulations using software such

as EnergyPlus (Energy.Gov 2017).

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Figure 2 Comparison of predictions on overheated hours

by Climate Consultant's building bioclimatic chart and building performance simulation using energy plus for a

naturally ventilated building. The bioclimatic chart reported 1550 overheated hours while on the other hand post

analysis of building simulation showed it is possible to achieve 100% comfort. The adaptive comfort model is used

in both cases.

The prediction of the number of overheated hours by Climate Consultant’s bioclimatic chart is

compared with the number of overheated hours calculated using building simulation of the

reference office building (see figure above). The prediction of overheated hours by the building

bioclimatic chart considers cooling ventilation and thermal mass strategies. The energy simulation

study showed that overheated hours can be reduced to zero with the application of ASHRAE 55

Adaptive Comfort Standard while Climate Consultant’s optimized result showed over 1,500

overheated hours.

The underlying principles and models used in Climate Consultant’s bioclimatic chart are discussed

in detail in the background section. Additional overview is included on the CBE online tool that is

written by the Center for the Built Environment at UC Berkeley. Advantages and limitations of

these tools are then compared with the proposed method with CLIMA+.

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2 Background

A tree doesn’t need a support system –it is a system.

The shelter of the future will embody energy.

Michael Reynolds

Comfort in Any Climate, 2001

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Figure 3 Important dates in the development of thermal comfort guidelines and standards.

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2.1 Thermal Comfort, Natural Ventilation and Thermal Mass

Thermal comfort and natural ventilation have a long history in the built environment. Around 400

BC, Socrates had some thoughts on the climatic suitability of houses and on how to build to ensure

thermal comfort. Vitruvius (1st century BC) also wrote about the need to consider climate in

building design for reasons of health and comfort. This, however, had very little influence on the

practice of architecture (Auliciems et Svokolay 2007).

Mechanical cooling became a possibility early 20th century (Auliciems et Svokolay 2007), and

comfort became a 'product' produced by machines that ran on cheap energy (Nicole et al 2012).

The result has contributed to a trend in buildings with increasing use of mechanical systems and

related energy consumption.

In the early 1920s, Houghten and Yagloglou (1923) at the ASHVE (American Society of Heating

and Ventilating Engineers) laboratories attempted to define the ‘comfort zone’. In England the

motivation came from industrial hygiene: the limits of environmental conditions for work. Vernon

and Warner (1932) and later Bedford (1936) carried out empirical studies among factory workers.

Analytical work started in the US in the mid-1930s, where Winslow, Herrington and Gagge (1937)

made a significant contribution. During and after World War 2, research activity increased and

many disciplines became involved besides engineering, from physiology and medicine to

geography and climatology. In architecture, Victor Olgyay (1963) was the first to collect findings

from the various disciplines and interpret them for practical, architectural purposes (Auliciems et

Svokolay 2007).

Good passive design can minimize the periods during which mechanical cooling may be needed

and can also substantially reduce the size of the required cooling equipment, perhaps restricting its

use to only critical locations (CIBSI 2015). A growing international consensus now calls for low-

energy buildings. This means designers must first produce robust, passive structures that provide

occupants with many opportunities to make changes to suit their environmental needs. Ventilation

should be most preferred strategy and mechanical conditioning only used when the climate

demands it (Nicole et al 2012). Recent studies have started recognizing the effects of air pollution

and urban heat island on natural ventilation potential. Tong et al (2016) have shown that the energy

savings and environmental benefits are affected greatly by ambient air pollution in China. In

addition, the urban heat island effect can reduce the opportunities for night cooling in urban areas

(CIBSI 2015).

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Figure 4 Acceptable operative temperature ranges for naturally conditioned spaces

The allowable operative temperature limits may not be extrapolated to outdoor temperatures above and below the

end points of the curves in this figure. If the prevailing mean outdoor temperature is less than 10 °C or greater than

33.5 °C, this option may not be used (ASHRAE 55-2013 in Figure 5.4.2).

The Adaptive Comfort Model promotes use of the comfort evaluation method using adaptive

temperatures. Recent standards (European Standard EN 15251, ASHRAE 55) and guidelines

(CIBSE) advise that comfort temperatures vary through the year as people adapt to changes in

outside temperatures. Adaptive comfort temperatures are most appropriate to "free running"

buildings where occupants have control over themselves and their environment. As comfort

temperatures vary, heating and cooling set-points should be adjusted to maintain optimum comfort.

This is in keeping with most peoples’ experience – a building at 24°C will feel cool in summer but

hot during cooler periods of the year (Low Carbon Comfort 2014).

Adaptive comfort equations are provided in EN1525, CIBSE and ASHRAE Standards. The

adaptive comfort temperatures are based on outside temperatures during the preceding few days.

The allowable indoor operative temperatures shall be determined from the figure above using 80%

acceptability limits or the following equations as provided in ASHRAE 55-2013.

Upper 80% acceptability limit (°C) = 0.31 Trm(out) + 21.3

Lower 80% acceptability limit (°C) = 0.31 Trm(out) + 47.9

The prevailing mean outdoor air temperature (Trm(out)) shall be based on no fewer than seven and

no more than 30 sequential days prior to the day in question. It shall be a simple arithmetic mean

of all of the mean daily outdoor air temperatures of all days in the considered period.

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ASHRAE 55-2013 permits weighting methods if the weighting curve continually decreases

towards the more distant days such that the weight applied to a day is between 0.6 and 0.9 of that

applied to the subsequent day. For this option, the upper limit on the number of days in the

sequence does not apply. A weighted running mean of outdoor temperatures, Trm, is calculated

based on the following equation given in CIBSI Guide A: Environmental Design:

Trm(out)= (1 - αrm) [Te(d-1) + αrm Te(d-2) + αrm2 Te(d-3) ...]

where αrm is a constant between 0 and 1 which defines the speed at which the running mean

responds to outdoor temperature, Te(d-1) is the daily mean outdoor temperature (°C) for the previous

day, Te(d-2) is the daily mean outdoor temperature (°C) for the day before that, and so on. The

recommended value of αrm is 0.8 (CIBSI A: Environmental Design).

If operative temperature is greater than 25 °C, then increasing the upper acceptability temperature

limits in Figure 4 by the corresponding change in temperatures is permitted. The following table

is adopted from ASHRAE 55-2013 (Table 5.4.2.4).

Average Air Speed (Va) 0.6 m/s

Average Air Speed (Va) 0.9 m/s

Average Air Speed (Va) 1.2 m/s

1.2°C 1.8°C 2.2°C

Figure 5 Increases in acceptable operative temperature limits

in occupant-controlled, naturally conditioned spaces resulting from increasing air speed above 0.3 m/s.

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Figure 6 Applications of Natural ventilation

Natural ventilation has two benefits: for fresh air supply and comfort cooling. Comfort cooling with natural

ventilation can take place during daytime or night time.

In buildings with operable windows and similar ventilation devices, free precooling can be used

when outside air temperatures are below inside temperatures. In air-conditioned buildings, the use

of natural ventilation can dramatically reduce the energy required to mechanically cool the space.

In buildings with heating only, natural ventilation can significantly reduce peak indoor summer

temperatures. (Low Carbon Comfort 2014).

On cool days, free cooling can meet all the cooling load. The space is ventilated to maintain a

comfortable indoor operative temperature. On hot days, there may be limited free cooling available

in the morning and no opportunity for pre-cooling earlier in the day. It may be possible to pre-cool

during the preceding night (often referred to as night cooling), though this will often be ruled out

on practical grounds due to security risks. Pre-cooling restricted to the morning-occupied period

will still have a major energy benefit during warm weather and can typically be expected to reduce

cooling energy by 30% (Low Carbon Comfort 2014).

Very often, peak temperatures in standard buildings will exceed the outdoor peak temperature by

three or more degrees. At best, peak indoor temperature can be maintained at a degree or so below

the peak outdoor temperature but this is only possible by means of night cooling combined with

thermal mass (CIBSI 2015). Climatic conditions such as the diurnal temperature swings influence

the effectiveness of night cooling. Additional discussion on the application of thermal mass to

improve thermal comfort is presented in the third section of this document, CLIMA+ Phase I.

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Figure 7 Coupling of building insulation and thermal mass

Michael Reynolds (2001) in his book ‘Comfort in Any Climate’ illustrated the coupling of building insulat ion and

thermal mass to enhance heating and cooling strategies.

The air temperature inside a building depends on many factors, including the outdoor temperature,

building geometry and internal heat gains from occupants, equipment and lighting (Holford et

Woods 2006). Thermal mass in buildings plays a great role in buffering internal temperature from

outdoor environmental fluctuations and building design can benefit from exploiting the potential

of thermal mass to enhance thermal comfort. The specific role of effective thermal mass

specifically in naturally ventilated buildings is explained in detail by Holford and Woods. They

have shown that the effective thermal mass, which is in good thermal contact with the air is limited

by the diffusion distance into the thermal mass over one diurnal temperature cycle. They have also

shown the great applicability of thermal mass models using lumped methods and numerical

integration of thermal diffusion for exact solutions.

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Figure 8 Comparison of thermal mass buffering

of a 10 cm thick concrete structure with other constructions having different thermal mass

thickness and volumetric heat capacity.

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Figure 9 Internal thermal mass

Michael Reynolds (2001) illustrates deep and shallow room layouts of naturally ventilated spaces to regulate

exposure to solar gain.

The thermal mass thickness within an interior space can be adjusted based on climatic conditions

of the building’s location. The geometry of the room and integration of thermal mass in the interior

surfaces can be designed to optimize heat energy storage by increasing solar gain in cold climates.

On the contrary, thermal mass in a deep space that is shaded from solar radiation will be kept

cooler than outdoor temperatures in hot climates.

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Figure 10 Natural ventilation integration with climate

Michael Reynolds (2001) illustrates various passive strategies for naturally ventilated spaces in different

climates in his book Comfort in Any Climate.

The climatic forces of wind (wind effect) and temperature (stack effect) drive natural

ventilation. For this reason, natural ventilation is highly variable since, at any instant, both

the pattern of airflow and the rate of ventilation will depend on the prevailing weather

conditions (CIBSI 2015). A strategic design of buildings that integrates the methods such

as natural ventilation, thermal mass, envelope insulation, and solar heat gain, will improve

comfort in any climate.

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Building energy standards provide insulation requirements for different types of constructions and

climate zones. Insulation requirements for mass construction is relatively lower than the

requirements for steel, metal and wood constructions in all climate zones defined in ASHRAE

90.1 (see figure above). Such variation in the minimum required U-values indicates that the

building construction standards accounted the potential benefit of thermal mass in meeting comfort

requirements and reducing space conditioning energy loads.

0 0.5 1 1.5 2 2.5 3

CZ0

CZ1

CZ2

CZ3

CZ4

CZ5

CZ6

CZ7

CZ8

Above Grade Wall, Assembly Maximum Transmittance

(U-Value) ASHRAE 90.1 (2016)

WOOD STEEL METAL MASS

Figure 11 Comparison of U-Values

The nine Climate Zones defined by ASHRAE

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2.2 Existing Tools and Methods for Early Design Decision

Figure 12 The description of thermal comfort models

used in the architectural design strategies book Sun, Wind and Light, Climate Consultant, Ecotect, ASHRAE

Thermal Comfort Tool and CBE Thermal Comfort Tool.

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Figure 13 Climate Consultant’s Bioclimatic Chart

is shown for the climate of Phoenix. The number of comfortable hours are calculated and selected strategies are

highlighted at the top left corner of the figure.

Figure 14 Components of the building bioclimatic chart of Climate Consultant

Climate Consultant is a simple to use, graphic-based computer program that helps users create

more energy efficient and sustainable buildings (Milne 2009). It is extensively used in academic

and professional work at an earlier design phase to better understand a given climate.

A summary of design strategies as a function of ambient conditions (climate) are reported based

on Pschrometric-Bioclimatic Chart by Baruch Givoni and Murray Milne. The concept of a building

bioclimatic chart combines Victor Olgyay’s bioclimatic chart (Olgyay 1993), the psychrometric

chart, and passive heating and cooling rules.

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Climate Consultant’s Psychrometric chart ventilation-cooling strategy is only attributed to

physiological cooling effects achieved by air movement, which increase sweat evaporation from

the skin, and it is clearly stated that the strategy does not reduce air temperature. This ventilation

cooling potential prediction method only takes wind speed as a measure of effectiveness, and the

approach does not fully represent the process that takes place in a naturally ventilated building. It

assumes an ideal ventilation situation where the indoor temperature follows the outdoor. The

temperature difference between the indoor and outdoor that drives buoyancy is neglected resulting

in an underestimation of natural ventilation potential. Furthermore, the benefit of coupling natural

ventilation and thermal mass is not sufficiently incorporated. Rather, thermal mass is calculated

independently as a passive cooling strategy. Its effectiveness is defined with maximum dry bulb

temperature difference that is as much as 16.7 °C above the comfort high and the dew point

temperature limits at the top and bottom of the comfort zone (Climate Consultant 6.0 2016).

Climate-file based analysis methods calculate ventilation cooling potential by estimating indoor

air movement for direct physiological cooling. Results are shown on psychrometric charts where

temperature and humidity values of analyzed hours are plotted. In the case of Climate Consultant,

this method accounts for hours where there is sufficient indoor air velocity and zone of

effectiveness is defined by a minimum air velocity to affect comfort, usually at least 0.2 m/s

(Climate Consultant 6.0 Documentation). The underlying assumption is that with effective daytime

cross-ventilation, the indoor air temperature tends to track the outdoor level along with higher

indoor airspeed. Therefore, the temperature limit of comfort ventilation applicability is the comfort

limit at the enhanced airspeed at any region or season (Givoni 1998). The quantitative effect of

convective cooling was studied extensively by Givoni at the Institute for Desert Research of Ben

Gurion University in Israel and at the University of California, Los Angeles (Givoni 1992).

There are two important limitations of this method that could cause errors on cooling ventilation

predictions. First, the comfort zone defined in Bioclimatic-based analysis do not align with comfort

zones defined in ASHRAE Standards 55. Hence, when users switch to detailed studies using

simulation tools and comfort standards, there is a high probability that the dynamic simulation

results are inconsistent with design concepts developed during early stages. Second, extended

comfort zones by the design strategies including cooling ventilation and thermal mass are shown

to improve comfort in all instances. The influence of the different strategies on each other when

implemented at the same time is not well explained. A very good example is the internal heat gain

zone that is defined only by a balance point temperature below which heating is needed. This

approach neglects the effects of internal heat gain during hours of high temperature when

mechanical cooling is required. Furthermore, ventilation heat loss, which results in effective

temperature reduction, is not considered with physiological cooling in the ventilation cooling

strategy. Therefore, identifying comfort ventilation potential for building programs with different

internal gains and envelope performances becomes challenging when using climate-file based

analysis.

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Figure 15: CBE Thermal Comfort Tool.

For the ASHRAE Standard 55-2010 Adaptive Comfort model (de Dear and Brager 1998), the comfort zone is

represented with indoor operative temperature as ordinate and prevailing mean outdoor temperature as abscissa.

The CBE Thermal Comfort Tool for ASHRAE-55 (see figure above) is an application that

provides a good alternative for cooling ventilation potential calculation. Designers can use this

application during the programming and schematic design phases to assess different thermal

control strategies including natural ventilation and elevated air speed (Schiavon et al 2014).

However, users can only calculate results for a single point in time by defining indoor air

temperature, mean radiant temperature, prevailing mean outdoor temperature and air speed. This

requires users to know indoor and outdoor conditions before conducting the analysis, and users

cannot run annual analysis in contrast to commonly used climate-file and simulation based

methods.

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3 C L I M A +

CLIMA+ is an integrated method proposed for predicting potential of natural ventilation that is

quick to use in comparison to detailed energy-performance simulation methods that are undertaken

by experts. It provides users with reliable recommendations by incorporating comprehensive

evaluations of comfort conditions based on current standards and studies. The analytical

computations in CLIMA+ are in two phases: using climate file and climate box simulation. The

two methods consider the coupling of natural ventilation and thermal mass.

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Figure 16 The effect of the rate of natural ventilation on thermal mass buffering

The result of thermal mass and natural ventilation coupling is regulated by the amount of natural ventilation rate

permitted.

3.1 Method for Natural Ventilation Potential Prediction

CLIMA+ promotes two analysis phases. In the first phase, a quick climate data based natural

ventilation prediction is reported based on selected parameters to represent natural ventilation and

thermal mass coupling. In the second phase, an additional step with a quick simulation of a single-

zone thermal model is used to predict overheated hours. These two phases are discussed in length

in the following sub-sections.

33

Figure 17 The components of CLIMA+ natural ventilation prediction method.

The highlighted section of the figure is showing Phase I.

3.1.1 Phase I- Using Climate Analysis

Climate-file based analysis is commonly used in the development of building strategies and

prediction of building performance. The method is promoted largely in standards related to

buildings and environment. ASHRAE 169: Climate Data for Building Design Standards provides

recognized climatic data for use in buildings and related equipment standards (ASHRAE 169 2013).

This standard provides a normative appendix that contains data for 5,564 U.S, Canadian, and

international locations that can be used for climatic design and definition of climatic zones

(ASHRAE 169 2013). Another standard CIBSI Guide A: Environmental Design provides the basic

weather and solar data required for manual calculations of heating and cooling loads in the UK

and Europe. In addition, CIBSI Guide A and ASHRAE 55 present comfort requirements using both

the PMV/PPD method and the adaptive comfort approach for free-running buildings. However,

these provisions do not layout a comprehensive methodology for predicting natural ventilation

potential using a climate data.

The author developed a simplified numerical calculation method on outdoor hourly temperature

and humidity to predict the potential of thermal mass and natural ventilation in improving thermal

comfort. Four main parameters to approximate ventilation scenarios and thermal mass coupling

are defined. These are the parameters to predict direct natural ventilation with physiological

cooling, buoyancy ventilation, thermal mass buffering with high and low ventilation rates. A

comparison of 20 different climates using the four parameters showed significant variations among

different climatic conditions. The method is repeated for 2,450 cities and the natural ventilation

potential predictions are mapped globally. The resulting interactive global map is hosted on the

web for public access. Please visit http://www.mit.edu/~aarsano/

34

Figure 18 The coupling of natural ventilation and thermal mass

The two charts illustrate the coupling of natural ventilation and thermal mass based on the work of Holford and

Woods.

Coupling Natural Ventilation and Thermal Mass

Holford and Woods (2006) had identified the following three important constituents and they are

used in this manuscript to discuss the proposed methodology. The time for the heat exchange

between the effective thermal mass and the air, the time for the natural ventilation to replace the

air in the space with air from the environment and the period of the diurnal oscillations of the

environment. Depending on the ventilation rate, the difference between the indoor and outdoor

temperature can be calculated. The indoor air temperature becomes very close to the outdoor air

temperature when high ventilation is permitted because internal heat loads are continuously

removed and thermal mass buffering effect is reduced. On the other hand, when ventilation rate is

35

low, indoor air temperature will be mainly affected by internal heat gains and the interaction with

the thermal mass.

The illustration in Figure 18 shows the coupling effect of natural ventilation and thermal mass

using the tool written by Salmaan Craig with the Cumulative Distribution Function (CDF) based

on the study presented by Holford and Woods. It is worth noting that Holford and Woods have

neglected internal thermal gains in the main simplification of the work in order to derive insight

into the principles of heat exchange in the building design.

The extended Adaptive Comfort Standard sets acceptable boundary conditions for thermal comfort

taking into account effects of elevated air speed. Acceptable humidity level is defined based on

the literature and standards review that is presented in section 2.1. The comfort conditions for

multiple climates are then predicted using a python-script routine. The physical considerations

underlying the four natural ventilation and thermal mass potential-prediction parameters are

discussed in the following subsection.

Direct natural ventilation potential and physiological cooling

The outdoor hourly air temperatures are evaluated if they are within the upper and lower limits of

the adaptive comfort range as provided in ASHRAE 55’s Adaptive Comfort Standard. Similarly,

the hourly relative humidity (RH) values are evaluated if they are below 85%. This parameter

assumes that the indoor air temperature closely follows the outdoor air temperature because high

ventilation rate is promoted. The comfort hours by physiological cooling that are affected by

elevated air speed are added in the direct natural ventilation potential predicted. ASHRAE 55-2013

permits the acceptable adaptive comfort range upper limit to be increased by 2.2 °C when the

average air speed is 1.2 m/s for occupant-controlled, naturally conditioned spaces (ASHRAE 55

2013).

Buoyancy ventilation potential

The buoyancy ventilation potential is calculated based on the assumption that the indoor air

temperature shall be kept at least 2k higher than the outdoor air temperature to maintain a minimum

temperature difference that drives outdoor air to flow into the space. Hence, the 80% upper and

lower acceptability limits given for indoor operative temperatures in the Adaptive Comfort

Standard are reduced by 2 K. The adjusted acceptability limits are then used to evaluate whether

the hourly outdoor air temperatures are within the expected temperature range so that buoyancy

ventilation is enhanced. This parameter considers the hourly indoor operative temperature to

remain above the outdoor air temperature. The natural ventilation air-change rate is regulated so

that it removes only part of the heat gained due to internal loads and solar radiation.

Thermal mass buffering

An ideal thermal mass buffering would result in indoor air temperature following closely the mean

outdoor temperature (Figure 18). The outdoor running mean temperature is considered as the

predicted indoor operative temperature as a result of thermal mass buffering. This outdoor running

mean temperature is also used in the Adaptive Comfort Standard and it is the average temperature

of the past 7 to 30 days. A detailed calculation method for the outdoor running mean is provided

in the ASHRAE and CIBSI standards and it is discussed in Section 2.1.

36

Holford and Woods have shown that temperature attenuation achieved with moderate and heavy

constructions in naturally ventilated buildings would range between 6.7 and 26 hours for

convection to affect mass temperature. This time lag caused by thermal mass is considered by

representing the predicted indoor operative temperature by the outdoor running mean temperature

rather than the mean temperature of a single day. This works for construction systems that have

insulation as required by building energy standards such as ASHRAE 90.1. The internal thermal

mass is exposed to the interior air temperature and is affected by outdoor air only during natural

ventilation.

The parameter to predict the effectiveness of thermal mass buffering is defined as the number of

hours where the predicted indoor operative temperature is within adaptive comfort range as a result

of thermal mass buffering in the naturally ventilated building.

Figure 19 Phase I study for Phoenix.

Outdoor air temperature from climatic data is evaluated based on the adaptive comfort standards requirements.

Thermal mass passive heating and cooling potential

When outdoor temperature is above or below acceptable thermal comfort limits, thermal mass can

be used to condition indoor air by convection and radiation. In a given climate where outdoor dry

bulb temperature goes lower than 10 °C, which is the lowest threshold defined by ASHRAE 55’s

Adaptive Comfort Standard, thermal mass can be used to store solar energy or heat from other heat

Predicted indoor temperature

With low ventilation rate

Adaptive comfort range

Outdoor temperature

Predicted indoor temperature

With high ventilation rate

Tem

per

ature

in 0

C

37

sources. Designing thermal mass for solar exposure in cold climates would help reduce heating

energy loads and this potential is calculated by adding all hours where the outdoor running mean

falls below the lower limit of adaptive comfort standard’s 80% acceptability range. Applying

similar calculation method but for overheated hours, the potential of pre-cooled thermal mass is

calculated by adding hours which are above the upper limit of adaptive comfort standard’s 80%

acceptability range.

Limitation of CLIMA+ Phase I

The current model for climate file based prediction of natural ventilation considers the high or the

low ventilation assumptions that are applied for all hours of the year. However most climates could

have optimized solutions by combining both high and low ventilation rates depending on outdoor

conditions of each hour or day. The four modes of coupling natural ventilation and thermal mass

discussed in the section above will be studied further to optimize their integration in a given

climate.

Potential extension of the

adaptive comfort range

Adaptive comfort range

Outdoor temperature

Predicted ideal time for a different ventilation method

Tem

per

ature

in 0

C

1 2

1

3

1

4

1

5

1

Figure 20 Potential application of different natural ventilation methods in

for different times of a year based on outdoor temperature for the climate of Phoenix. Parts 1 and 5 have cold

hours limiting potential ventilation hours. On the other hand, parts 2 and 4 have better potential for direct

ventilation because of the hours of temperature within the adaptive comfort range.

38

Natural Ventilation Potential for 20 Selected Climates

The 20 different climates that are used to study the natural ventilation prediction parameters are

selected from the commercial and residential reference buildings provided by the US Department

of Energy (DOE). They represent climates ranging from extreme cold to extreme hot.

The predicted direct ventilation, buoyancy ventilation and thermal mass buffering for high and low

ventilation scenarios are compared for the 20 selected climates. Direct ventilation and

physiological cooling improve comfort in humid climates such as Miami and Mumbai where the

diurnal temperature fluctuation is relatively small and most of hourly temperatures are within the

adaptive comfort range. In this case, the indoor air temperature is considered to closely follow the

outdoor temperature where by internal heat gain is continuously removed with free running

ventilation. Temporal plots of the 20 climates are shown in Figure 19.

For the case of buoyancy ventilation, the primary driving force for air change rates is temperature

difference of at least 2 K and such a difference is maintained by restricting natural ventilation rate.

Temperate and cold climates such as Lisbon and San Francisco have better potential for buoyancy

ventilation than direct ventilation.

0 2000 4000 6000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

Tel Aviv

Chicago

El Paso

Lisbon

Boston

Burlington

Duluth

Minot

Los Angeles

Boise

Albuquerque

Salem

SanFrancisco

Vancouver

TM Buffering (Low Ventilation)

TM Buffering (High Ventilation)

0 2000 4000 6000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

Tel Aviv

Chicago

El Paso

Lisbon

Boston

Burlington

Duluth

Minot

Los Angeles

Boise

Albuquerque

Salem

SanFrancisco

Vancouver

Direct Ventilation with Physiological Cooling

Buoyancy

Humidity

0 2000 4000 6000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

Tel Aviv

Chicago

El Paso

Lisbon

Boston

Burlington

Duluth

Minot

Los Angeles

Boise

Albuquerque

Salem

SanFrancisco

Vancouver

TM Passive Cooling Potential

TM Passive Heating Potential

Figure 21 compared for 20 selected climates.

Direct ventilation, buoyancy ventilation and thermal mass buffering potentials

39

Physiological cooling adds about 500 or more comfort hours in the hot to warm climates such as

Riyadh, Mumbai, Miami, Houston and Phoenix. For climates where there are high daily

temperature changes thermal mass buffers indoor air from the outdoor air fluctuations above and

below the adaptive comfort range and increases number of comfortable hours. Thermal mass adds

about a thousand comfortable hours in Albuquerque where significant number of hours with

outdoor temperatures that are outside of the adaptive comfort limits.

Thermal mass buffering has different results when combined with high and low natural ventilation

rates. In the case of Mumbai and Miami thermal mass buffering is effective when natural

ventilation is not restricted. Annual temporal maps for these climates as illustrated in Figure 19

show that thermal mass buffering is the preferred strategy when indoor air temperature is close to

the outdoor running mean temperature. On the other hand, in the colder and the temperate climates

such as Lisbon and Albuquerque thermal mass buffering is effective with limited ventilation rate.

In this case indoor air temperature is higher than outdoor air temperature and hence it is within the

adaptive comfort range.

In hot climates such as Riyadh and Kuwait, that have cold winter seasons with temperatures below

the adaptive comfort lower limit, thermal mass has the potential to reduce both heating and cooling

energy loads. On the other hand, for predominantly hot to warm climates of Mumbai and Miami,

thermal mass can be cooled to attenuate indoor air temperature and increase comfort hours. Cold

and temperate climates benefit greatly from thermal mass by storing solar energy or other form of

heat energy.

40

Figure 22 The components of CLIMA+ natural ventilation prediction method.

The highlighted section of the figure is showing Phase II.

3.1.2 Phase II- Using Climate Box Simulation

This section presents an integrated method where a simplified simulation of a climate box is

performed to calculate operative temperature for a generic well-ventilated single zone building.

The predicted number of overheated hours for the climate zone is calculated based on the Adaptive

Comfort Standard. An additional comfort improvement that is achieved with elevated air speed is

also considered and it is termed as physiological cooling effect. The climate box (simulation

thermal zone), the assumptions for the simulation and output results of the method are discussed

in detail in the following subsections.

41

Non-geometric building template library

All non-geometric building information for construction, occupancy, internal heat loads, and

conditioning are compiled in each template based on programmatic and climatic differences. A

library that is populated with residence and office building templates is then created for the second

phase of CLIMA+. The construction requirements for both residence and office are different in

the different climate zones that are defined in ASHRAE 169 2013. Appendix B is a table with the

number of heating and cooling degree-day limits given by the standard to define each thermal

climate zone. Templates for the nine thermal climate zones are prepared to represent most climates

based on the constructions specified in ASHRAE: Energy Standard for Buildings Except Low-Rise

Residential Buildings (ANSI/ASHRAE/IES Standard 90.1-2016).

The non-geometric building template is a JSON file format that is created using Archsim which is

a Grasshopper plugin that uses the EnergyPlus engine in the 3D CAD working environment called

Rhinoceros (Rhino, Archsim 2017). The template files are integrated with a geometric information

that defines a thermal zone and intermediate data files (IDF) are created to run building

performance simulation. The geometric abstraction implemented this phase of CLIMA+ is

presented in the following subsection.

Figure 23 The nine thermal climate zones defined by ASHRAE

42

Climate box: best-case thermal energy model

As a first step, it is assumed that a user selects a specific climate file (same as for Climate

Consultant) along with a program type such as office, residential etc. Information for the latter

such as envelope materials and construction, conditioning schedules, internal loads, and ventilation

ware stored in a template library and applied to a single-zone EnergyPlus model (Figure 4). This

model is supposed to represent a “climate box”, i.e. the abstraction of a building rather than an

actual architectural design. The climate box is 10m by 10m open plan with 3m floor to ceiling

height and 30% window to wall ratio. Operable area ratio is 30% of opening area and discharge

coefficient is 0.65 giving a net area of 1.8m2 for air exchange.

Ventilation Air Change Rate (ACH) of the zone is calculated using simple wind and stack

equations implemented in Archsim based on EnergyPlus Input Output Reference

(http://archsim.com/documentation-energy-modeling/natural-ventilation/). The upper setpoint is

33.5 oC as the Adaptive Comfort Standard works if the mean monthly outdoor temperature is

between 10 oC and 33.5 oC (ANSI/ASHRAE Standard 55-2010). The lower natural ventilation

setting is adjusted to 23 oC outdoor air temperature. Indoor air speed can not be more than 0.2 m/s

for temperatures lower than 23 oC (ANSI/ASHRAE Standard 55-2010). Physiological cooling of

elevated air speed can be implemented for temperatures above 23 oC where air speeds can go up

to 0.8 m/s for office spaces and 1.2 m/s for less sedentary activity spaces such as residence

(ANSI/ASHRAE Addendum g 2016).

In addition to calculated ventilation and physiological cooling, a constant infiltration rate of 0.6

ACH is considered based on the base reference given in PNNL-18898 document prepared for the

U.S Department of Energy (PNNL-18898 2009). This infiltration rate is equivalent to 50 lit/sec

and sufficient to provide required fresh air supply for a maximum of 5 people with 10 lit/sec/person

base standard.

The climate box, being a small and very open space, is supposed to yield the maximum ventilation

cooling potential for a given program type and climate. Cross ventilation based on wind and

buoyancy ventilation are both supported. Further study is being conducted to optimize physical

definition of the climate-box and possibilities of providing user control on building parameters

such as occupancy schedules while maintaining the simplicity of the method.

Figure 24 Single zone thermal zone

is used with program and climate zone based building templates.

43

Thermal simulation

From a building physics standpoint, direct natural ventilation effects on comfort can be classified

into two different phenomena: cooling ventilation by lowering operative temperature and cooling

ventilation effected by moving air near an occupant inside a building.

Cooling ventilation by lowering operative temperature

This approach measures how much operative temperatures during overheated hours are reduced

with cooling ventilation where indoor warmer air is replaced with outdoor cooler air. Air

displacement calculation methods that naturally exchange inside air with outside air lead to

comfort improvements if outside air is cooler than inside air. In the case of buoyancy driven

ventilation, this temperature difference between inside and outside is required to initiate the air

exchange in the first place. Once the temperature difference drops below 3 K the sensible cooling

effect becomes quite small, even if air change rates as high as 5ACH can be maintained (CIBSI

AM 10). Transient thermal simulation programs such as EnergyPlus consider temperature and air

change rates. Effective reduction in overheating hours achieved by ventilation can be measured by

comparing simulation results from low and high ventilation scenarios.

Cooling ventilation by the effect of moving air (physiological cooling)

Moving air has long been used to provide comfort in warm environments. Provision for indoor air

movement was one of the wellsprings of traditional architectural design in warm regions, affecting

building form, components, and equipment over millennia (Arens et al 2009).

Design strategies and

annual results Building Program

Weather File

Figure 25 CLIMA+ user inputs

Users select the building program and upload weather file before running

EnergyPlus thermal simulation.

Figure 26 Occupancy schedules used for office and residence templates

44

Residence Office

Occupancy (no of people) 0.018 p/m2 0.062 p/m2

Equipment 5 W/m2 14 W/m2

Lighting set point 200 lx 500 lx

Electrical lighting load 1W/m2 8 W/m2

Heating set point 20 oC 20 oC

Ventilation Buoyance and wind Buoyance and wind

Figure 27 Thermal model settings

Residence and Office single zone thermal model settings for internal loads,

conditioning and ventilation defined in simulation input files.

Envelope and thermal mass properties

ASHRAE 90.1 defines construction types based on energy performance requirements and the

standard presented for the different climate zones applies for all building types except low-rise

residential building. The envelope performances for all templates are defined by U-values as

provided in ASHRAE 90.1.

Among the four construction types in the ASHRAE Energy Standard; mass, metal buildings, steel

structures and wood framed; at the current stage of the method only envelope performance value

of steel structure is used for the single zone model. The U-values range between 0.705 (climate

zone 0) and 0.212 (climate zone 8).

For each of the functions, residence and office, 18 variants of single zone energy plus intermediate

data files, IDFs are created. Envelope performance and thermal mass of the building highly

influence the effectiveness of cooling ventilation. Consequently, the 18 variants presented are

based on the 9 different envelope performances that are defined for each thermal climatic zone.

For each of the 18 templates, four different thermal mass integration options that range from high

mass (10 cm thickness) to low mass (without additional mass) are provided. The additional thermal

mass is applied on the internal surface of the climate zone’s floor. For high thermal mass

conditions, the additional 10 cm thermal mass has a volumetric heat capacity of 50 x 106 J/K.

Cold Average Hot

External Facade U-0.212 U-0.315 U-0.705

Glazing Triple-Pane Double-Pane Double-Pane

Glass Coating Low-E Low-E Low-E

Shading Internal External External

Slab Adiabatic Adiabatic Adiabatic

Ceiling/roof Adiabatic Adiabatic Adiabatic

Figure 28 Building constructions

for three different envelope performance options

45

Post processing of simulation results

Simulated results are evaluated based on the ASHRAE 55’s Adaptive Comfort Model and Elevated

Air Speed standards to calculated number of hours that fall outside of the comfort limit

(ANSI/ASHRAE/IES Standard 55-2010). In addition, indoor air humidity levels which are less

than 20% and higher than 85% RH (relative humidity percentage) are counted towards hours of

discomfort.

User inputs and strategy selection

To achieve sufficient simplicity while guaranteeing consideration of critical building parameters,

all the zone input settings are predefined for the climate box as discussed in the above section. The

user is able to run all prototypes that are defined in the IDF simulation files by selecting the

program and uploading EnergyPlus weather data for the project’s location.

As mentioned above, there are two main categories of user inputs: building preferences and

occupant preferences (Figure 6). Building preferences are given for envelope performance where

three options are provided: cold, temperate and hot climates. Furthermore, these options can be

used with base construction option for thermal mass or can be combined with high thermal mass

option where additional construction layer is introduced to augment thermal capacity of the zone.

Occupant preferences are defined for physiological cooling effects with elevated air speed and

indoor humidity levels. Under the Graphical Elevated Air Speed Method (ANSI/ASHRAE

Standard 55-2010), the required air speed for light, primarily sedentary activities may not be higher

than 0.8 m/s—although higher air speeds are acceptable when using the SET Method

(ANSI/ASHRAE Standard 55-2010, Section 5.2.3.2). In contexts where occupants are engaged in

non-sedentary activities, most commonly in residences, have a wider tolerance for higher elevated

air speed of a 1.2 m/s maximum threshold.

Envelope Thermal Mass Building Preference

Occupant Preference Indoor air speed Humidity

Figure 29 Building and occupant preferences

Designers can select building envelopes, thermal mass and indoor air

speeds from provided options.

46

User interface and visualization of results

Once all the six simulations are completed for the selected program and climate data, the interface

displays a temporal graph for the typology with the least number of overheated hours, giving a

summary of selected envelope, thermal mass definition and indoor air speed. The number of

overheated hours are shown in bold at the top-right corner of the chart. A comfort level rating

highlighting the number with green, yellow or red marks the range from comfortable to very hot.

Analysis result for the chosen set of building parameters is shown in a comprehensive time-based

chart (Figure 28). The main graph in the upper section of the interface displays operative

temperatures of all hours in dark dotted marks. Outdoor dry bulb temperature is shown in a light

grey color shade at the background to give a good sense of outdoor condition in contrast to the

indoor operative temperatures. The grey band going across all hours represents the adaptive

comfort range as defined by the ASHRAE standard 55’s adaptive comfort model. The comfort

band clearly shows when in the year thermal comfort is achieved with natural ventilation and when

it is too hot. The two horizontal bands in the lower part of the graph summarize comfortable hours

and relative humidity levels as shown in Figure 28.

Overheated hours

and comfort rating

Outdoor

temperature

Adaptive comfort

range

Indoor operative

temperature

Temperature bar:

shows hours

outside of comfort

rage Humidity bar:

shows hours

outside of comfort

rage Figure 30 Temporal chart for a residence in Phoenix

Most overheated hours are from May to September. Indoor humidity levels remain

below 85% all year round.

47

Figure 32 CLIMA+ interface 2

showing natural ventilation prediction in the first phase using climate data.

Figure 31 CLIMA+ interface 1

showing natural ventilation prediction in the first phase using climate data.

48

3.2 Integration with Design Process

The optimized template using CLIMA+ can be imported to Grasshopper by using Archsim’s Zone

component. This optimized template can then be integrated with a new design geometry. The

designer has the option to re-evaluate the performance of the design during the design process

using CLIMA+. One of the buttons in the top left corner of the interface that has a CSV file icon

is designed to import such type of EnergyPlus simulation result files (see Figures 30 and 31).

The Building Performance Simulation (BPS) engine that is used by Archsim is EnergyPlus

(Crawley et al., 2000). The journal paper by ANSI/ASHRAE (2011) has stated that EnergyPlus

has been thoroughly validated and tested in practice so that whole buildings can be modeled

reliably and in great detail (Archsim Primer). The first generation of BPS engines emerged in the

eighties and nineties to overcome limitations of the until then common steady-state single room

heat balance models. The purpose of “dynamic” models using computational heat transfer methods

such as response functions or finite-difference methods was to model transient thermal-mass

effects (Clarke, 2000).

Archsim Energy Modeling is a plugin that brings fully featured EnergyPlus simulations to

Rhino/Grasshopper and thus links the EnergyPlus simulation engine with a powerful parametric

design and CAD modeling environment. Archsim allows you to create complex multi-zone energy

models, simulate them and visualize results all within the Rhino/Grasshopper environment.

Archsim supports advanced daylighting and shading controls, ventilation modules such as wind

and stack natural ventilation, airflow-networks, simple HVAC, photovoltaics and phase changing

materials. It is typically used for rapid early design exploration where building shape, window to

wall ratios, facade and glazing systems and passive approaches such as shading and natural

ventilation potential are tested for their impact on the building environmental performance and

comfort (Archsim Primer).

49

Workflow with 3D CAD Design Environment

Figure 33 Workflow of CLIMA+ with a 3D CAD design environment.

C L I M A +

50

Figure 34 A comparison of predicted overheated hours

by Climate Consultants Psychrometric chart and the proposed method with CLIMA+

3.3 Results and Discussion

The authors have closely studied the cooling ventilation calculation methods used by climate-file

based bioclimatic charts and simulation based calculations to predict potential of natural

ventilation in a particular climate to achieve thermal comfort. The 20 different climates that are

used to study the natural ventilation prediction parameters presented in the first phase of CLIMA+

are used in this section to compare results in the second phase.

Hours of discomfort calculations are based on the extended Adaptive Comfort Model (CBE

Thermal Comfort Tool) where physiological cooling effect with elevated air speed is incorporated

to the Adaptive Comfort Model. In addition, the authors have accounted discomfort in naturally

ventilated zone caused due to high humidity where indoor air relative humidity is higher than 85%.

0 1000 2000 3000 4000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

TelAviv

Chicago

ElPaso

Lisbon

Boston

Burlington

Duluth

Minot

LosAngeles

Boise

Alburquerque

Salem

SanFrancisco

Vancouver

Climate Consultant and CLIMA+

Climate Consultant Best Residence

51

Figure 34 compares Climate Consultant’s report on overheated hours and calculated results using

the proposed method for 20 different climates. Results from Climate Consultant, best residence

and office scenarios consider high thermal mass strategy and cooling ventilation. The locations are

selected mainly from the list of DOE’s prototypes for different climates ranging from Climatic

Zone 1 (hot) to Climatic Zone 8 (cold) as referenced in ASHRAE’s construction standards. A few

more climates including Kuwait and Mumbai are added to represent wider variety of climatic

conditions.

Climate consultant considers the effect of comfort ventilation where by indoor air is completely

replaced with outdoor temperature hence indoor air temperature follows outdoor air temperature.

The underlying logic behind this climate-based analysis assumes that 100% heat and mass transfer

has taken place between indoor air and incoming outdoor air. In addition, it accounts for

Physiological cooling effect by evaluating wind speed from weather data and translating it into

indoor air speed according to the guidelines given in ASHRAE Fundamentals 2005 (Climate

Consultant Documentation: Natural Ventilation Cooling). This results in a perceived temperature

reduction of 2.5 oC for air velocity of 0.82 m/s and 3.7 oC for air velocity of 1.60 m/s (Climate

0 1000 2000 3000 4000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

TelAviv

Chicago

ElPaso

Lisbon

Boston

Burlington

Duluth

Minot

LosAngeles

Boise

Alburquerque

Salem

SanFrancisco

Vancouver

CLIMA + overheated occupied hours

Office Occ Best Residence Occ BestOffice Residence

Figure 35 Office and residence occupied hours

A comparison of overheated hours predicted by CLIMA+

52

Consultant 6.0 Documentation). As a result, climate consultant’s comfort prediction during warm

to hot seasons is calculated mainly based on outdoor conditions of air temperature, humidity and

wind speed. Effects of internal gain and solar gain are only accounted during hours of low

temperatures.

Climate Consultant considers thermal mass as a cooling design strategy independent from the

comfort ventilation. Maximum and minimum dry bulb temperatures above and below comfort

thresholds are used to evaluate each hour of each day rather than diurnal cycles. As a result,

comparison of proposed method and climate consultant shows that the latter tends to estimate

higher number of discomfort hours from overheating than simulated thermal zones with thermal

mass (See Figure 34).

The evaluation shown in Figure 35 clearly indicated that making functional distinctions is crucial

when predicting potential of ventilation cooling. In addition, it is very critical to analyze occupied

hours of the respective programs to estimate hours of discomfort. In all prototypes, the goal is to

provide maximum ventilation cooling as discussed in the methodology section. One limitation of

Climate Consultant is the absence of occupancy schedule definition except the general filtering to

select months, dates and hours of the year. At the current stage of the study presented in this paper,

residence and office prototypes are considered. Other programs including retails and

manufacturing spaces will be studied in future work.

0 1000 2000 3000 4000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

TelAviv

Chicago

ElPaso

Lisbon

Boston

Burlington

Duluth

Minot

LosAngeles

Boise

Alburquerque

Salem

SanFrancisco

Vancouver

CLIMA+ discomfort hours for residence

High Humidity High Temperature

Figure 36 A comparison of number of discomfort hours

due to high temperature and high humidity.

53

Limitation of natural ventilation cooling in different climates can be because of high humidity or

high temperature. About 100% of discomfort in the climates of Kuwait, Riyadh and Phoenix is

due to high temperature, which is above the adaptive comfort maximum threshold while in Miami,

Mumbai and Houston discomfort is due to a combination of high humidity and temperature (See

Figure 36).

The distinction between high temperature and high humidity is important in selecting natural

ventilation strategies and other complementary active systems when necessary. If the main cause

of discomfort is high outdoor temperature the goal of design will be to lower operative

temperatures. On the other hand, if the main cause of discomfort is high air humidity the strategy

will be to increase physiological cooling by enhancing air movement.

0 1000 2000 3000 4000

Kuwait

Riyadh

Mumbai

Miami

Houston

Phoenix

TelAviv

Chicago

ElPaso

Lisbon

Boston

Burlington

Duluth

Minot

LosAngeles

Boise

Alburquerque

Salem

SanFrancisco

Vancouver

CLIMA+ on thermal mass effectiveness

Low Thermal Mass High Thermal Mass

Figure 37 Effect of thermal mass

Hours of discomfort due to overheating calculated for

residence for all hours to study the effect of thermal mass

54

Designing naturally ventilated buildings with thermal mass reduces overheated hours significantly.

A comparison of residence prototypes with high and low thermal mass for the selected 20 cities is

shown in Figure 37. This allows for daytime ventilation when outdoor temperature is below

adaptive comfort’s upper threshold. Moreover, when the condition for daytime ventilation is not

met, night ventilation will be used to cool thermal mass to a lower temperature during the previous

night. With this mode of ventilation, daytime ventilation will not be allowed and the space will be

kept in comfort temperature during the day by radiation and convection from the cooled thermal

mass.

When acceptable comfort cannot be met with only natural ventilation and thermal mass, a hybrid

system shall be considered by integrating mechanical cooling and ventilation. The proposed

method gives annual building performance analysis for a given climate by indicating times in the

year where conditions are above acceptable maximum thresholds (Figure 38). Two separate bars

report overheated hours and high humidity hours. This in turn can be used to predict the need for

active cooling and ventilation to provide comfortable environment.

The first two charts at the top of Figure 38 illustrates analysis with the proposed method for high

thermal mass residence prototypes for Kuwait and Miami. Discomfort hours in naturally ventilated

space in Kuwait are due to overheating in May through August. In comparison, number of

discomfort hours in Miami is a fifth of that of Kuwait and is due to both overheating and high

humidity.

55

Kuwait (left) and Miami (right) prototypes with high thermal mass

Phoenix, residence (left) and office (right) with low thermal mass

Albuquerque, with high thermal mass (left) and with low thermal mass (right)

San Francisco, with high thermal mass (left) and with low thermal mass (right)

Figure 38 The comparisons of temporal graphs

for the climates of Kuwait, Phoenix, Albuquerque, and San Francisco

56

4 Mapping Natural Ventilation Potential Globally

By 2030, 1.1 billion more people will live on Earth – bringing the total to about 8.5 billion (Forman

et Wu 2016). Such an increase in population will result in urban expansion and more pollution,

and it will alter the built environment as well as the natural environment. The mapping of natural

ventilation potential globally shows the potential of ventilation in cities worldwide ranging from

cold to hot and from humid to dry.

Different sources of climatic data that have outdoor temperature and humidity are explored. The

environmental data presented by ASHRAE 169: Climate Data for Building Design Standards and

CIBSI Guide A: Environmental Design have been compared. However, digitally available weather

data in EPW format is chosen for this study because of its convenience for a python script based

calculation method.

Typical Meteorological Year (TMY) weather files are available for 1,600 locations (Source: Dru

Crawly et Linda Lawrie, Big Ladder Software). However, these weather files do not have sufficient

coverage in the Sub-Saharan Africa and the Latin America where cities with large number of

population are located. Additional EPW format weather files are accessed using Meteonorm

(http://www.meteonorm.com). A total of 2,450 weather files are compiled into a library to create

the global map.

The mapping is done using Data-Driven Documents (D3.js) by Mike Bostock which is a JavaScript

library for visualizing data using web standards. It includes special libraries for data mapping on

available geographical, topographical and choropleth maps. D3 creates interactive data

visualizations for the web (Murray 2013). ArcGis platforms enabled by ESRI is used to pre-

analyze some of the data on maps. The resulting interactive global map is hosted on the web for

public access. Please visit http://www.mit.edu/~aarsano/

57

Figure 39 Global maps showing natural ventilation predictions

Each of these maps show the natural ventilation prediction parameters discussed in the second section CLIMA+

Phase I. The dots on the maps represent the locations of the 2,450 cities that have accessible weather data from

EnergyPlus weather database and Meteonorm. The size of each dot represent the number of predicted natural

ventilation hours. The distribution of the variation in the size of the dotes gives insights about the dominant

predicted natural ventilation method for different regions of the globe.

58

5 Concluding Remarks

The different natural ventilation cooling potential prediction methods currently used during the

different phases of a design process of buildings can lead to inconsistent results, especially in

cooling and heating dominated climates. This may lead to confusion among design team members

and uncertainties whether natural ventilation is actually an option for a particular project. Going

forward, the method promoted in this manuscript is important for steadfast design concept

development by giving feedback on the best strategies where natural ventilation will be most

effective. Temporal visualizations of comfort indicators inform when in the year selected strategies

have achieved thermal comfort. Finally, the capability to analyze only for occupied hours of the

building or for all hours of the year helps to customize design strategies based on intended

programs of the project.

CLIMA+ has the benefit of comparing strategies by enhancing indoor air movement, improving

envelope properties and adding thermal mass. Furthermore, it shows the number of comfort hours

added by the selected strategies. In the case of climate-file based analysis using building

bioclimatic charts the application of all strategies is considered to increase comfort hours in all

climates. Nevertheless, simulation based analysis clearly shows that strategies such as improving

envelope performance and adding thermal mass do not necessarily contribute to comfort hours in

some climates. Hence, the proposed method with CLIMA+ for an early design aims to guide

designers towards reliable decisions by resolving inconsistencies during a design process.

Comparing the building templates created for residence and office programs shows that the

effectiveness of strategies differs among different climates. The templates are combinations of

high and low thermal mass for envelope performances of the 9 climate zones as defined by

ASHRAE 90.1 Energy Standard for Buildings. Designing high performance envelopes with lower

U-values in hot climates such as Kuwait, Riyadh, Mumbai, Houston and Phoenix will increase

hours of discomfort. However, adding thermal mass in these warm to hot climates will

significantly increase comfort hours.

As discussed in the third section of this manuscript, using a single zone model for evaluating

potential of natural ventilation for cooling by lowering operative temperature as well as providing

physiological cooling effect is made possible. This approach allows to account for building

envelope properties and internal loads from occupancy, equipment and lighting in contrast to other

climate-file based early design tools.

The single zone model used for the proposed method is compared with the energy model of DOE’s

middle-sized commercial prototype building in Phoenix. The simulations are done using

EnergyPlus engine and Archsim, which is a Grasshopper plugin in the 3D CAD working

environment called Rhinoceros (Rhino3D, Grasshopper3D). The validation analysis has shown

that the whole building simulation result is consistent with the proposed method.

59

5.1 Further Work

C L I M A + Additional Capabilities

Radiation analysis on vertical surfaces will be added to further enhance calculations of overheated

hours. In addition to the annual temporal chart used to show simulated results in the tool’s user

interface, a psychrometric chart will be added in the options tab to display comfort predictions.

The psychrometric chart will show comfort evaluations based on the PMV method as well as the

adaptive comfort model for the predicted indoor conditions.

Weather file morphing method for changed climate based on IPCC database will be integrated into

CLIMA+. This feature will morph existing weather data for any location to enable building

performance study under future climates (Jentsch et al). Climate data generations and morphing

for natural ventilation and building performance study purposes require availability of building

design related weather parameters. The study requires a coupling of climatic parameters such as

temperature and humidity, and building design parameters including envelope performance,

thermal mass and ventilation openings by comparing climate-file and thermodynamics based

methods. Nine climate parameters have been looked at by M.F.Jentsch et al. These parameters are

available readily in the HadCM3’s A2 model of Third Assessment Report (TAR).

Generating Non-Geometric Building Template

The climate file study proposed in CLIMA+ Phase I can be further expanded to auto-generate

building template that is customized for the selected climate. The new building template can have

heating, cooling and natural ventilation schedules optimized based on preferred strategies.

Effect of Climate Change on Natural Ventilation Potential

In higher greenhouse-gas emission scenarios, a global average 2 °C warming threshold is

likely to be crossed by 2060, whereas in a lower emissions scenario, the crossing of this

threshold is delayed by up to several decades. On regional scales, however, the 2 °C threshold

will probably be exceeded over large parts of Eurasia, North Africa and Canada by 2040 if

emissions continue to increase — well within the lifetime of many people living now (Joshi et

al 2011).

A much bigger challenge of accommodating the projected 10.9 billion people in 2100 (Gerland et

al 2014) follows the current challenge of accommodating the next billion people by 2030. The

study of natural ventilation in buildings requires considering a longer period. Such a study has to

deal with possible challenges of a changed climate in addition to population growth. Climate

research can answer questions such as how does the climate influence weather and how does the

climate affect the habitability of regions and, design research can respond to questions such as

where to build (Marotzke et al 2017).

The lifespan of a building can be different among different stakeholders involved in the

construction and operation. Roof, mechanical systems, windows, wall, claddings, structure, floor

60

and foundation have different lifetime for refurbishment. A factsheet by University College

London Faculty of Engineering sciences time generalizes life expectancy of a building to be 80

years while the other time horizon seen by energy policy is 5 to 50 years (UCL Engineering). This

calls for a careful study of building performance in relation to external environmental conditions

in current time as well as in projected period.

The global-scale land planning proposed by Forman et Wu in their publication Where to put the

next billion people has marked locations which are ‘Suitable’ and ‘Somewhat suitable’ for the next

billion people. Working towards accommodating projected global population in the 21st century

requires addressing climate change impact. Heating dominated regions will get warmer, hence

higher chance for natural ventilation. On the other hand, temperate and cooling dominated regions

could experience temperatures higher than acceptable comfort ranges reducing natural ventilation

potential. Future study will answer a much broader question: What will be the effect of climate

change on natural ventilation? Can natural ventilation enhance accommodation of the next billion

people?

61

Appendix

A. Thermal Climate Zone Definition

62

B. Temporal Charts of the Selected 20 Climates

63

64

References

CIBSI (2015). Environmental Design Guide. Guide A, 7th Edition. Chartered Institution of

Building Services Engineers, London.

CIBSI (2005). Heating, Ventilating, Air Conditioning and Refrigeration. Guide B

TU Dresden, Institut für Bauklimatik (IBK) Research for energy-optimized

construction: Projects: Therakles – Rapid individual zone simulation for thermal flows. (n.d.).

Retrieved 27 March 2017, from http://www.enob.info/en/software-and-

tools/projects/details/therakles-rapid-individual-zone-simulation-for-thermal-flows/

Arens E., S. Turner, H. Zhang, and G. Paliaga. (2009). Moving air for comfort. ASHRAE Journal,

May 51(25),8-18. https://escholarship.org/uc/item/6d94f90b

ANSI/ASHRAE/IES Standard 90.1-2013 Energy Standad for Buildings Except Low-Rise

Residential Buildings

ASHRAE (2009). ASHRAE 2009 Handbook of Fundamentals .

ASHRAE Journal (2000). Heat Gain From Office Equipment

ANSI/ASHRAE/IES Standard 169 (2013) Climatic Data for Building Design Standards

ASHRAE (2009). Handbook of Fundamentals.

ASHRAE Journal (2000). Heat Gain from Office Equipment

Climate Consultant. Accessed March 2017. http://www.energy-design-tools.aud.ucla.edu/climate-

consultant/.

Climate Consultant 6.0 (2016) User help documentation

Rhino. Accessed March 2017. https://www.rhino3d.com

Grasshopper. Accessed March 2017. http://www.grasshopper3d.com/group/archsim-energy-modeling

CBE Thermal Comfort Tool, Adaptive Method, http://comfort.cbe.berkeley.edu/

de Dear RJ and Brager GS (1998). Developing an adaptive model of thermal comfort and

preference, ASHRAE Transaction, 104, 145-167.

Gvoni B (1992). Comfort, climate analysis and building design guidelines, Energy and Buildings,

18, 11-23.

Givoni B. (1998). Climate considerations in buildings and urban design, 185-189.

Milne M, Liggett R, Benson A and Bhattacharya Y (2009). Climate Consultant 4.0 develops design

guidelines for each unique climate. In: American Solar Energy Society Meeting, .

Olgyay V. (1963). Design with Climate, A Bioclimatic Approach to Architectural Regionalism,

Princeton, NJ, Princeton University Press.

PNNL-18898 (2009). Infiltration Modeling Guidelines for Commercial Building Energy Analysis,

Pacific Northwest National Laboratory

Schiavon S., T. Hoyt, and A. Piccioli. (2014). Web application for thermal comfort visualization

and calculation according to ASHRAE Standard 55. Building Simulation, Volume 7, Issue 4,

321-334. doi.org/10.1007/s12273-013-0162-3 http://escholarship.org/uc/item/4db4q37h

LowCarbonComfort : Adaptive comfort theory and temperatures (BS EN 15251, CIBSE Guide A,

ASHRAE Standard 55-2004), free and pre cooling natural ventilation. (n.d.). Retrieved April

15, 2017, from https://www.lowcarboncomfort.com/about_this_site.php

65

Energy.Gov, Commercial Reference Buildings. Retrieved May 1, 2017, from

https://energy.gov/eere/buildings/commercial-reference-buildings

Rhino3D. Retrieved May 1, 2017, from https://www.rhino3d.com

Grasshopper3D. Retrieved May 1, 2017, from http://www.grasshopper3d.com/group/archsim-

energy-modeling

Auliciems A. and Szakolay S. Thermal Comfort, Passive and Low Energy Architecture

International (PLEA), Design Tools and Techniques, January 2007, University of Latvia.

Nicol F., Humphreys M. and Roef S. Adaptive Thermal Comfort: Principles and Practice, March

2012

Tong Z., Chen Y., Malkawi A., Liu Z., and Freeman R. Energy saving potential of natural

ventilation in China: The impact of ambient air pollution, May 2016, Applied Energy 169

(2016) 660-668

Archsim Primer: Architectural Energy Modeling. A quick start guide for Rhino/Grasshopper based

building energy simulation with Archsim and EnergyPlus. Retrieved May 1, 2017, from

https://www.gitbook.com/book/tkdogan/archsim-primer/details

Holford, J. M. et Woods, A. W. (2006). On the thermal buffering of naturally ventilated

buildings through internal thermal mass, BP Institute, University of Cambridge, Cambridge

doi:10.1017/S0022112007005320, vol. 580, pp. 3-29.

Forman, R. T. T., & Wu, J. (2016). Where to put the next billion people. Nature News,

537(7622), 608. https://doi.org/10.1038/537608a

Brager, G. S. et de Dear, R. (2001). Climate, Comfort, and Natural Ventilation: A new adaptive

comfort standard for ASHRAE Standard 55, Center for the Built Environment, University of

California, Berkeley.

Gerland, P., Raftery, A. E., Ševčíková, H., Li, N., Gu, D., Spoorenberg, T., … Wilmoth, J.

(2014). World population stabilization unlikely this century. Science, 346(6206), 234–237.

https://doi.org/10.1126/science.1257469

Craig, S. (2017). Some Ways to Contribute to Climate Research. Retrieved 15 March 2017, from

https://www.pubpub.org/pub/588623e7b8ea0300345a4726

Marotzke, J., Jakob, C., Bony, S., Dirmeyer, P. A., O’Gorman, P. A., Hawkins, E., … Tuma, M.

(2017). Climate research must sharpen its view. Nature Climate Change, 7(2), 89–91.

https://doi.org/10.1038/nclimate3206

University College London Engineering - Change the World (UCL Engineering), Life

expectancy of different types of buildings. Retrieved 15 March 2017

D3.js, Micke Bostock, https://d3js.org/

Murray, S. (2013) Interactive Data Visualization for the Web: An Introduction to Designing with

D3, O’Reilly

Joshi, M., Hawkins, E., Sutton, R., Lowe, J., & Frame, D. (2011). Projections of when

temperature change will exceed 2 °C above pre-industrial levels. Nature Climate Change, 1(8),

407–412. https://doi.org/10.1038/nclimate1261