IES VE

Integrated Environmental

Solution <Virtual Environment>

Building energy simulation tool

gbXML

How will we get geometry into IES?

ModelViewer• Solar Arc – full immersion solar penetration visualisation• Multiple default animations • Intuitive video controls, new X-Ray feature• Model Viewer – Camera Path

ApacheSim• Tabular room edit - import and export Room Data from excel• Formulae profiles - ramp, step, multi variable control using

simulation results time steps down to 1 minute• Integrated HVAC / Natural Ventilation model - no post

processing• Near Future: Optimisation

• Heating & Cooling Load Calculations

• HVAC Plant and Control Systems

• Dynamic Thermal Simulations

• Wall/Window Make-ups &

Condensation Analysis

• Energy Analysis

• CO2 Emissions Calculations

• Natural Ventilation & Mixed Mode Systems

Thermal Analysis

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

180

160

140

120

100

80

60

40

20

0

Po

we

r (M

BH

)

Date: Wed 01/Jan to Wed 31/Dec

Boilers energy: (csi - load calculations - oa off.aps) Chillers energy: (csi - load calculations - oa off.aps)

Annual Energy Consumption

Load Summary

• What is driving the building

energy consumption over the

course of the full year?

• Are external factors (building

envelope) or internal factors

(lights, equipment, people)

responsible for the building

loads?

Detailed Energy & Load Calculations

Peak daily cooling loads Daily CO2 concentrations

Comfort predictions

• How does the HVAC system and

distribution method impact

thermal comfort?

Thermal Comfort Assessment

SunCast• Full solar penetration analysis• New Feature: Solar intensity visualisation• Pre-processing simulation for Dynamic Thermal Modelling

AEC Software: MacroFlo• Calculation of infiltration based on internal /external pressure

regime + Visualisation in VistaPro• Natural ventilation assessment through windows / doors• Coupled to ApacheHVAC enables true mixed mode assessment• Utilises Performance Components: Monodraught wind-catchers

Natural Ventilation

• Predict Complex Air Flow Inside and Around Buildings

• Visual Results

• Comfort Analysis

• Ventilation Airflow Analysis

• Wind Pattern Studies

Computational Fluid Dynamics (CFD)

PMV DEFINITION

-3 COLD

-2 COOL

-1SLIGHTLY

COLD

0 NEUTRAL

+1SLIGHTLY WARM

+2 WARM

+3 HOT

Predicted Mean Vote:

An index that predicts the mean value of the votes of a group of occupants on a 7-point thermal sensation scale.

Note:

The horizontal slice shown is at a seated head-height of 4’-3.6”.

The occupied area of the laboratory is in the range of (-0.1 to -0.5).

The area in front of the fume cupboard is approximately -0.7 but this is assuming the sash is fully open and designed with a face velocity of

1.6 ft/sec.

Comfort levels: Predicted Mean Vote (PMV)

Note:

The horizontal slice shown is at a seated head-height of 5’-0”.

The occupied area of the laboratory is in the range of (11% to 7%).

The area in front of the fume cupboard is approximately 20% but this is assuming the sash is fully open and designed with a face velocity of

1.6 ft/sec.

The only other areas of high PPD are in stagnant areas of the room e.g. Corner areas.

Percentage People Dissatisfied:

An index that predicts the percentage of occupants expressing dissatisfaction with the room thermal environment.

ASHRAE 55-2004 specifies the combination of indoor space environment and personal factors that will produce thermal environment

conditions acceptable to 80% or more of the occupants within a space.

Comfort levels: Percentage People Dissatisfied (PPD)

Dry Resultant Temperature:

This is the mean temperature of the room air temperature and the mean radiant temperatures.

The upper left image shows a vertical

slice 2.8” from theexternal wall and

glazing system.

Crack flow

infiltration of cold

air shows a down-

draught falling to

the floor level.

The lower left image shows a

vertical slice 14” from the external

wall and glazing

system. Linear

slot diffusers are

supplying 80°F air

to act as a warm-

air curtain.The horizontal slice shown is at an ankle-height of 0’-3”.

The occupied area of the laboratory at this height is in the range of 64-65°F

Note:

The strategy of employing a linear slot diffuser to combat the cold air draughts of cold window surface temperature and crack flow infiltration is

not preventing cooler air temperatures at occupant’s ankles and may cause discomfort.

The crack flow of the external glazing was assumed to be a “semi-exposed wall” and was set at 12.69 cfm/ft.(in Hg) ^0.6.

Dry Resultant Temperature (DRT)

Warm convective currents from occupants rising to high level.

Fume Hood sash face velocity not to

exceed -/second.

1. A combination of cold window surface temperature and cold air infiltration cause convective currents to drop to low level.

2. The cold air accumulates and spills inwards towards the occupants.

3. The strategy of employing a linear slot diffuser to combat the cold downward draught is may cause discomfort to the occupants.

Linear slot diffusers supply velocity not to exceed -/second.

Air Velocity (m/second)

AEC Software: SimulexNEW visualisation approach

Case study: First A+ manufacture building in Lithuania

Facts about building:

Overall building area – 4674

m2

Overall volume -42000 m3

Predicted energy

consumption – 26,48 kWh/m2

of heat

By applying heat pump it

should be 5,44 kWh/m2

Targets:

• A+ energy efficiency class

• BREEAM „very good“

• Reasonable price

Geometry optimization by means ofnatural light and energy consumptiom

Initial

design:

Daylight / Energy / Cost optimized :

• Initial design had poor daylight

utilization and high artificial

lightning costs

• Reduced loads due to small

glazed area rates

• Increased glazing rates alowed to

get more daylight and reduce

artificial light consumption

• Glazing creates more solar gains,

but increases capacity

requirements

• Optimal point between glazing

and lighting consumption

Detailed shading analysis with customoverhang design

• Solar exposure was

studied

• Suitable shading

solutions was chosen

• Influence of more

expensive shading

solutions was examined

and rejected after

examining cost savings

Envelope properties optimization bymeans of energy consumption and

investment costs

• More detailed selection of envelope properties by assessing influence to

energy consumption and initial envelope costs

• Different properties for different building spaces

Influence of air permeabilityof building envelope

• Local regulations requires – 1,0 h-1 value

at 50Pa difference

Target – go below 0,6 h-1

• Preliminar studies have shown that

infiltration air change has about 34%

influence to overall heat load

• This fact helped drawn more

attention to air tightness planning

and quality checks during

construction works

Control strategies assesment for moreaccurate heat/cooling sizing aiming at optimal cost

Ventilation strategies was

assessed:

• Flow rate reduction at low

ambient temperatures

• Flow rate adjustment according

to CO2 levels

• Time scheduled pre-cooling of

office spaces

• Summer ventilation by-pass

Influence determination for:

• Set points for heating set back

strategy

• Examination of suitable dead-bands

• Multisource (panel cooling and

fancoil) cooling strategies

examination

More accurate prediction than energy certification

Purpose of energy certification procedure are to give

label to the buildings at equal boundary condition

Dynamic simulation are free for

applying custom boundaries

more suitable for each case –

user and technology heat gains,

hot water usage and shedules,

microclimate systems control

strategies and passive demand

reduction strategies

26

19,6

0

5

10

15

20

25

30

Simulated value Energy certification

Future use of simulation model

After completing construction

works model could be used for

simulation based energy audith

and fault detection after

calibrating actual model

It is possible due to installed

sub-metering devices and data

collection systems.

IES VE

Integrated Environmental

Solution <Virtual Environment>

Building energy simulation tool