AWARE P Manual

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software documentationDraft version: 2012-02-09

www.baseform.org/np4/awareApp


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AWARE-Psoftware documentation

2012

Diogo VitorinoSergio T CoelhoHelena AlegreAndr MartinsJoo Paulo LeitoMaria Santos Silva

Draft version: 2012-02-09

Acknowledgements

Te AWARE-P sofware is developed in the context o the AWARE-P project, a leading edge R&Deffort unded by the European Economic Area (Contract No. P 0043) and by the project partners.Te project was developed and co-unded by a consortium led by LNEC National CivilEngineering Laboratory (Portugal) and comprising IS Instituto Superior cnico(echnical University o Lisbon, Portugal), SINEF (Norway), Addition (Portugal) andYDreams (Portugal), as well as by ERSAR Water and Waste Services Regulator (Portugal),and by the AWARE-P end-user partners: AGS S.A., AdP Servios S.A, SMAS Oeiras &Amadora and Veolia guas de Mara.Sofware development benefited rom suggestions and contributions rom a large numbero team members and project riends, including: Adriana Cardoso, Andr Martins, AndrPina, Daniel Mendes, Didia Covas, Diogo Vitorino, Enrique Cabrera, Helena Alegre, Joo

Feliciano, Joo Paulo Leito, Joaquim Beleza, Julieta Marques, Kjersti Holte, Lus Loureiro,Lus Mamouros, Maria do Cu Almeida, Maria Santos Silva, Nelson Carrio, PedroRamalho, Pedro Rufino, Pedro Pereira, Rita Ugarelli, Rodrigo Borba, Rui Rua, Srgio Coelho and Sigurd Haskjold.

LicenseTe sofware described in this document is distributed under the GNU General PublicLicense. For urther details go to: www.baseorm.org/np4/aboutLicense.htmlFor inormation on the several components used, see the Detailed Licensing section in:www.baseorm.org/np4/awareApp

DisclaimerAlthough all efforts have been undertaken to ensure that the sofware described here iso the highest possible quality and that the results obtained are correct, the authors donot warrant the unctions contained in the program will meet your requirements or thatthe operation o the program will be uninterrupted or error-ree. Te authors are notresponsible and assume no liability or any results or any use made thereo, nor or anydamages or litigation that may result rom the use o the sofware or any purpose.Google, Chrome, Google Earth, Mozilla, WebGL, Fireox, Apple, Mac, Saari, Windows,Microsof, Word, Excel, Bing, OpenStreetMaps and all other trademarks and copyrights

mentioned herein are the property o their respective owners.


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Contents

7 AWARE-P 7 Purpose

7 Overview

8 Details

12 Usage

12 Further reading

13 See also

15 TOOLS

15 PLAN AWARE-P planning

15 Purpose

15 Overview

15 Usage

16 Further reading

16 See also

17 NETWORK EPANET

17 Purpose

17 Overview

17 Details

17 Usage

19 Further reading

20 PI PERFORMANCE INDICATORS

20 Purpose

20 Overview

20 Details

21 Usage

21 Further reading

22 See also

23 PX Performance Indices

23 Purpose

23 Overview

23 Details

24 Usage

24 Further reading

24 See also

25 FAIL Failure Analysis

25 Overview

25 Details

26 Usage

27 Further reading

27 See also

27 CIMP Component importance

27 Purpose

27 Overview

28 Details

28 Usage

28 Further reading

28 See also

29 UNMET Expected Unmet Demand

29 Purpose

29 Overview

29 Details

29 Usage

29 See also

30 IVI Value Index

30 Purpose 30 Overview

30 Details

31 Usage

31 Further reading

31 See also

32 CORE 32 Purpose

32 Overview

32 Details

34 Appendix A


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FOREWORD

his document aims at helping users understand the purpose o the AWARE-P planning sot-ware and provides guidance on how to use it. he document describes the application in gen-eral terms, beore introducing the tools that are included, and the core sotware platorm where

they exist. Each section is organized into purpose, overview, details, usage and urther reading.

he sotware is publicly available at www.baseorm.org, and can be accessed through a sim-ple ree registration procedure. It runs rom any common browser (or best results, use GoogleChrome, Mozilla Fireox or Apple Saari, on any Windows, Mac or Linux system).

Further inormation, instructional materials and videos are available at www.baseorm.org.


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AWARE-PP

Purpose

he AWARE-P inrastructure asset management (IAM) planning sotware or drinkingwater, wastewater and storm water services is an organized assessment environment whereplanning alternatives or competing projects are measured up and compared through selectedperormance, risk and cost metrics. It comprises a portolio o metrics and analysis tools thatmay be used individually or diagnosis and sensitivity gain purposes, or as part o the inte-grated planning procedure laid out by the AWARE-P IAM programme.

Overview

he inrastructure asset management approach developed in the AWARE-P project (www.aware-p.org) is a broad management and engineering process aiming at alignment o objec-tives and targets, as well as eective eedback across the various decisional levels strategic,tactical, operational (Alegre et al., 2011).

he IAM process is undamentally led by the stated objectives and by an educated choice oassessment criteria, well-chosen metrics and quantiiable targets. Based on the simple notionthat every investment in a system or any change to the way it is managed will most probablyimpact not just one, but all three o the dimensions involved perormance, risk and cost the AWARE-P approach provides an unbiased and quantiied ramework or organizing thetask o generating, comparing and selecting alternatives or system improvement.

he AWARE-P IAM planning sotware makes available a coherent set o user-conigurableassessment models related to perormance, cost and risk, which are used to evaluate user-deined alternative system modiications, planning solutions or competing projects, over a

given analysis period. Based on given planning objectives and measuring criteria, the user


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selects a set o metrics rom the sotwares metrics portolio and proceeds to evaluate eachplanning alternative at the selected time rames within the planning and analysis horizons,eeding a cubic space o planning results.

he sotwares tools may also be used in stand-alone, direct assessment mode or the astest

possible path to results, or in the context o general-purpose sensitivity gain and system di-agnosis. Examples o such uses may be: an analysis o ailures rates (Poisson and LEYP mod-els are available) and o risk o service interruption; a PI calculation (AWARE-P includes aull-ledged PI tool with the most up-to-date libraries); a water quality simulation, exploringthe impact o alternative sites or a new rechlorination acility; or a ully hydraulic-enabledinvestigation o network component importance (aka criticality).

he sotwares tools have been speciically developed to make the best available methods andanalysis algorithms accessible or eective industry usage, retaining a maximum o simplic-ity in delivering meaningul and useable results.

he AWARE-P sotware is a web-based application that may be run on public or privateserver, or as a local, stand-alone deployment. It is implemented using the open-source Base-orm development platorm and materializes as a growing set o plug-in tool modules madeavailable on that platorm, taking advantage o its user management, common data integra-tion services and next-generation 2D/3D visualization capabilities.

Details

he AWARE-P sotware provides the means to visualize, diagnose and evaluate any given

water supply, wastewater or stormwater system, through a portolio o perormance, risk andcost models, at both global and detail levels; and, i so desired, to compare a system withany number o planning alternatives or competing projects using standardized methods thatacilitate choice and decision-making both manually and with the assistance o decision-support tools tested against current or projected scenarios.

AWARE-P has essentially two main usage modes:(i) as a portfolio of assessment-oriented models and analysis tools that may be used (individually or in

combination) in order to diagnose and gain sensitivity to a system; or

(ii) supporting the AWARE-P IAM planning procedure through to the definition of a planning framework

(time horizon, metrics, alternatives) and by feeding the planning tool with metric values produced

using the tools available.

PLAN is the tool that embodies the central planning ramework o the AWARE-P inrastruc-ture asset management programme, where planning alternatives or competing projects aremeasured up and compared through selected perormance, risk and cost metrics, throughinteractive numerical and 2D/3D graphical inormation display.

AWARE-P hosts a growing number o plug-in tools that are as eective at producing metricsthat eed PLAN, as they are tailored or stand-alone usage, as ully-ledged analysis algo-rithms and models. he range o metrics-producing tools that are currently available, and

whose details are described urther along in this document, include:


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PI Performance Indicators, quantitative assessment of the efficiency or effectiveness of a system

through the calculation of performance indicators based on state-of-the-art, standardized PI librar-

ies as well as user-developed or customized ones.

PX Performance Indices, technical performance metrics based on the values of certain features

or state variables of water supply and waste/stormwater networks. The indices measure perform-

ance concepts related to level-of-service, network effectiveness and efficiency.

FAIL using models such as Poisson and LEYP, prediction of future pipe or sewer failures for a given

network, e.g. in the context of estimating risk or cost metrics, based on an organized failure history

in the form of work orders and pipe data records.

CIMP calculates a component importance metric for each individual pipe in a network, based on

the impact of its failure on nodal consumption. The measure is computed based on the networks

hydraulic model, using full simulation capabilities.

UNMET calculates a service interruption risk metric expressed as the expected volume of unmet

demand in a system over one year, given the expected number of outages for each pipe, the aver-

age downtime per pipe outage, and the component importance of each pipe, expressed in terms of

unmet demand; system pipes are ranked accordingly.

IVI Infrastructure Value Index, representing the ageing degree of an infrastructure, calculated

through the ratio between the current value and the replacement value of the infrastructure.

NETWORK-EPANET an efficient, Java-implemented Epanet simulation engine and natively inte-

grated MSX library, for full-range hydraulic and water quality network simulation. It takes advantage

of Baseform Cores NETWORK and its 2D / 3D network and results visualization.


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Systems, not just collections of assets

he NEWORK tool is o crucial importance in the sense that it relates to one very impor-tant eature o the sotware and o the AWARE-P IAM approach: its ocus on evaluatingwater networks as systems rather than as collections o independent assets. For this reason,

and whenever needed, the available range o assessment models and methods draws on thecapability to simulate system behavior, either in simpliied terms o by drawing support romnetwork simulators such as Epanet.

he entire set o visualization and analysis tools is available or exploratory use without hav-ing to ollow a predeined project-driven script. From this viewpoint, the sotware is akin toa wide-ranging, system modeling sotware, suited to what-i and sensitivity analyses and togeneral system modeling.

Planning approach: the AWARE-P IAM programme

Good IAM is about inding the best possible balance o perormance, risk and costs over along-term planning horizon. here are many progression paths that improve an urban watersystems service perormance or help control risks such as interruption o supply or waterquality incidents, and there will be a certain combination o interventions that will maxi-mize the beneit o a given amount o investment. It is vital that many diverse alternativesolutions to improving the system are explored and compared, on a quantiiable and stand-ardized basis.

AWARE-P has deined both a language anda complete IAM programme to achieve that

goal. he inrastructure asset managementapproach developed in the AWARE-P projectis a broad management process that address-es the need or a plan-do-check-act (PDCA)philosophy at the various decisional levelsin a utility strategic, tactical, operational aiming at alignment o objectives, metricsand targets, as well as solid eedback acrosslevels (Alegre et al., 2011). his concept per-meates the planning processes at each o thelevels, through the PDCA-inspired loop illus-trated here.

he IAM process is undamentally led by the stated objectives, and by an educated choiceo assessment criteria, metrics and quantiiable targets. his is particularly evident at thestrategic and tactical levels, the latter being the prime ield o application or the sotwaredescribed here.

Producing the plan is a problem-driven process, with a strong emphasis on thorough diagno-sis in order to identiy and assess the systems main issues and shortcomings, in view o theset targets, and to help decide where and how to act. Diagnosing and assessing a water supply,

wastewater or stormwater system, over given time horizons (at least the planning horizon


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Usage

AWARE-P is accessed as a regular website, using any common web browser, (1)by addressinga public www link (public versions), a private or enterprise server, or a local (stand-alone)installation server. Versions where user-management has been activated will require a log in.

A general introduction to the principles and usage concepts behind the Core platorm, wherethe application is based, is given in the CORE section.

he sotwares environment includes a main menu on the let side, and an expandable mainwindow. he main menu groups the DAA manager and the PLAN and NEWORK ocalpoints; the Perormance, Risk and Cost model sections; and housekeeping core tools such asthe User Manager and Data ype Manager.(2)

Data is managed, imported and exported through the DAA manager, which is in manyways a starting point or exploring and interacting with the sotwares environment. here

is a ile system organized in olders and iles. Files may be added (uploaded), while new ilesare created through adding a pre-deined data table. he sotware is used by adding and/ormanaging data iles through the DAA manager, and then using those iles in the variousanalysis modules available.

Application modules are implemented as individual plug-ins, taking advantage o the plat-orms inrastructure (DAA manager, User Manager, Data ype Manager). he anchormodules, natively present in AWARE-P, are PLAN and the core NEWORK tool. he latteris the main vehicle or the sotware to interact with, and express results relative to, the waternetwork. he target o the AWARE-P analysis is the PLAN tool.

he metrics used in PLAN are grouped in the Perormance, Risk and Cost sections o themain menu. Each o those tools may be used independently. Please reer to the appropriatesections or urther explanation.

Further reading

Alegre, H., Almeida, M.C., Covas, D.I.C., Cardoso, M.A., Coelho, S.T. (2011). Integratedapproach for infrastructure asset management of urban water systems. Proc. IWA LESAM2011, Germany.

Alegre, H., Covas, D.(2010). Water supply infrastructure asset management a rehabilita-tion-based approach. (in Portuguese). echnical Guide no.16. ERSAR, LNEC, IS, Lisboa,472 pp. (ISBN: 978-989-8360-04-5).

1. In order to make ull use o the 3D visualization capabilities on oer, the Google Earth browserplug-in should be instal led. Additionally, WebGL-capable browsers, such as Google Chrome, MozillaFireox or Apple Saari, should have that eature enabled.

2. Available to system administrators.


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Almeida, M. C., Leito, J. P., Martins, A. (2011). Incorporating risk in infrastructure assetmanagement of urban water systems.Urban Water (submitted).

AWARE-P(2011). www.aware-p.org

Marques, M. J., Saramago, A. P., Silva, M. H., Paiva, C., Coelho, S., Pina, A., Oliveira, S.C., Teixeira, J. P., Camacho, P. A., Leito, J. P., Coelho, S. T.(2011). Rehabilitation in Oeiras& Amadora: a practical approach. Proc. IWA LESAM 2011, Germany.

See also

PLAN AWARE-P Planning

NETWORK-EPANET

PI Performance Indicators

PX Performance Indices

FAIL Failure Analysis

CIMP Component Importance

UNMET Expected Unmet Demand

IVI Infrastructure Value Index

CORE


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TOOLS

PLAN AWARE-P planning

PurposePLAN embodies the central planning

ramework o the AWARE-P inrastructureasset management methodology, whereplanning alternatives or competing projectsare measured up and compared, throughselected perormance, risk and cost metrics,using interactive numerical and 2D/3Dgraphical inormation display.

OverviewPLAN provides an organized assessment

and comparison environment where anumber o competing projects or alternativedesigns can be pitched against eachother and numerically as well as visuallycompared, with a view to supportingdecision-making.

he tool is based on the 3 main axes thatcharacterize the assessment and comparisonexercise: a number o alternatives orprojects, a set o standardized metrics anda given time rame. he latter comprisesa number o user-speciied time steps andincludes both a planning horizon (i.e., thetime rame o the intervention itsel) and ananalysis horizon (a longer time rame wherethe impact o the intervention is assessed).

he metrics selected by the user, which

may come rom the perormance, risk

and cost assessment tools present in theAWARE-P environment, or rom externalevaluations as selected by the user, arestandardized as numerical indices and thencategorized as color-coded levels, with the

emphasis on coherent deinition by theuser o the target category values. A score isalso calculated as a weighted average o theindices or each alternative, and a rankingo the alternatives is given according to thisscore.

PLAN uses a very lexible 2D/3D cubedisplay to give the user total control owhich dimensions and viewpoints arerequired or analysis.

UsagePLAN is launched rom the AWARE-P

main menu. he initial screen displays anyexisting plan iles, and gives the option tocreate a new plan. Existing plans may beedited by clicking on the ile name, skippingthe creation stage and leading directly to thetools main window.

Creating a new plan entails identiyingthe plan name, start year, planning horizon

and analysis horizon. here is optionalspace to register planning objectives andany relevant notes. Completing the requiredields and pressing Create takes the user tothe tools main window. A base alternative(named Status quo by deault, though thiscan be edited) is automatically created.

PLANs main window has 3 tabs: Data,Ranking and 3D Cube. he Data tab isessentially used to deine alternatives andmetrics, and then ill out the resultingtable with values o those metrics or eachalternative, or each o the time stepsincluded in the analysis. he Ranking tabis used or comparing and ranking thealternatives, using essentially 2D views. he3D Cube tab is used or a tridimensionaldisplay o the results (alternatives, metricsand time steps).

In the Data tab, time steps can be editedand urther adjusted by pressing the Edit

Plan button. Add Alternative gives access to


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the alternative editor, where a code, a nameand a description are illed out. Add Metricallows the user to speciy the type o metric(perormance, risk or cost) as well as a code,a name(3) and its description.

he most crucial eature in the metricspeciication is the set o values thattransorm it into a standardized index rom0 to 3, and into color-coded levels, whose

values have the ollowing meaning: (Green) 2 3: good

(Yellow) 1 2: fair

(Red) 0 1: poor

he user must deine the limits o thegreen, yellow and red bands or the metric.

A speciic weight can be assigned to thenew metric using 5 levels, rom very lowto very high (numerically, rom 0.5 to 2.0).he weight can also be speciied or eachtime step, i the importance o the metric isthought to vary with time.

he metric may also be marked asmandatory: i the metric is in the red ora particular alternative , then the wholealternative will be ranked in the red,regardless o how it ares in the other

metrics.he planning table that is displayed in the

data tab relects the standardization o themetrics values into indices, by displayingthe standardized values (0-3) in shadedtypeace under each metric value. hecolors relect the level.

Important: remember to save theplanning table each time it is edited.

he Ranking tab gives access to a color-coded display o results in 2D tables, or aspeciic year (alternatives vs. metrics), ora speciic alternative (metrics vs. years) oror a speciic metric (alternatives vs. years).Click on any alternative code, metric codeor year to launch the corresponding table.

he Ranking tab also presents thescores and the respective rankings othe alternatives, or each year or or eachmetric. Overall scores and rankings arepresented when selecting the option Overall

in the Metric drop-down menu. his score

is obtained calculating the weighted meano the standardized indices or each metricin each time step. Metrics that are deinedas mandatory are depicted by a spikycircle symbol instead o the regular circle.

Dierent weights associated to the metricsare translated by the size o the circles.

he 3D Cube tab gives access to atridimensional display cube that combinesthe 3 views. Full 3D navigation, zoomingand panning is available. Clicking on anyalternative code, on any metric code or onany year isolates the respective 2D view.

Further reading

Alegre, H., Almeida, M.C., Covas, D.I.C.,Cardoso, M.A., Coelho, S.T.(2011).Integrated approach for infrastructure assetmanagement of urban water systems.Proc.IWA LESAM 2011, Germany.

Alegre, H., Covas, D.(2010). Water supplyinrastructure asset management arehabilitation-based approach. (inPortuguese). Technical Guide no.16.ERSAR, LNEC, IS, Lisboa, 472 pp.(ISBN: 978-989-8360-04-5).

Marques, M. J., Saramago, A. P., Silva,M. H., Paiva, C., Coelho, S., Pina, A.,Oliveira, S. C., Teixeira, J. P., Camacho,P. A., Leito, J. P., Coelho, S. T.(2011).Rehabilitation in Oeiras & Amadora: a

practical approach. Proc. IWA LESAM2011, Germany.

See also PI Performance Indicators





IVI Infrastructure Value Index

3. It is good practice to include the units in themetric name, encased in brackets, so thatthey are displayed in the main planningtable e.g., Expected unmet demand (m3/

year)


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NETWORK EPANET

PurposeNEWORKEPANE offers an efficient,

Java-implemented Epanet simulation engine

and natively integrated MSX library, or ull-range hydraulic and water quality networksimulation. It takes advantage o BaseormCores NEWORK and its 2D / 3D networkand results visualization.(4)

OverviewNEWORK makes available a network

simulation engine that is a ull Java re-writeand implementation o the Epanet standard.It integrates the Epanet MSX advancedwater quality simulation library, and offersthe ull network modeling unctionality,perorming static or extended-periodsimulation on .INP standard model files.

Te simulators implementation isparticularly strong in network visualization,with the capability to seamlessly overlayon a range o publicly available maps (suchas Google, Bing or OpenStreetMaps) oron the users own maps. It takes advantageo powerul charting tools that allow orull manipulation o the networks values(parameters or simulation results), and ituses the Baseorm Cores NEWORK 2Dand 3D network displays to ull effect.

DetailsWater distribution simulation modeling

details can be ound in the extensive

documentation available or the USEPAsEpanet simulator (e.g., Rossman, 2000). Tenetwork model implemented is a rigorous,rom-scratch Java implementation o theEpanet hydraulic and water quality model

and o the Epanet MSX advanced waterquality library (EPA, 2008). A degree o

visual and unctional similarity with theoriginal was sought in integrating it in theBaseorm and NEWORK user interace,while taking advantage o the latters next-generation capabilities, such as the 3D

visualization.At the present stage, network editing is

not available and the program is essentially

intended or use with network model filesprepared elsewhere. Some simulation optionssuch as the time options or the unit systemcan be parameterized, as detailed in Usage.

UsageNEWORK opens to display a list o

the .INP network model files presentin the selected older. Clicking on a fileopens it in the main NEWORK window.Alternatively, rom the DAA manager,

clicking on a .INP file name will open apreview and offer the possibility to open themodel file directly in NEWORK.

Tree sets o unctionality are availablein separate tabs: Model, Chart & Scale,and Visualization. On the lef-hand side, anumber o collapsible drawers are used ineach tab or setting specific options.

Te Model tab displays the content andsettings o the network model containedin the .INP file opened. It offers a networksummary; a choice o base map layers, suchas Google or OpenStreetMaps; simulationtime parameterization; easy inspection oelement properties and simulation settings;and export to .INP, Excel, XML/KMLormats.

Te Chart & Scale tab is where the scalesused in displaying pipe and junction dataand results in the Visualization tab areselected. Additionally, it uses a (transposed)

cumulative distribution chart that is very


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useul in learning about the population ovalues present or the particular parameteror analysis result. Te latter are simulation-time sensitive, and thereore a timelineslider is made available.

Te Visualization tab is where 2D/3Ddisplay o the network, its parameters andmodeling or analysis results takes place. 2Dis implemented in a amiliar Epanet-likeormat; 3D is offered both in a ully embed-ded Google Earth visualization, takingadvantage o that platorms wealth o mapsand 3D eatures (such as buildings), and inBaseorms own high-perormance WebGL3D visualizer. Tis tab has a ull screen

mode or better spatial display capabilities.Te Model tabTe Model tab displays the content and

settings o the network model contained inthe .INP file opened. Te Summary gives afirst digest o the models main figures, andincludes a button or opening the file in theDAA manager (this is a recurring eaturein any application tool).

Te Layers section allows or selection owhich network eatures to display, and what

background layer to use or display - sourcesavailable include several Google and Binglayers, as well as OpenStreetMaps. In caseone o these is selected, the EPSG projectioncode(5)or the area concerned must bespecified in order to adjust or the sourcefile projection on the map.

Te Simulation section allows or thetime-related settings o the simulationto be adjusted, and the simulation to belaunched. Element Properties gives accessto the properties specified or any networkcomponent. Likewise, the Settings sectiondisplays the general simulation settings.Tough the current version does not allowor editing o these properties, the eatureis expected to be included in orthcoming

versions.However, the units system and the flow

units can be specified and changed on thefly, or any network model. Tis useul

eature does not compromise the integrity

o the .INP model file, as all necessarychanges are taken care o internally by theimplementation: the model file does notneed to be modified or the model to workin the new choice o units.

Finally, the Export section allows or theexport o model files to INP, Excel andXML ormats. Tere is also an export toExcel o the ull simulation results, as wellas o the visualization data to Google Earth/ KML. Te Excel option is particularlyuseul as a urther editing acility and modelsection workflow manipulation.

Te Chart & Scale tabTe Chart & Scale tab is where the pipe

and junction data to be displayed in thevisualizer are selected, and the respectivescales are adjusted. Tis includes networkeatures and simulation model results, aswell as results rom any o the network-leveltools present in the AWARE-P portolio,such as CIMP or PX.

A (transposed) cumulative distributionchart is used or displaying the populationo values present or the particular param-eter or (simulation time-sensitive) modeling

result. wo preset scale modes are available,by dividing the population into 25% quartilesin either the X or Y axes. Alternatively, thescale markers on the chart can be displacedindividually by the user or fine adjustments.

When adjusting the display scales ortime-sensitive results (any network simula-tion results in an extended-period simula-tion), care should be taken in selecting theappropriate time rame. For example, iinvestigating low velocities, it will be a goodidea to select a time step when demand islow, such as during nighttime.

Te Visualization tabTis is where ull 2D/3D visualization

o the network, its parameters andmodeling or analysis results takes place.Te Visualization tab has the capability todisplay network eatures and simulationmodel results, as well as results rom anyo the network-level analysis tools present

in the AWARE-P portolio, such as CIMP


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or PX. Te pipe- or node-related eature todisplay is selected in the Chart & Scale tab.

A ull screen mode is accessible rom thistab. A time-slider controls any time-sensitiveresult display, in a standard way as usually

ound in simulators. Tere is the option toplay the simulation at a video-like experi-ence, in single, double or maximum-availa-ble speed. Te parameters or results shownare those selected in Te Chart & Scale tab,with the corresponding selected scale.

Selecting 2D displays the network in anEpanet-like map. Te pipes and junctionsare color-coded to reflect the scale chosen.I displaying time-sensitive values, such

as model results in an extended-periodsimulation, the time slider should beadjusted to the desired time-step.

3D WebGL displays the network and theselected parameters in a very ast native 3D

viewer implemented using WebGL browser-side technology. A browser that enablesWebGL must be used(6)in order or thisoption to be available. In this viewer, it ispossible to use the customary pan and zoomcommands, as well as snap onto predefined

perspective views that include isometric andNorth, West, South and East.

3D Google Earth displays the networkand the selected parameters over GoogleEarth visualization. Usage is intuitive andwill be very amiliar to users o Googles

viewer. It is possible to toggle on/off therepresentation o model junctions as wellas place & road names, 3D buildings andthe zoom & scale controls. urning on3D buildings provides the most complete

viewing experience, in locations wherebuilding shapes are available in the GoogleEarth database. Note that building shapesmay need a ew more seconds to load thanthe underlying terrain view, depending oninternet connection speed, but are usuallyworth the wait in terms o the richness opresentation o analysis results. Tis viewingoption requires the Google Earth plug-in tobe installed in the browser.(7)

Further readingEPA(2008). EPANE-MSX (Multi-Species

eXtension). http://www.epa.gov/nrmrl/wswrd/dw/epanet.html#extension(accessed 2012/01/12)

Rossman, L.(2000). Epanet 2.0 UsersManual. Water Supply and WaterResources Division, National RiskManagement Research Laboratory, U.S.Environmental Protection Agency.

See also Baseform CORE




4. his model or pressurized networksis the irst in a series that will in theuture hopeully include GIS network ilecompatibility and models or wastewater/stormwater networks.

5. see www.epsg.org and www.epsg-registry.org

6. At the date o publication, browsers oeringthat eature include Fireox, Chrome,Opera and Saari.

7. Go to http://www.google.com/earth/

explore/products/plugin.html


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PurposePI allows or the quantitative assessment

o the efficiency or effectiveness o a system

through the calculation o perormance in-dicators based on state-o-the-art, standard-ized PI libraries as well as user-developed orcustomized sets.

OverviewUnderpinning the AWARE-P methodolo-

gy and embedding the principles o the ISO

standards 24510/24511/24512, the PI toolmakes available a perormance indicatorsramework or rigorous assessment o urbanwater system efficiency and effectiveness.

Te tool allows the users to select PIsrom a rather comprehensive list organizedby objectives and assessment criteria.Te main leading-edge reerence librarieso perormance indicators relevant orinrastructure asset management o urbanwater services are incorporated, includingthe International Water Association (IWAPI systems) libraries, the CARE-W andCARE-S libraries and the Portuguese WaterServices Regulator (ERSAR) libraries.Other indicators developed within theAWARE-P project are also included. Teuser is ree to urther edit the database (ullyMS Excel compliant) and customize thelist o objectives, criteria and perormanceindicators offered.

Te user creates a set o PIs, through

a shopping list mechanism intuitivesearch allows the user to filter out a givensubset o available pre-defined PIs e.g.,drinking water or wastewater, IWA/CARE/ERSAR libraries, a specific assessment

criterion, a given keyword. Once a givenPI is pre-selected, the user is shown its ulldefinition (code, name, units, concept,processing rule, comments and input

variables needed) and is given the optiono including it in the shopping list. Whenthis process is complete, a table is producedwith all the variables needed, ready ordata input reerred to one or several user-defined periods o time. Te indicators are

automatically calculated.Details

Perormance assessment reers to theevaluation o the efficiency or the effec-tiveness o a process or activity throughthe production o perormance measures.Perormance measures are the specific pa-rameters that are used to inorm the assess-ment (Matos et al., 2003, Alegre et al. 2006,Cabrera & Pardo, 2008, ISO 24510, ISO

24511, ISO 24512). Perormance indicatorsare quantitative efficiency or effectivenessmeasures or the activity o a utility.

A perormance indicator consists o avalue (resulting rom the evaluation o agiven processing rule) expressed in specificunits, and a confidence grade which indi-cates the quality o the data represented bythe indicator. Perormance Indicators aretypically expressed as ratios between varia-bles; these may be commensurate (e.g. %) ornon-commensurate (e.g. $/m3). In the lat-ter case, the denominator should representone dimension o the system (e.g. numbero service connections; total mains length;annual costs), to allow or comparisons.(8)

Te components o PI systems shouldcomply with some key requirements (ISO24500 standards). Perormance indicatorsare computed rom variables, and interpretedtaking into account explanatory actors.

An explanatory actor is any element o the


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system o perormance indicators that canbe used to explain PI values, at the analysisstage. Tis includes PI, variables, context in-ormation and other data elements not play-ing an active role beore the analysis stage.

AWARE-Ps PI tool is based on theconcept o PI libraries, coherent sets oPI developed or a specific purpose, romregulation, international statistics, globalmanagement o the utility or or a givendecision support system. Te PI toolincludes libraries rom some the worldsmost relevant PI systems in the field ourban water supply and wastewater/stormwater services, such as those

developed by the International WaterAssociation (IWA PI systems), by theCARE-W and CARE-S projects and bythe Portuguese Water Services Regulator(ERSAR), one o the most advancedregulatory systems internationally.

Besides those sets o highly validated,proessionally developed PI, the PI tool al-lows the user to modiy, customize or defineown PI or libraries, and easily share or inter-change them in the shape o Excel files.

UsageTe PI tool is started rom the main

menu. Te first step when creating a newPI analysis file is to select a PI library (e.g.IWA, AWARE-P), which contains a set operormance indicators. Te PI tool mainwindow presents all available PIs in theselected PI library, organized by the objec-tives and criteria proposed in the AWARE-Pmethodology (see page 10).

By selecting the chosen PIs, in accordancewith the objectives and assessment criteria, alist o the variables needed or their calcula-tion is automatically generated. Te ollowingstep is the definition o the timesteps, i.e. theinstants in time, in which the PIs are calculat-ed. Te value o each input variable involvedin the calculation o the PIs is introduced bythe user, or each timestep. By pressing theSave button, the sofware will calculate the

values o the PIs in each timestep.

Te PI libraries available in the sofwareare to be taken as a reerence, but the usermay decide to incorporate new objectives,assessment criteria or even perormanceindicators that may be deemed better

suited to a particular need. o do so, it ispossible to export (download) a predefinedPI library rom the Data Manager into a.xlsx file. Tis file is easily edited in Excel,enabling the user to modiy existingPIs, variables or criteria, and create newones the user must only make sure thetables ormat is preserved so that it can beimported (uploaded) again. Te ollowingpoints are important:

Each row of the Excel table represents either

a PI (pi_type as PI), an input variable (pi_type

as UI), or a criterion (pi_type as OBJ).

PI rows must present: PI as pi_type; a unique

pi_code; and a pi_rule that uses only existing

input variables (UI).

The input variables must present: UI as pi_

type; and a unique pi_code.

The criteria must present: OBJ as pi_type;

a unique pi_code; a pi_description that

indicates the set of associated PIs, identified

by their pi_code; and a pi_group specifyingthe associated objective.

Te modified xlsx file can then be imported(uploaded) into a new Perormance Indicatorlibrary, which can be created using the unc-tion Add table in the Data manager. It will beautomatically saved in the users profile.

Further readingAlegre, H.(2008). Inrastructure asset man-

agement o drinking water and wastewatersystems (in Portuguese), PI 52, LNEC,Lisbon, ISBN 9789724921341 (385 p.).

Alegre, H., Baptista, J.M., Cabrera Jr.,E., Cubillo, F., Duarte, P., Hirner,W., Merkel, W., Parena, R.(2006).Perormance indicators or water supplyservices, 2nd edition, Manual o BestPractice Series, IWA Publishing, London,ISBN: 1843390515 (305 p.).

Alegre, H.; Cabrera, E.; Merkel, W. (2008).

Current challenges in perormance


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assessment o water services. WaterUtility Management International, Vol. 3,N. 3, IWA Publishing (p. 6-7).

Alegre, H., Cabrera, E., Merkel, W.(2009). Perormance assessment

o urban utilities: the case o watersupply, wastewater and solid waste.Journal o Water Supply: Research andechnologyAQUA (JWSRAQUA-D-08-00041R1) n. 58.5/2009 (305-315 p.).

Cabrera, E., Pardo, M.A.(eds.) (2008).Perormance Assessment o UrbanInrastructure Services: drinking water,wastewater and solid waste, IWAPublishing, ISBN: 9781843391913, IWA

Publishing.ISO 24510:2007 Activities relating todrinking water and wastewater services -Guidelines or the assessment and or theimprovement o the service to users

ISO 24511:2007Activities relating todrinking water and wastewater services- Guidelines or the managemento wastewater utilities and or theassessment o wastewater services Guide

ISO 24512:2007Activities relating to

drinking water and wastewater services- Guidelines or the management odrinking water utilities and or theassessment o drinking water services.

Matos, R., Cardoso, M.A., Ashley, R,Duarte, P., Schulz A(2003). Perormanceindicators or wastewater services, Manualo Best Practice Series, IWA Publishing,ISBN: 9781900222907 (192 p.).

See also PLAN AWARE-P Planning



8. he use as denominators o variables thatmay vary substantially rom one yearto another, particularly i not under thecontrol o the undertaking, should beavoided (e.g. annual consumption, that maybe aected by weather or other external

reasons), unless the numerator varies in the

same proportion. he inormation providedby a perormance indicator is the result oa comparison (with a target value, previousvalues o the same indicator, or values o thesame indicator rom other undertakings)

(Alegre et al. 2006; ISO 24500).


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PurposeTe PX model produces technical peror-

mance metrics based on the values o certain

eatures or state variables o water supplyand waste/stormwater networks. Te indicesmeasure perormance concepts related tolevel-o-service, network effectiveness andefficiency, in areas such as hydraulic capacity,water quality, redundancy or energy behavior.

Overview

Te PX tool produces perormance indi-ces and levels by evaluating the numericalresults o network simulation models. It usesa network model file representing the appro-priate set o conditions or the analysis o thedesired network. Te PX are evaluated at thecomponent level and then generalized to anetwork-wide value.

Te PX are selected rom the AWARE-Pextensive library o water supply and waste/stormwater perormance indices, which iscontinually updated with the latest R&Dadvances in the field, and may be edited,modified and added to by the inormeduser. Examples o PX are:

compliance with a minimum required service

pressure at network nodes, by comparing

with a user-defined reference and a zero-

consumption threshold;

compliance with a maximum required travel

time at network nodes, by comparing with a

user-defined maximum reference travel time

and a given tolerance above it.

Te results are produced both at pipe/nodelevel, and at the aggregated network level.

Details

Perormance assessment in urban wa-ter systems may complement perormanceindicators (see PI in p.16) with perormanceindices and levels (Alegre & Cabrera, 2011).Perormance indices are measures result-ing rom the combination o disaggregatedperormance measures (e.g. weighted averageo perormance indicators) or rom analysistools (e.g. simulation models, statistical tools,cost efficiency methods). In general, they aim

at aggregating several perspectives into in asingle measure. Compared to perormanceindicators, their main advantages are that theycan be more aggregated measures and canbe used to assess uture scenarios (e.g. usingsimulation results or statistical analyses).

Perormance levels are measures o aqualitative nature, expressed in discretecategories (e.g. excellent, good, air, poor).In general they are adopted when the useo quantitative measures is not appropriate

(e.g. evaluation o customer satisaction bymeans o surveys) or when synthesizing andstandardizing a range o different metrics,e.g. as the basis or a decisionmakingprocess (such as can be ound in PLAN).

Te model used to calculate perormanceindices is a relatively straightorwardprocess that applies a perormance curve tothe values o a given network model result,e.g., flow velocity (Coelho, 1997, Cardosoet al., 2004; Cardoso et al., 2005). Te valuethus obtained contains a perormance

judgment, expressed on a standardized 0-3scale that implies good (2-3), adequate (1-2)and inadequate (0-1) ranges.

Te perormance curve is the unda-mental evaluation mechanism and is usu-ally designed by a knowledgeable analyst.It should reflect the users sensitivity, andis ofen parameterized to that effect. Eachperormance index is associated with one

or several ways to calculate a network-wide


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value rom the component values. Tis istermed a generalizing unction, and maytake up the orm o a weighted average or agiven percentile (including extremes) o thecomponent values.

UsagePX opens to display a list o the

perormance index tables available inthe selected older. Creating a new tablerequires selecting an uploaded Epanetmodel, where the perormance index willbe evaluated. A perormance index mustbe selected rom the available indices o theselected PX library and the name o the new

perormance index table must be filled out.Pressing Create takes the user to the mainPX window.

A brie explanation o the selectedperormance index is given at the top othe main PX window. In order to calculatethe index o each pipe, the input boxeso the reerence values must be filledout. Pressing Calculate will calculate theperormance index or each pipe/node,using the reerence values, and presented in

the 2-D network model. Te PX results canbe visualized in a 3-D network model, usingthe NEWORK tool.

New PXs can be introduced by modiyingthe PX libraries. In the Data manager it ispossible to download a Perormance Indexlibrary into a xlsx file. Opening this file willallow the user to modiy existing PXs andcreating new ones. Te modified xlsx file,with new PXs, can then be uploaded intoa Perormance Index library. As in PI, theuser must make sure that the tables or-mat is preserved so that it can be imported(uploaded) again. A new Perormance Indexlibrary can be created using the unctionAdd table o the Data manager.

Further readingAlegre, H., Cabrera, E.(2011). Perormance

Indicators. In WaterWiki, updated2011/08/05 (http://iwawaterwiki.

org/xwiki/bin/view/Articles/

PerormanceIndicators), IWA.Cardoso, M. A., Coelho, S. T., Matos,

R., Alegre, H.(2004). Perormanceassessment o water supply andwastewater systems. Urban Water Journal

1 (1), pp. 55-67.Cardoso, M. A., Coelho, S. T., Praa. P.,

Brito, R. S., Matos, J.(2005). echnicalperormance assessment o urban sewersystems. J. Perormance o ConstructedFacilities 19 (4), ASCE, pp. 339-346.

Coelho, S.T. (1997). Perormance inwater distribution: a systems approach,Research Studies Press -John Wiley &Sons, New York, E.U.A. (225 p.).

Coelho, S.T., Jowitt, P.J.(1997).Perormance analysis in waterdistribution, Computing and Controlor the Water Industry, Research StudiesPress - John Wiley & Sons, New York,E.U.A. (pp.3-20).

See also PLAN AWARE-P Planning

PI - Performance Indicators

NETWORK-EPANET


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PurposeTe aim o the FAIL model is to predict

uture pipe or sewer ailures or a given

network, e.g. in the context o estimatingrisk or cost metrics. It requires an organizedailure history to be supplied, in the orm owork orders and pipe data records, in orderto predict uture behavior.

Overviewwo alternative stochastic processes are

offered or calculating ailure predictions:the Poisson process and the Linear ExtendedYule Process (LEYP). Te probability distri-bution o the number o ailures is estimatedusing the maximum likelihood method.Te probability o ailure and the number outure ailures is predicted or each pipe, us-ing the probability unction and the expected

value o the stochastic process selected.Te ailure data must be provided in two

data tables: (i) a work orders (maintenancerecords) table; and (ii) a pipe inventory table,containing the universe o pipes that the workorders table reers to. Tis is not necessarilythe same universe o pipes i.e., network orsector that the results o the analysis will beapplied to: ofen the latter is a subset o theormer; it may be a distinct set altogether, e.g.,i the results rom one system are applied toanother where data is not available.

In the pipe inventory table, each pipe

is identified by a unique IPID code and

described by length, installation year,material and diameter. Te maintenancerecords table gathers all ailure recordso the water network. Each record mustbe associated with a pipe IPID code and

contain ailure date. Tese two tables areassociated in order to build the ailurehistory o each pipe.

Te analysis is applied to a network thatmust be specified in the orm o a networkmodel file (.INP ormat). A summary onetwork inormation is displayed, alongwith a network map.

Te NEWORK tool and its visualizationcapabilities may be invoked rom this tool,

namely as a swif shortcut to visualize theresults on 2D or 3D maps results becomeavailable or display in that tool as soon asthey are produced.

DetailsTe Poisson processA Poisson process is a counting process

in which the events occur independentlyat a constant rate and where the numbero events ollows a Poisson distribution.

It is assumed that the rate o the countingprocess is proportional to the length o eachpipe. Te ailure rate is estimated by themaximum likelihood method.

I the ailure rate were estimated using theentire data set, then it would be the sameor all pipes, no matter their properties. Inthis implementation, the data set is dividedbased on the pipe material, thus creating

various pipe material categories. Once thepipe data set is categorized, the ailure rateis estimated or each category using themaximum likelihood method.

Te predicted number o ailures in eachpipe is obtained using the expected value othe Poisson distribution, whereas the ailureprobabilities are obtained using the Poissonprobability unction.

Te Linear Extended Yule Process (LEYP)Te Linear Extended Yule Process (LEYP)

implemented in this project is a counting

process where the intensity unction


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depends on the age o the pipe, the numbero past events and a vector o covariates(potentially predictive variables, such aspipe diameter), (Le Gat, 2009; Martins,2011). Te covariates taken into account in

this implementation are the pipe diameterand the logarithm o pipe length.

Furthermore, the data set is dividedaccording to the material o each pipe. Foreach pipe material category, there will bea different set o estimated parameters.All parameters are estimated through thenumeric maximization o the log-likelihoodunction, derived by Le Gat (2009), usingthe Nelder-Mead nonlinear optimization

method. A significance test is carried out oreach estimated parameter, resorting to thelikelihood ratio test, using the Chi-squaredistribution, given by the Wilks theoremapproximation.

Once the LEYP parameters have beenestimated, the ailure probabilities oeach pipe are obtained using the NegativeBinomial probability unction, presentedin Le Gat (2009) and Martins (2011). Tepredicted number o ailures is obtained

as the expected value o the same NegativeBinomial distribution.

For urther details about the theoreticalmodels behind both processes, and theirimplementation in the sofware, please reerto Appendix A.

UsageFAIL is launched rom the Failure Analy-

sis option on the AWARE-P main menu.Te initial screen displays any existingailure analysis tables, and gives the optionto create a new table.

Creating a new ailure analysis tableentails selecting an existing work orderpipes table and an existing work orderailures table, which can be uploaded in theDAA tool. Furthermore an Epanet modelcan be selected in order to visualize theestimated ailure probabilities.

Te main FAIL window presents a pipe

inventory description; ailure estimates or

each pipe material; ailure estimates oreach pipe; and a visualization o the ailureprobabilities in the uploaded Epanet modelnetwork.

In the middle o the FAIL window an

option button allows to switch between twostochastic models to estimate the ailureprobabilities: Poisson or LEYP.

When the LEYP option is selected, undereach estimated parameter, the associatedp-value is presented. I the p-value is closeto zero, the associated parameter is moresignificant.

Selecting a network model on thelef-hand side menu (or i a model was

previously selected) will allow to visualizethe ailure estimates on a 2-D map.Importing failure dataTe ailure analysis tool requires a work

order pipes table and a work order ailurestable. Both tables can be created in theData manager tool, selecting the Add tableoption. In the Add table window the nameo the table must be filled out and a tabletype must be selected (work order pipes orwork order ailures). Pressing the button

Create will add a new empty table, with 0rows, to the specified older.

In order to import the required ailuredata, both empty tables can be downloadedas xlsx files, filled out with the necessaryinormation and uploaded next.

Te six pipe attributes to be filled out inthe work order pipes table are:

pipe_id: an alphanumeric code that identifies

uniquely each pipe of the water network.

Does not accept empty values;

material: a text value representing the pipe

material;

diameter: a numeric value representing the

pipe diameter. Does not accept empty values;

length: a numeric value representing the pipe

length in meters. Does not accept empty

values;

installation_date: a date value representing

the installation date of each pipe, in the form

day-month-year (e.g. 27-03-1994). Does not

accept empty values;


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decommissioning_date: a date value

representing the decommissioning date of

each pipe, in the form day-month-year (e.g.

27-03-1994).

Te our ailure attributes to be filled out

in the work order ailures table are: failure_date: a date value representing the

date of occurrence of each failure, in the form

day-month-year (e.g. 27-03-1994). Does not

accept empty values;

failure_type: a text value representing the

type of failure (e.g. break or leakage);

failure_duration: a numeric value representing

the downtime caused by each failure;

pipe_id: an alphanumeric code that identifies

the pipe where each failure occurred; does

not accept empty values.

Further readingLe Gat, Y. (2009). Une extension du

processus de Yule pour la modlizationstochastique des vnements rcurrents.Application aux daillances decanalizations deau sous pression. Ph.D.thesis, Cemagre Bordeaux, Paristech.

Martins, A. (2011).Stochastic models or

prediction o pipe ailures in water supplysystems. MSc thesis, Instituto Superiorcnico, echnical Univ. Lisbon, Portugal

Martins, A., Amado, C., Leito, J.P.(2011). Stochastic models or predictiono pipe ailures in water supply systems.(undergoing submission)

See also NETWORK-EPANET




CIMP Component importance

PurposeTe CIMP model calculates a component

importance metric or each individual pipe

in a network, based on the impact o itsailure on nodal consumption. Te measureis computed based on the networks hydrau-lic model, using ull simulation capabilities.Component importance (also termed hy-draulic criticality) is a crucial measure o apipes consequence in the network, used orexample in the assessment o risk associatedwith pipe ailure.

OverviewTe component importance o each indi-

vidual pipe is calculated by comparing the totaldemand that the network is hydraulically ableto satisy when that pipe is out o service, withthe total demand that the original network isable to supply. Te calculation is computedover the entire simulation duration specifiedin the network model used i.e., the unmetdemand caused by each individual pipe ailureis added or all time steps and compared withthe total supplied by the original network overthe entire simulation duration.

Component importance values are given,or each pipe, between the values o zero(i.e., i the pipe ails, all network demand isstill satisfied, over the simulation duration)and 1 (i.e., when the pipe ails, no demand issatisfied across the entire network, over the

simulation duration).


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For example: i a given pipe has acomponent importance o 0.81, it meansthat, when the pipe ails, the networkwill not be able to supply 81% o the totaldemand (i.e., only 19% will be supplied).

In addition, the actual value o the unmetdemand over the simulation period isshown or each pipe.

Te NEWORK tool and its visualizationcapabilities may be invoked rom this tool,namely as a swif shortcut to visualize theresults on 2D or 3D maps results becomeavailable or display in that tool as soon asthey are produced.

DetailsTe calculation o satisfied demand

(actual consumption) is based on a simplerelationship between available pressure andeffective consumption or the particularsimulation time step at each node. Tisrelationship is built on two user-specifiedreerence pressure values:

the Zero-Consumption Pressure is the

value below which there is no physical

consumption at the node (e.g., 8 m / 24 ft);

and the Required Minimum Pressure is the

nodal pressure value above which the nodal

demand is considered to be fully satisfied

(e.g., 25 m / 75 ft).

A linear interpolation is used or pressurevalues in between the two limits. Nodaldemand is understood as the specified base-demand multiplied by the demand patternsactor and by any applicable demandmultiplier.

Te computation is based on ull hydrau-lic response simulation as provided by thenetwork model, where the nodal pressure

values or each time step are computed orthe reduced network (i.e., with the targetpipe missing), and the expected satisfied de-mand at each node is calculated by applyingthe above relationship. Te total demand orthe network, which is used as the basis orthe ratio, is computed in the same way but

with the original network. Te current ver-

sion uses Epanets standard demand-drivenhydraulic model.

UsageCIMP is launched rom the AWARE-P

main menu. Te initial screen displays anyexisting component importance tables,and gives the option to create a new table.Creating a new component importancetable requires an uploaded Epanet model.

A brie explanation o the tool is given atthe top o the main CIMP window. In orderto calculate the component importance oeach pipe, the two input boxes Zero-Con-sumption Pressure and Required Minimum

Pressure must be filled out (deault valuesare 15.0 m and 35.0 m, respectively). Press-ing Calculate will compute the percentageo unmet demand caused by the closing oeach pipe o the network.

Further readingAndrianov, A.(2010). MIKE NE and

RELNet: which approach to reliabilityanalysis is better? Available at: http://www.vateknik.lth.se/exjobb/E315.pd

[accessed: 19 July 2010]CARE-W.,2003. ests and validation o

echnical ools. Cemagre, INSA Lyon,NNU, Brno University. Report.

CARE-W., 2004. Guidelines or the useo echnical ools. Cemagre, SINEF,INSA Lyon. Report.

Wagner, J. M., Shamir, U., Marks, D. H.(1998). Water Distribution Reliability:Simulation Methods. Journal o WaterResources Planning and Management,114(3), pp. 276-294.






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PurposeTe UNME model calculates a service

interruption risk metric expressed as theexpected volume o unmet demand in asystem over one year, given the expectednumber o outages or each pipe, theaverage downtime per pipe outage, andthe component importance o each pipe,expressed in terms o unmet demand.

OverviewTe tool combines the results o the Failure

Analysis and the Component Importancetools (although it can use ailure rate andcomponent importance tables manually pro-duced in the same ormat).

Te NEWORK tool and its visualizationcapabilities may be invoked rom this tool,namely as a swif shortcut to visualize theresults on 2D or 3D maps results becomeavailable or display in that tool as soon asthey are produced.

DetailsFor each pipe, the value o expected unmet

demand in case o outage is multiplied by thepipes expected number o ailures in 1 year,and by the average outage time (user input).

Te result is the expected value o thetotal volume o unmet demand in thenetwork caused by the individual outage o

each pipe. Tis provides a direct measure o

expected loss o service or loss o revenue (imultiplied by the unit revenue).

Usage






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IVI Value Index

PurposeTe Inrastructure Value Index represents

the ageing degree o an inrastructure, and

is calculated through the ratio between thecurrent value and the replacement value othe inrastructure.

OverviewTis tool calculates the Inrastructure

Value Index. Te process o calculation o IVIis based on individual pipe characteristics,

but the IVI is presented to the inrastructureas a whole.

Te cost data used to calculate the IVImust be provided in one data table: a costtable. Te cost table contains the characteris-tics o the inrastructure pipes that are usedto calculate the global inrastructure IVI.

In the cost table, each pipe is identifiedby a unique IPID code and described bylength, installation year, material, diameter,useul lie time and construction andreplacement cost.

For the specific case o a water supplysystem inrastructure, the analysis canalso be applied to a network that must bespecified in the orm o a network modelfile (.INP ormat). A summary o networkinormation is displayed, along with anetwork map.

Te NEWORK tool and its visualizationcapabilities may be invoked rom this tool,

namely as a swif shortcut to visualize the

results on 2D or 3D maps results becomeavailable or display in that tool as soon asthey are produced.

Details

Te IVI at a given time t (IVIt) is a per-ormance-cost measure that reflects the ageo an inrastructure. It is given by the ratiobetween the present value and the respectivereplacement value (Alegre & Covas, 2010) othe inrastructure. Tis index is particularlyadequate or establishing goals associated toinrastructural sustainability criteria.

Te calculation o the IVI starts with thecalculation o the residual lie or all pipes

and associated present value, individually.Subsequently, the global inrastructureIVI is calculated (Equation 8). Te IVI oa pipe corresponds to the percentage o itsremaining lie.

(8)

Where: IVI(t) is the dimensionless infrastructure value

index at year t (-); t is the evaluation year (year);

N is the number of infrastructure components (-);

csi,t is the replacement cost of the

infrastructure component i in year t (currency

units);

vri,t is the residual lifetime of infrastructure

component i in year t (year); and

vui is the total technical lifetime of

infrastructure component i (year).

Inrastructure value index values orstabilized inrastructures should be around0.5 (e.g. 0.4-0.6), i.e. the investmentduring a specific time period is equivalent,in average, to the depreciation o theinrastructure during the same time period.IVI values above 0.6 can mean one o theollowing:

recent infrastructures not yet stabilized;

new developments in old infrastructures; or

infrastructures where there has been a

rehabilitation over-investment.


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Low IVI values (e.g.


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CORE

PurposeTe nuclear unctionality o a platorm

that has been built rom scratch with plug-

gability and extensibility in mind, Core is theconceptual and technical conductor o everyapp and tool in the baseorm portolio.

OverviewCore is a common set o unctionality and

services used by baseorm tools, includingdata manager, data type manager, web-

enabled user interace, user manager andnetwork/data visualization environment.Every baseorm tool exists on top obaseorm core, using these eatures andworking within defined boundaries.

Core is the reason why going rom onetool to the next is a seamless experience, allinside the same platorm, always knowingwhere things are and how they behave.

Detailsools & appsBaseorm is a host o different unctional-

ity meant to work together. Baseorm toolsare plugins to the core platorm. Baseorm

applications (apps) are suites o tools work-ing together to provide added unctionality.

Using an example rom a well-knownapplication amily: Microsof Wordincludes a charting tool which is alsopresent on Microsof Excel; this tool makessense on both applications, as it provides aclear unction and works in a common wayon both.

Data manager

Data manager works like WindowsExplorer (or the Finder i you preer theMac): you have files and olders there, youcan organize, sort, rename, copy, move, etc.;all in a amiliar way.

Data manager is actually smarter thana regular file manager. Data is defined ashaving two possible orms: data files anddata tables. Data files are what you wouldexpect: images, pds, binary outputs,etc.. Data tables are seen as special data

that is organized in rows and columns asany spreadsheet; in act, baseorm corerecognizes spreadsheets as particularlyimportant tools, and allows or the importand export o any data table to and romnative MS Excel files.

It is smarter because it knows specificdata types, and acts on them in specificways. For example, it knows a data tableo the ailure analysis type (containingthe probability o ailure o each pipe oa system); it lets you look at the data in atabular way, but it also invokes the network

visualizer to show an image o the networkwith the data.

Each data type can have a specificmanager allowing you to see, create andinteract with data in a special, direct andmeaningul way. You can even use our datatype manager to extend current data typesto your specific needs, or to create new data

types altogether.


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Finally, data manager recognizes that datais interdependent. It registers that a certainfile was used to create another; it shows youthat and lets you navigate through inter-dependent files and tables. One way this

makes a lot o sense is that you can backupone data file, including its all dependentdata, analysis and tables rom one instanceto another just by clicking one button,preserving all the dependencies.

Users: accountability, security andpermissions

Te baseorm platorm is designed tobe just as good or one user as or multipleusers, and to gather as many users rom any

organization or project as possible insideevery application. Tus, it is natural to pro-vide user, security and permissions manage-ment. Baseorm core has built-in user man-agement that is both simple and powerul.Te data manager allows users to managetheir files and share permissions, and everytool has access to this security ramework.

Security also means accountability: bydeault every action is duly logged; accessand searching in these logs is given inside

the applications to super/admin users.As many other aspects o baseorm core,

user management is there but you use itonly i you need it. I all you need is just todownload an app to run on your computer,you will not be bothered by it.

Networks: infrastructures, systems anddata from a new angle

Baseorm is a platorm designed or host-ing a growing amily o tools and applica-tions or networked urban inrastructures.Tis system approach means that accessingand relating to network files is central orevery tool.

Cutting-edge research and developmentis applied to interacting with data and es-pecially with network data. You can chartany parameter, variable or assessment; youcan see your networks over any maps, or ontop o interactive Google Earth, and clickon any element; you can explore our unique

3D viewing and you can even play back and

orth with time to visualize network behavior.Whenever a new tool is developed, makingavailable new assessments or your system,it will directly benefit rom baseorms coreinteractive network visualization.

One way the baseorm platorm is movingorward is by expanding the possibledefinitions o network: currently, it hasworld-class support or hydraulic modelsusing Epanet, but incorporation o GIS andother network models is on its way..

Inclusive technology: running in thepresent and in the future

Core defines a new technology environ-ment designed or running everywhere.

Baseorm apps run on (just a ew examples): MacBook Air Any Windows PC, including netbooks such

as the Eee line

Any virtual machine, Blade or Unix server

environment

Regular or private cloud servers, such as the

Amazon EC2 platform.

Tose were examples o configurationsable to run baseormed apps. In order to usethem, all you need is a modern web browser:

Full functionality, including 3D WebGL, isavailable on Chrome, Firefox or Safari, on

Windows, Linux or Mac OS.

Main functionality also works fine in Android

smartphones and tablets, and on iPhones

and iPads.


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Further reading

Le Gat, Y. (2009). Une extension du processus de Yule pour la modlization stochastique des vnements

rcurrents. Application aux dfaillances de canalizations d'eau sous pression . Ph.D. thesis, Cemagref

Bordeaux, Paristech.Martins, A. (2011). Stochastic models for prediction of pipe failures in water supply systems . MSc thesis,

Instituto Superior Tcnico, Technical Univ. Lisbon, Portugal

Martins, A., Amado, C., Leito, J.P. (2011). Stochastic models for prediction of pipe failures in water supply

systems. (undergoing submission)


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