01791nas a2200229 4500008004100000245007800041210006900119260001200188520103000200653003101230653002001261653002001281653001401301653001801315653002701333653002701360653002801387100002001415700002301435700002101458856008201479 2019 eng d00aAssessing the Potential to Reduce U.S. Building CO2 Emissions 80% by 20500 aAssessing the Potential to Reduce US Building CO2 Emissions 80 b c08/20193 a

Buildings are responsible for 36% of CO2 emissions in the United States and will thus be integral to climate change mitigation; yet, no studies have comprehensively assessed the potential long-term CO2 emissions reductions from the U.S. buildings sector against national goals in a way that can be regularly updated in the future. We use Scout, a reproducible and granular model of U.S. building energy use, to investigate the potential for the U.S. buildings sector to reduce CO2 emissions 80% by 2050, consistent with the U.S. Mid-Century Strategy. We find that a combination of aggressive efficiency measures, electrification, and high renewable energy penetration can reduce CO2 emissions by 72%–78% relative to 2005 levels, just short of the target. Results are sufficiently disaggregated by technology and end use to inform targeted building energy policy approaches and establish a foundation for continual reassessment of technology development pathways that drive significant long-term emissions reductions.

10aBuilding energy efficiency10adecarbonization10aelectrification10aemissions10aenergy models10aenergy policy analysis10anational climate goals10apathways building stock1 aLangevin, Jared1 aHarris, Chioke, B.1 aReyna, Janet, L. uhttps://simulationresearch.lbl.gov/publications/assessing-potential-reduce-us02298nas a2200277 4500008004100000022001300041245016000054210006900214260001600283300001600299490000800315520136500323653004401688653002401732653002301756653001801779653002201797653002301819100001201842700001701854700001501871700001901886700001301905700001501918856008701933 2019 eng d a0048969700aAssessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California0 aAssessment of occupantbehaviorbased indoor air quality and its i cJan-10-2019 a1251 - 12610 v6863 a

The recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires—by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviours by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires

10acomputational fluid dynamics siumlation10ahuman exposure risk10aindoor air quality10aNAPA wildfire10aoccupant behavior10arespiratory injury1 aLuo, Na1 aWeng, Wenguo1 aXu, Xiaoyu1 aHong, Tianzhen1 aFu, Ming1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/assessment-occupant-behavior-based02102nas a2200121 4500008004100000245005000041210004600091520170800137100001701845700001901862700001401881856008501895 2017 eng d00aAn Agent-Based Stochastic Occupancy Simulator0 aAgentBased Stochastic Occupancy Simulator3 a

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with Reinhart’s LIGHTSWITCH-2002 model, (2) the random moving events (e.g., from one office to another) simulated with Wang’s homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.

1 aChen, Yixing1 aHong, Tianzhen1 aLuo, Xuan uhttps://simulationresearch.lbl.gov/publications/agent-based-stochastic-occupancy02453nas a2200253 4500008004100000245013600041210006900177260001200246300001200258490000800270520159800278653002101876653002301897653003201920653001601952653001901968653001401987653002502001653001802026100002302044700001902067700002902086856008402115 2017 eng d00aAnalysis of heating load diversity in German residential districts and implications for the application in district heating systems0 aAnalysis of heating load diversity in German residential distric c01/2017 a302-3130 v1393 a

In recent years, the application of district heating systems for the heat supply of residential districts has been increasing in Germany. Central supply systems can be very efficient due to diverse energy demand profiles which may lead to reduced installed equipment capacity. Load diversity in buildings has been investigated in former studies, especially for the electricity demand. However, little is known about the influence of single building characteristics (such as building envelope or hot water demand) on the overall heating peak load of a residential district. For measuring the diversity, the peak load ratio (PLR) index is used to represent the percentage reduction of peak load of a district system from a simple sum of individual peak loads of buildings. A total of 144 residential building load profiles have been created with the dynamic building simulation software IDA ICE for a theoretical analysis in which the PLR reaches 15%. Within this study, certain district features are identified which lead to higher diversity. Furthermore, these results are used in a district heating simulation model which confronts the possible advantage of reduced installed capacity with the practical disadvantage of heat distribution losses.  Likewise, the influence of load density and the district´s building structure can be analyzed. This study shows that especially in districts with high load density, which consist of newly constructed buildings with low supply temperature and high influence of the hot water demand, the advantages of load diversity can be exploited.

10adistrict heating10adomestic hot water10adynamic building simulation10aheat supply10aLoad diversity10apeak load10aresidential district10aspace heating1 aWeissmann, Claudia1 aHong, Tianzhen1 aGraubner, Carl-Alexander uhttps://simulationresearch.lbl.gov/publications/analysis-heating-load-diversity02592nas a2200193 4500008004100000245013700041210006900178520187800247653002902125653001202154653003302166653001502199653002202214653001602236100001702252700001902269700002202288856008802310 2017 eng d00aAutomatic Generation and Simulation of Urban Building Energy Models Based on City Datasets for City-Scale Building Retrofit Analysis0 aAutomatic Generation and Simulation of Urban Building Energy Mod3 a

Buildings in cities consume 30% to 70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23%-38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Franciso due to the city’s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

10aBuilding Energy Modeling10aCityBES10aEnergy conservation measures10aenergyplus10aRetrofit Analysis10aUrban Scale1 aChen, Yixing1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/automatic-generation-and-simulation01628nas a2200241 4500008003900000245009100039210006900130260001200199300001200211490000800223520083600231653002201067653003401089653003601123653001501159653002201174100001901196700002801215700001801243700001201261700002601273856008701299 2016 d00aAdvances in research and applications of energy-related occupant behavior in buildings0 aAdvances in research and applications of energyrelated occupant  c03/2016 a694-7020 v1163 a

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead.

10aBehavior Modeling10aBuilding design and operation10abuilding performance simulation10aenergy use10aoccupant behavior1 aHong, Tianzhen1 aTaylor-Lange, Sarah, C.1 aD'Oca, Simona1 aYan, Da1 aCorgnati, Stefano, P. uhttps://simulationresearch.lbl.gov/publications/advances-research-and-applications01736nas a2200121 4500008003900000245007500039210006900114520129700183100001701480700001401497700001901511856008401530 2016 d00aAn Agent-Based Occupancy Simulator for Building Performance Simulation0 aAgentBased Occupancy Simulator for Building Performance Simulati3 a

Traditionally, in building energy modeling (BEM) programs, occupancy inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents an agent-based occupancy simulator, which models each occupant as an agent with specified movement events and statistics of space uses. To reduce the amount of data inputs, the simulator allows users to group occupants with similar behaviors as an occupant type, and spaces with similar function as a space type. It is a web-based application with friendly graphical user interface, cloud computing, and data storage. A case study is presented to demonstrate the usage of the occupancy simulator and its integration with EnergyPlus and obFMU. It first shows the required data inputs and the results from the occupancy simulator. Then, the generated occupant schedules are used in the EnergyPlus and obFMU simulation to evaluate the impacts of occupant behavior on building energy performance. The simulation results indicate that the occupancy simulator can capture the diversity of space’s occupancy behavior rather than the static weekly profiles, and can generate realistic occupancy schedules to support building performance simulation.

1 aChen, Yixing1 aLuo, Xuan1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/agent-based-occupancy-simulator02261nas a2200241 4500008003900000245011100039210006900150260001200219520144900231653002401680653003201704653002001736653001501756653003101771653001301802100002001815700001901835700002201854700001701876700001701893700002801910856008101938 2015 d00aAccelerating the energy retrofit of commercial buildings using a database of energy efficiency performance0 aAccelerating the energy retrofit of commercial buildings using a c07/20153 a

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback.

10abuilding simulation10aEnergy conservation measure10aenergy modeling10aenergyplus10aHigh Performance computing10aretrofit1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann1 aSawaya, Geof1 aChen, Yixing1 aTaylor-Lange, Sarah, C. uhttps://simulationresearch.lbl.gov/publications/accelerating-energy-retrofit02732nas a2200265 4500008003900000245013300039210006900172260001200241300001200253490000600265520189500271653001302166653001002179653002202189653001202211653001202223100002102235700001802256700001902274700002102293700002902314700001802343700001502361856009002376 2015 d00aAssessment of the Potential to Achieve Very Low Energy Use in Public Buildings in China with Advanced Window and Shading Systems0 aAssessment of the Potential to Achieve Very Low Energy Use in Pu c05/2015 a668-6990 v53 a

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the US model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future.

System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24-66% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30-80% reductions in perimeter zone HVAC electricity use in Beijing and 18-38% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

10abuilding10aChina10aenergy efficiency10ashading10awindows1 aLee, Eleanor, S.1 aPang, Xiufeng1 aMcNeil, Andrew1 aHoffmann, Sabine1 aThanachareonkit, Anothai1 aLi, Zhengrong1 aDing, Yong uhttps://simulationresearch.lbl.gov/publications/assessment-potential-achieve-very-low01318nas a2200193 4500008003900000245006300039210006300102260002500165520071500190100002400905700001500929700001900944700002200963700002900985700002601014700002001040700001801060856004601078 2012 d00aApplication of a stochastic window use model in EnergyPlus0 aApplication of a stochastic window use model in EnergyPlus aMadison, WIc08/20123 a

Natural ventilation, used appropriately, has the potential to provide both significant HVAC energy savings, and improvements in occupant satisfaction.

Central to the development of natural ventilation models is the need to accurately represent the behavior of building occupants. The work covered in this paper describes a method of implementing a stochastic window model in EnergyPlus. Simulated window use data from three stochastic window opening models was then compared to measured window opening behavior, collected in a naturally-ventilated office in California. Recommendations regarding the selection of stochastic window use models, and their implementation in EnergyPlus, are presented.

1 aDutton, Spencer, M.1 aZhang, Hui1 aZhai, Yongchao1 aArens, Edward, A.1 aSmires, Youness, Bennani1 aBrunswick, Samuel, L.1 aKonis, Kyle, S.1 aHaves, Philip uhttps://escholarship.org/uc/item/2gm7r78300476nas a2200109 4500008004100000245011200041210006900153260001900222100001600241700002000257856008900277 2011 eng d00aAdvanced simulations of building energy and control systems with an example of chilled water plant modeling0 aAdvanced simulations of building energy and control systems with aNanjing, China1 aZuo, Wangda1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/advanced-simulations-building-energy00620nas a2200169 4500008004100000245008700041210006900128260003100197100002300228700001800251700001500269700002100284700002100305700002100326700002000347856008300367 2011 eng d00aAn Assessment of the use of Building Energy Performance Simulation in Early Design0 aAssessment of the use of Building Energy Performance Simulation  aSydney, Australiac11/20111 aBazjanac, Vladimir1 aMaile, Tobias1 aRose, Cody1 aO'Donnell, James1 aMrazovic, Natasa1 aMorrissey, Elmer1 aWelle, Benjamin uhttps://simulationresearch.lbl.gov/publications/assessment-use-building-energy00596nas a2200169 4500008004100000245008000041210006900121260000900190653003200199653001500231653002100246653001500267653001200282100001900294700002700313856008600340 2010 eng d00aAssessment of Energy Impact of Window Technologies for Commercial Buildings0 aAssessment of Energy Impact of Window Technologies for Commercia c201010abuilding energy performance10aenergyplus10ashading controls10asimulation10awindows1 aHong, Tianzhen1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/assessment-energy-impact-window-003910nas a2200229 4500008004100000245013300041210006900174260006100243300001200304490000600316520299300322653002403315653004003339653007503379653003403454653001903488653003403507653001003541100001903551700002203570856008803592 2010 eng d00aAssessment of Energy Savings Potential from the Use of Demand Control Ventilation Systems in General Office Spaces in California0 aAssessment of Energy Savings Potential from the Use of Demand Co aBerkeleybLawrence Berkeley National Laboratoryc06/2010 a117-1240 v33 a

Demand controlled ventilation (DCV) was evaluated for general office spaces in California. A medium size office building meeting the prescriptive requirements of the 2008 California building energy efficiency standards (CEC 2008) was assumed in the building energy simulations performed with the EnergyPlus program to calculate the DCV energy savings potential in five typical California climates. Three design occupancy densities and two minimum ventilation rates were used as model inputs to cover a broader range of design variations. The assumed values of minimum ventilation rates in offices without DCV, based on two different measurement methods, were 81 and 28 cfm per occupant. These rates are based on the co‐author's unpublished analyses of data from EPA's survey of 100 U.S. office buildings. These minimum ventilation rates exceed the 15 to 20 cfm per person required in most ventilation standards for offices. The cost effectiveness of applying DCV in general office spaces was estimated via a life cycle cost analyses that considered system costs and energy cost reductions.

The results of the energy modeling indicate that the energy savings potential of DCV is largest in the desert area of California (climate zone 14), followed by Mountains (climate zone 16), Central Valley (climate zone 12), North Coast (climate zone 3), and South Coast (climate zone 6).

The results of the life cycle cost analysis show DCV is cost effective for office spaces if the typical minimum ventilation rates without DCV is 81 cfm per person, except at the low design occupancy of 10 people per 1000 ft2 in climate zones 3 and 6. At the low design occupancy of 10 people per 1000 ft2, the greatest DCV life cycle cost savings is a net present value (NPV) of $0.52/ft2 in climate zone 14, followed by $0.32/ft2 in climate zone 16 and $0.19/ft2 in climate zone 12. At the medium design occupancy of 15 people per 1000 ft2, the DCV savings are higher with a NPV $0.93/ft2 in climate zone 14, followed by $0.55/ft2 in climate zone 16, $0.46/ft2 in climate zone 12, $0.30/ft2 in climate zone 3, $0.16/ft2 in climate zone 3. At the high design occupancy of 20 people per 1000 ft2, the DCV savings are even higher with a NPV $1.37/ft2 in climate zone 14, followed by $0.86/ft2 in climate zone 16, $0.84/ft2 in climate zone 3, $0.82/ft2 in climate zone 12, and $0.65/ft2 in climate zone 6.

DCV was not found to be cost effective if the typical minimum ventilation rate without DCV is 28 cfm per occupant, except at high design occupancy of 20 people per 1000 ft2 in climate zones 14 and 16.

Until the large uncertainties about the base case ventilation rates in offices without DCV are reduced, the case for requiring DCV in general office spaces will be a weak case.

10abuilding simulation10acalifornia building energy standard10aCommercial Building Ventilation and Indoor Environmental Quality Group10ademand controlled ventilation10aenergy savings10aindoor environment department10aother1 aHong, Tianzhen1 aFisk, William, J. uhttps://simulationresearch.lbl.gov/publications/assessment-energy-savings-potential00569nas a2200157 4500008004100000245006300041210006300104260003000167100001900197700001900216700002700235700002600262700001800288700001800306856008700324 2010 eng d00aAutomated Continuous Commissioning of Commercial Buildings0 aAutomated Continuous Commissioning of Commercial Buildings aWashington, D.C.c11/20101 aBailey, Trevor1 aO'Neill, Zheng1 aShashanka, Madhusudana1 aBhattacharya, Prajesh1 aHaves, Philip1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/automated-continuous-commissioning02004nas a2200301 4500008004100000022001400041245013400055210006900189260001200258300001100270490000700281520102100288653001501309653001801324653002601342653003601368653003201404653001501436653002401451100001401475700002401489700002201513700002001535700001601555700002101571700002101592856008901613 2009 eng d a1573-198700aAnisotropy invariant Reynolds stress model of turbulence (AIRSM) and its application on attached and separated wall-bounded flows0 aAnisotropy invariant Reynolds stress model of turbulence AIRSM a c07/2009 a81-1030 v833 a

Numerical predictions with a differential Reynolds stress closure, which in its original formulation explicitly takes into account possible states of turbulence on the anisotropy-invariant map, are presented. Thus the influence of anisotropy of turbulence on the modeled terms in the governing equations for the Reynolds stresses is accounted for directly. The anisotropy invariant Reynolds stress model (AIRSM) is implemented and validated in different finite-volume codes. The standard wall-function approach is employed as initial step in order to predict simple and complex wall-bounded flows undergoing large separation. Despite the use of simple wall functions, the model performed satisfactory in predicting these flows. The predictions of the AIRSM were also compared with existing Reynolds stress models and it was found that the present model results in improved convergence compared with other models. Numerical issues involved in the implementation and application of the model are also addressed.

10aAnisotrpoy10aInvariant map10aReynolds stress model10aReynolds-averaged Navier-Stokes10aSeparated wall-bounded flow10aTurbulence10aTurbulence modeling1 aKumar, V.1 aFrohnapfel, Bettina1 aJovanović, Jovan1 aBreuer, Michael1 aZuo, Wangda1 aHadzić, Ibrahim1 aLechner, Richard uhttps://simulationresearch.lbl.gov/publications/anisotropy-invariant-reynolds-stress01856nas a2200133 4500008004100000245009800041210006900139260002400208520133300232100001701565700003101582700002101613856008801634 2009 eng d00aApplication of software tools for moisture protection of buildings in different climate zones0 aApplication of software tools for moisture protection of buildin aSisimiut, Groenland3 a

The application of software tools for moisture protection of buildings in different climatic zones is demonstrated in this paper. The basics of the programs are presented together with a typical application for a problem specific for the chosen climatic zone. A 1-D calculation has been performed for tropical climate zone with the improvement of a flat roof in Bangkok as an example. For half timbered buildings, which are common in the temperate zone with the 2-D model an infill insulation and its benefits are demonstrated. Finally the combined appliance of the whole building model and the mould risk prognosis model is shown in detail as a special case for the cold climate zone: In heated buildings of cold climate zones the internal climate with its low relative humidity in wintertime often causes discomfort and health problems for the occupants. In case of using air humidifier the risk of mould growth increases. Instead of an uncontrolled humidifying of the dry air an innovativecontrol system using a thermal bridge, which switches the humidifier off when condensation occurs is presented. To quantify the improvement in the comfort while preventing the risk of mould growth for a typical building comparative calculations of the resulting inner climates and its consequences on comfort have been performed.

1 aKrus, Martin1 aNouidui, Thierry, Stephane1 aSedlbauer, Klaus uhttps://simulationresearch.lbl.gov/publications/application-software-tools-moisture00473nas a2200121 4500008003900000245008000039210006900119260001200188100001900200700002700219700002100246856008400267 2009 d00aAssessment of Energy Impact of Window Technologies for Commercial Buildings0 aAssessment of Energy Impact of Window Technologies for Commercia c10/20091 aHong, Tianzhen1 aSelkowitz, Stephen, E.1 aYazdanian, Mehry uhttps://simulationresearch.lbl.gov/publications/assessment-energy-impact-window00509nas a2200133 4500008004100000245007900041210006900120260001200189100002000201700002500221700002400246700001800270856008700288 2008 eng d00aApplication of Machine Learning in Fault Diagnostics of Mechanical Systems0 aApplication of Machine Learning in Fault Diagnostics of Mechanic c10/20081 aNajafi, Massieh1 aAuslander, David, M.1 aBartlett, Peter, L.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/application-machine-learning-fault00473nas a2200097 4500008004100000245012400041210006900165260002800234100002500262856008800287 2007 eng d00aAdvanced Zone Simulation in EnergyPlus: Incorporation of Variable Properties and Phase Change Material (PCM) Capability0 aAdvanced Zone Simulation in EnergyPlus Incorporation of Variable aBeijing, Chinac09/20071 aPedersen, Curtis, O. uhttps://simulationresearch.lbl.gov/publications/advanced-zone-simulation-energyplus00356nas a2200097 4500008004100000245004300041210004300084260002800127100001500155856008800170 2007 eng d00aAirflow Network Modeling in EnergyPlus0 aAirflow Network Modeling in EnergyPlus aBeijing, Chinac09/20071 aGu, Lixing uhttps://simulationresearch.lbl.gov/publications/airflow-network-modeling-energyplus00792nas a2200229 4500008004100000245009200041210006900133300001300202100002900215700001700244700001900261700002000280700001800300700002100318700002200339700001900361700002100380700002300401700003100424700002200455856008500477 2006 eng d00aAdvanced modeling and simulation techniques in MOSILAB: A system development case study0 aAdvanced modeling and simulation techniques in MOSILAB A system  app.63-721 aNytsch-Geusen, Christoph1 aErnst, Thilo1 aSchwarz, Peter1 aVetter, Mathias1 aHolm, Andreas1 aLeopold, Juergen1 aMattes, Alexander1 aNordwig, Andre1 aSchneider, Peter1 aWittwer, Christoph1 aNouidui, Thierry, Stephane1 aSchmidt, Gerhardt uhttps://simulationresearch.lbl.gov/publications/advanced-modeling-and-simulation00486nas a2200109 4500008004100000245010600041210006900147260003200216100001900248700002100267856008800288 2006 eng d00aAn Analysis of Building Envelope Upgrades for Residential Energy Efficiency in Hot and Humid Climates0 aAnalysis of Building Envelope Upgrades for Residential Energy Ef aCambridge, MA, USAc08/20061 aMalhotra, Mini1 aHaberl, Jeff, S. uhttps://simulationresearch.lbl.gov/publications/analysis-building-envelope-upgrades00459nas a2200109 4500008004100000245008100041210006900122260003200191100001700223700002300240856008600263 2006 eng d00aAnalysis Process for Designing Double Skin Facades and Associated Case Study0 aAnalysis Process for Designing Double Skin Facades and Associate aCambridge, MA, USAc08/20061 aDoebber, Ian1 aMcClintock, Maurya uhttps://simulationresearch.lbl.gov/publications/analysis-process-designing-double00535nas a2200133 4500008004100000245011600041210006900157260003200226100001500258700002000273700001300293700001500306856008000321 2006 eng d00aThe Application of Building Energy Simulation and Calibration in Two High-Rise Commercial Buildings in Shanghai0 aApplication of Building Energy Simulation and Calibration in Two aCambridge, MA, USAc08/20061 aPan, Yiqun1 aHuang, Zhizhong1 aWu, Gang1 aChen, Chen uhttps://simulationresearch.lbl.gov/publications/application-building-energy00480nas a2200121 4500008004100000245008900041210006900130260001200199100002400211700002500235700001500260856008300275 2006 eng d00aAssessment of the Technical Potential for Achieving Zero-Energy Commercial Buildings0 aAssessment of the Technical Potential for Achieving ZeroEnergy C c08/20061 aGriffith, Brent, T.1 aTorcellini, Paul, A.1 aRyan, John uhttps://simulationresearch.lbl.gov/publications/assessment-technical-potential00514nas a2200133 4500008004100000245006500041210006500106260003200171100002100203700002400224700001900248700002500267856008800292 2006 eng d00aAutomated Multivariate Optimization Tool for Energy Analysis0 aAutomated Multivariate Optimization Tool for Energy Analysis aCambridge, MA, USAc08/20061 aEllis, Peter, G.1 aGriffith, Brent, T.1 aLong, Nicholas1 aTorcellini, Paul, A. uhttps://simulationresearch.lbl.gov/publications/automated-multivariate-optimization00453nas a2200121 4500008004100000245007400041210006900115300001200184490000700196100002100203700001800224856008900242 2004 eng d00aANN Modeling and Self-tuning Control of the Oil Field Heating Furnace0 aANN Modeling and Selftuning Control of the Oil Field Heating Fur a338-2400 v121 aJiang, Yongcheng1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/ann-modeling-and-self-tuning-control00431nas a2200121 4500008004100000050001500041245006000056210005700116100001300173700001700186700001800203856008800221 2003 eng d aLBNL-5351200aAn automated functional test and fault detection method0 aautomated functional test and fault detection method1 aXu, Peng1 aKim, Moosung1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/automated-functional-test-and-fault01417nas a2200145 4500008004100000245008800041210006900129490000700198520090100205100001901106700001801125700001801143700002201161856008801183 2002 eng d00aOn Approaches to Couple Energy Simulation and Computational Fluid Dynamics Programs0 aApproaches to Couple Energy Simulation and Computational Fluid D0 v373 a

Energy simulation (ES) and computational fluid dynamics (CFD) can play important roles in building design by providing complementary information about the buildings' environmental performance. However, separate applications of ES and CFD are usually unable to give an accurate prediction of building performance due to the assumptions involved in the separate calculations. Integration of ES and CFD eliminates many of these assumptions since the information provided by the models is complementary. Several different approaches to integrating ES and CFD are described. In order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs, a staged coupling strategy for different problems is proposed. The paper illustrates a typical dynamic coupling process by means of an example implemented using the EnergyPlus and MIT-CFD programs.

1 aZhai, Zhiqiang1 aChen, Qingyan1 aHaves, Philip1 aKlems, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/approaches-couple-energy-simulation01870nas a2200193 4500008004100000245009500041210006900136260001200205300001200217490000700229520122600236653002801462653002301490653000901513100002201522700002601544700001801570856008801588 2001 eng d00aAnalysis of an Information Monitoring and Diagnostic System to Improve Building Operations0 aAnalysis of an Information Monitoring and Diagnostic System to I c10/2001 a783-7920 v333 a

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

10abuilding control system10abuilding operation10aimds1 aPiette, Mary, Ann1 aKhalsa, Satkartar, T.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/analysis-information-monitoring-and00515nas a2200121 4500008004100000245012500041210006900166260001900235300001600254100001800270700002300288856008200311 1998 eng d00aThe application of Problem Reduction Techniques Based on Graph Theory to the Simulation of Non-Linear Continuous Systems0 aapplication of Problem Reduction Techniques Based on Graph Theor aManchester, UK app. 203-2071 aHaves, Philip1 aSowell, Edward, F. uhttps://simulationresearch.lbl.gov/publications/application-problem-reduction00446nas a2200121 4500008004100000245005200041210005200093260002900145100002300174700001800197700002000215856008900235 1993 eng d00aAutomatic Commissioning of HVAC Control Systems0 aAutomatic Commissioning of HVAC Control Systems aLondon, Englandc11/19931 aDexter, Arthur, L.1 aHaves, Philip1 aJorgensen, D.R. uhttps://simulationresearch.lbl.gov/publications/automatic-commissioning-hvac-control00414nas a2200097 4500008004100000245008700041210006900128260001500197100001800212856008600230 1987 eng d00aThe Application of Simulation to the Evaluation of Building Energy Control Systems0 aApplication of Simulation to the Evaluation of Building Energy C aBangor, UK1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/application-simulation-evaluation01768nas a2200169 4500008004100000245009200041210006900133260002500202300001200227490000600239520120000245100001801445700001601463700001801479700001501497856008601512 1982 eng d00aAccuracy of a Simple Method of Estimating the Minimum Temperature of a Sealed Roof Pond0 aAccuracy of a Simple Method of Estimating the Minimum Temperatur aHouston, TXc07/1982 a709-7140 v53 a

Detailed heat flux and temperature measurements have been made in two residential scale roof pond buildings in San Antonio, Texas from July to November 1981. The minimum temprature of the 4 in deep roof pond sealed in PVC bags was approximately equal to the minimum ambient dry bulb temperature. The sensitivity of this equality to changes in meteorological conditions, maximum pond temperature and thermal load is evaluated using the measurements. Verified simulations are then used to evaluate the sensitivity of this equality to changes in the thermal load, and to changes in the depth, surface emittance and surface thermal resistance of the sealed pond in various climates. For the range of roof pond design options of interest in passive cooling of buildings, the minimum pond temperature was found to be within 2 F of the minimum ambient temperature in all climates considered. The equality of these minimum temperatures is advocated as a useful rule of thumb for feasibility assessment and as part of a simplified design methodology. The simulated minimum pond temperature was found to be surprisingly insensitive to a 50% decrease in the fraction of pond area exposed to the sky.

1 aSchutt, Brady1 aClark, Gene1 aHaves, Philip1 aMerino, M. uhttps://simulationresearch.lbl.gov/publications/accuracy-simple-method-estimating