Building designers are increasingly relying on complex fenestration systems to reduce energy consumed for lighting and HVAC in low energy buildings. Radiance, a lighting simulation program, has been used to conduct daylighting simulations for complex fenestration systems. Depending on the configurations, the simulation can take hours or even days using a personal computer. This paper describes how to accelerate the matrix multiplication portion of a Radiance three-phase daylight simulation by conducting parallel computing on heterogeneous hardware of a personal computer. The algorithm was optimized and the computational part was implemented in parallel using OpenCL. The speed of new approach was evaluated using various daylighting simulation cases on a multicore central processing unit and a graphics processing unit. Based on the measurements and analysis of the time usage for the Radiance daylighting simulation, further speedups can be achieved by using fast I/O devices and storing the data in a binary format.

10adaylighting simulation10agraphics processing unit10amulticore central processing unit10aOpenCL10aparallel computing1 aZuo, Wangda1 aMcNeil, Andrew1 aWetter, Michael1 aLee, Eleanor, S. uhttps://buildings.lbl.gov/publications/acceleration-matrix-multiplication01607nas a2200133 4500008003900000245006700039210006500106260003000171520113400201100003101335700002001366700001601386856007101402 2013 d00aFunctional Mock-Up Unit Import in EnergyPlus For Co-Simulation0 aFunctional MockUp Unit Import in EnergyPlus For CoSimulation aChambery, Francec08/20133 aThis paper describes how to use the recently implemented Functional Mock-up Unit (FMU) for co-simulation import interface in EnergyPlus to link EnergyPlus with simulation tools packaged as FMUs. The interface complies with the Functional Mock-up Interface (FMI) for co-simulation standard version 1.0, which is an open standard designed to enable links between different simulation tools that are packaged as FMUs. This article starts with an introduction of the FMI and FMU concepts. We then discuss the implementation of the FMU import interface in EnergyPlus. After that, we present two use cases. The first use case is to model a HVAC system in Modelica, export it as an FMU, and link it to a room model in EnergyPlus. The second use case is an extension of the first case where a shading controller is modeled in Modelica, exported as an FMU, and used in the EnergyPlus room model to control the shading device of one of its windows. In both cases, the FMUs are imported into EnergyPlus which models the building envelope and manages the data-exchange between the envelope and the systems in the FMUs during run-time.

1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aZuo, Wangda uhttps://buildings.lbl.gov/publications/functional-mock-unit-import00421nas a2200133 4500008004100000245005000041210005000091300001200141490000600153100001600159700001700175700001800192856007700210 2012 eng d00aReduction of numerical viscosity in FFD model0 aReduction of numerical viscosity in FFD model a234-2470 v61 aZuo, Wangda1 aJin, Mingang1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/reduction-numerical-viscosity-ffd01272nas a2200145 4500008004100000245008300041210006900124260002900193520073500222100003100957700002100988700001601009700002001025856008101045 2012 eng d00aValidation and Application of the Room Model of the Modelica Buildings Library0 aValidation and Application of the Room Model of the Modelica Bui aMunich, Germanyc09/20123 aThe Modelica *Buildings* library contains a package with a model for a thermal zone that computes heat transfer through the building envelope and within a room. It considers various heat transfer phenomena of a room, including conduction, convection, short-wave and long-wave radiation. The first part of this paper describes the physical phenomena considered in the room model. The second part validates the room model by using a standard test suite provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). The third part focuses on an application where the room model is used for simulation-based controls of a window shading device to reduce building energy consumption.

This paper describes the validation of the window model of the free open-source Modelica Buildings library. This paper starts by describing the physical modeling assumptions of the window model. The window model can be used to calculate the thermal and angular properties of glazing systems. It can also be used for steady-state simulation of heat transfer mechanism in glazing systems. We present simulation results obtained by comparing the window model with WINDOW 6 the well established simulation tool for steady-state heat transfer in glazing systems. We also present results obtained by comparing the window model with measurements carried out in a test cell at the Lawrence Berkeley National Laboratory.

1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aZuo, Wangda uhttps://buildings.lbl.gov/publications/validation-window-model-modelica00489nas a2200133 4500008004100000245008700041210006900128260001600197300001400213100001700227700001600244700001800260856007700278 2012 eng d00aValidation of three dimensional fast fluid dynamics for indoor airflow simulations0 aValidation of three dimensional fast fluid dynamics for indoor a aBoulder, CO a1055-10621 aJin, Mingang1 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/validation-three-dimensional-fast01206nas a2200157 4500008004100000245009300041210006900134260003100203300001500234520064900249100001600898700001900914700002000933700002100953856007400974 2011 eng d00aAcceleration of Radiance for Lighting Simulation by using Parallel Computing with OpenCL0 aAcceleration of Radiance for Lighting Simulation by using Parall aSydney, Australiac11/2011 ap. 110-1173 aThis study attempted to accelerate annual daylighting simulations for fenestration systems in Radiance ray-tracing program. The algorithm was optimized to reduce both the redundant data input/output operations and floating-point operations. To further accelerate the simulation speed, calculation for matrices multiplications was implemented in parallel on a graphics processing unit using OpenCL, a cross-platform parallel programming language. Numerical experiments show that combination of above measures can speed up the annual daylighting simulations 101.7 times or 28.6 times when sky vector has 146 or 2306 elements, respectively.

1 aZuo, Wangda1 aMcNeil, Andrew1 aWetter, Michael1 aLee, Eleanor, S. uhttps://buildings.lbl.gov/publications/acceleration-radiance-lighting00467nas a2200109 4500008004100000245011200041210006900153260001900222100001600241700002000257856008000277 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://buildings.lbl.gov/publications/advanced-simulations-building-energy00512nas a2200133 4500008004100000245007500041210006900116260003100185300001400216100002000230700001600250700003100266856008100297 2011 eng d00aModeling of Heat Transfer in Rooms in the Modelica "Buildings" Library0 aModeling of Heat Transfer in Rooms in the Modelica Buildings Lib aSydney, Australiac11/2011 a1096-11031 aWetter, Michael1 aZuo, Wangda1 aNouidui, Thierry, Stephane uhttps://buildings.lbl.gov/publications/modeling-heat-transfer-rooms-modelica01476nas a2200157 4500008004100000245009800041210006900139260002100208520088700229653002801116653001201144100002001156700001601176700003101192856009501223 2011 eng d00aRecent developments of the Modelica Buildings library for building energy and control systems0 aRecent developments of the Modelica Buildings library for buildi aDresden, Germany3 aAt the Modelica 2009 conference, we introduced the Buildings library, a freely available Modelica library for building energy and control systems [16]. This paper reports the updates of the library and presents example applications for a range of heating, ventilation and air conditioning (HVAC) systems. Over the past two years, the library has been further developed. The number of HVAC components models has been doubled and various components have been revised to increase numerical robustness. The paper starts with an overview of the library architecture and a description of the main packages. To demonstrate the features of the Buildings library, applications that include multizone airow simulation as well as supervisory and local loop control of a variable air volume (VAV) system are briey described. The paper closes with a discussion of the current development.

10abuilding energy systems10aheating1 aWetter, Michael1 aZuo, Wangda1 aNouidui, Thierry, Stephane uhttps://www.modelica.org/events/modelica2011/Proceedings/pages/papers/12_1_ID_113_a_fv.pdf01516nas a2200169 4500008004100000245011000041210006900151260002700220520091900247653000801166653000801174653002201182653002801204100001601232700001801248856008001266 2011 eng d00aValidation of a Fast-Fluid-Dynamics Model for Predicting Distribution of Particles with Low Stokes Number0 aValidation of a FastFluidDynamics Model for Predicting Distribut aAustin, Texasc06/20113 aTo design a healthy indoor environment, it is important to study airborne particle distribution indoors. As an intermediate model between multizone models and computational fluid dynamics (CFD), a fast fluid dynamics (FFD) model can be used to provide temporal and spatial information of particle dispersion in real time. This study evaluated the accuracy of the FFD for predicting transportation of particles with low Stokes number in a duct and in a room with mixed convection. The evaluation was to compare the numerical results calculated by the FFD with the corresponding experimental data and the results obtained by the CFD. The comparison showed that the FFD could capture major pattern of particle dispersion, which is missed in models with well-mixed assumptions. Although the FFD was less accurate than the CFD partially due to its simplification in numeric schemes, it was 53 times faster than the CFD.10acfd10affd10alow stokes number10aparticle transportation1 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/validation-fast-fluid-dynamics-model00483nas a2200121 4500008004100000245011800041210006900159300001200228490000700240100001600247700001800263856008000281 2010 eng d00aFast and informative flow simulation in a building by using fast fluid dynamics model on graphics processing unit0 aFast and informative flow simulation in a building by using fast a747-7570 v451 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/fast-and-informative-flow-simulation00385nas a2200109 4500008004100000245005200041210005200093260002100145100001600166700001800182856007500200 2010 eng d00aFast simulation of smoke transport in buildings0 aFast simulation of smoke transport in buildings aBeograd, Serbian1 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/fast-simulation-smoke-transport00466nas a2200133 4500008004100000245007200041210006900113260001700182300001000199100001600209700001600225700001800241856007300259 2010 eng d00aImpact of time-splitting schemes on the accuracy of FFD simulations0 aImpact of timesplitting schemes on the accuracy of FFD simulatio aSyracuse, NY a55-601 aHu, Jianjun1 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/impact-time-splitting-schemes00455nas a2200133 4500008004100000245007000041210006900111300000900180490000700189100001600196700001600212700001800228856007500246 2010 eng d00aImprovements on FFD modeling by using different numerical schemes0 aImprovements on FFD modeling by using different numerical scheme a1-160 v581 aZuo, Wangda1 aHu, Jianjun1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/improvements-ffd-modeling-using00451nas a2200121 4500008004100000245008000041210006900121260001700190300001200207100001600219700001800235856007600253 2010 eng d00aImprovements on the fast fluid dynamics model for indoor airflow simulation0 aImprovements on the fast fluid dynamics model for indoor airflow aNew York, NY a539-5461 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/improvements-fast-fluid-dynamics00414nas a2200121 4500008004100000245006300041210006300104300001200167490000700179100001600186700001800202856007200220 2010 eng d00aSimulations of air distribution in buildings by FFD on GPU0 aSimulations of air distribution in buildings by FFD on GPU a783-7960 v161 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/simulations-air-distribution01995nas a2200301 4500008004100000022001400041245013400055210006900189260001200258300001100270490000700281520102100288653001501309653001801324653002601342653003601368653003201404653001501436653002401451100001401475700002401489700002201513700002001535700001601555700002101571700002101592856008001613 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 aNumerical 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 aJovanoviÄ‡, Jovan1 aBreuer, Michael1 aZuo, Wangda1 aHadziÄ‡, Ibrahim1 aLechner, Richard uhttps://buildings.lbl.gov/publications/anisotropy-invariant-reynolds-stress00414nas a2200109 4500008004100000245006700041210006700108260001700175100001600192700001800208856007800226 2009 eng d00aFast parallelized flow simulations on graphic processing units0 aFast parallelized flow simulations on graphic processing units aBusan, Korea1 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/fast-parallelized-flow-simulations00400nas a2200121 4500008004100000245004600041210004600087260001800133300001200151100001600163700001800179856008100197 2009 eng d00aHigh performance computing for indoor air0 aHigh performance computing for indoor air aGlasgow, U.K. a244-2491 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/high-performance-computing-indoor-air00430nas a2200121 4500008004100000245007400041210006900115300001000184490000700194100001600201700001800217856007300235 2009 eng d00aReal time or faster-than-real-time simulation of airflow in buildings0 aReal time or fasterthanrealtime simulation of airflow in buildin a33-440 v191 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/real-time-or-faster-real-time00491nas a2200133 4500008004100000245009200041210006900133260001800202300000800220100001800228700001600246700001600262856007900278 2007 eng d00aComputational fluid dynamics for indoor environment modeling: past, present, and future0 aComputational fluid dynamics for indoor environment modeling pas aSendai, Japan a1-91 aChen, Qingyan1 aZhang, Zhao1 aZuo, Wangda uhttps://buildings.lbl.gov/publications/computational-fluid-dynamics-indoor00391nas a2200121 4500008004100000245004600041210004600087260001800133300001200151100001600163700001800179856007200197 2007 eng d00aReal time airflow simulation in buildings0 aReal time airflow simulation in buildings aSendai, Japan a459-4661 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/real-time-airflow-simulation00417nas a2200121 4500008004100000245005500041210005500096260001900151300001200170100001600182700001800198856007900216 2007 eng d00aValidation of fast fluid dynamics for room airflow0 aValidation of fast fluid dynamics for room airflow aBeijing, China a980-9831 aZuo, Wangda1 aChen, Qingyan uhttps://buildings.lbl.gov/publications/validation-fast-fluid-dynamics-room00426nas a2200133 4500008004100000245005500041210005500096300001000151490000700161100001600168700001700184700001600201856007500217 2004 eng d00aUpdating traditional CRM system by terminal server0 aUpdating traditional CRM system by terminal server a94-950 v271 aZuo, Wangda1 aYang, Tianyi1 aZou, Wenyan uhttps://buildings.lbl.gov/publications/updating-traditional-crm-system