GPPre:A Python⁃Based Tool in Grasshopper for Office Building Performance Optimization

With the development of the economic and low⁃carbon society,high⁃performance building(HPB)design plays an increasingly important role in the architectural area.The performance of buildings usually includes the building energy consumption,building interior natural daylighting,building surface solar radiation,and so on.Building performance simulation(BPS)and multiple objective optimizations(MOO)are becoming the main methods for obtaining a high performance building in the design process.Correspondingly,the BPS and MOO are based on the parametric tools,like Grasshopper and Dynamo.However,these tools are lacking the data analysis module for designers to select the high⁃performance building more conveniently.This paper proposes a toolkit“GPPre”developed based on the Grasshopper platform and Python language.At the end of this paper,a case study was conducted to verify the function of GPPre,which shows that the combination of the sensitivity analysis(SA)and MOO module in the GPPre could aid architects to design the buildings with better performance.

On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

Occupant behavior(OB)is one of the significant sources of uncertainty in building performance simulation.While OB modeling has received increased attention in the past decade,research on the degree of granularity or level of detail(LoD)required for representing occupants is still in the nascent stages.This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment.A medium-sized prototype office building located in Chicago,Illinois is used as the simulation case study.Ten occupant-centric attributes are adopted to develop the LoDs for OB representation.We first demonstrate the different modeling approaches required for simulating the three fidelity levels.Later,we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages.This study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

Residential building performance analysis at near extreme weather conditions in Hong Kong through a thermal-comfort-based strategy

The precise building performance assessment of residential housings in subtropical regions is usually more difficult than that for the commercial premises due to the much more complicated behavior of the occupants with regard to the change in indoor temperature.The conventional use of a fixed schedule for window opening,clothing insulation and cooling equipment operation cannot reflect the real situation when the occupants respond to the change in thermal comfort,thus affecting the appropriateness of the assessment results.To rectify the situation,a new modeling strategy in which the modification of the various operation schedules was based on the calculated thermal comfort(TC),was developed in this study.With this new TC-based strategy,the realistic building performances under different cooling provision scenarios applied to a high-rise residential building under the near extreme weather conditions were investigated and compared.It was found that sole provision of ventilation fans could not meet the zone thermal comfort by over 68%of the time,and air-conditioning was essential.The optimal use of ventilation fans for cooling could only help reduce the total cooling energy demand by less than 12%at best which could only be realistically evaluated by adopting the present strategy.Parametric studies were conducted which revealed that some design factors could offer opportunities for reducing the total cooling energy under the near extreme weather conditions.

Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest energy.Therefore,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become paramount.In this vein,efforts have been made to predict the HL and CL using a univariate approach.However,this approach necessitates two models for learning HL and CL,requiring more computational time.Moreover,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware requirement.In this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D CNN.Considering the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and CL.As the 1D data are not affected by excessive parameters,the pooling layer is not applied in this implementation.Besides,the use of pooling has been questioned by recent studies.The performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.

Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper

With the expansion of the office building area,the energy consumption of office buildings is growing.High⁃performance building design contributes to energy saving and the development of green buildings.However,there is a lack of high⁃performance building tools and the workflow is often time⁃consuming.The building performance simulation,multiple objective optimizations,and the decision support model are the new approaches of high⁃performance building design.This paper proposes a newly developed decision support model,a high⁃performance building decision model named HPBuildingDSM,which integrates the building performance simulation,building performance multiple objective optimizations,building performance sampling,and parameter sensitivity analysis to design high⁃performance office buildings.In this research,the HPBuildingDSM was operated to search for the desirable office building design results with low⁃energy and high⁃quality daylighting performances.The simulated results had better daylighting performance and lower energy consumption,whose UDI100-2000 was 37.94%and annual energy consumption performance was 76.28 kWh/(m2·a),indicating a better building performance than the optimized results in the previous case study.

Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches

Buildings have a significant impact on global sustainability.During the past decades,a wide variety of studies have been conducted throughout the building lifecycle for improving the building performance.Data-driven approach has been widely adopted owing to less detailed building information required and high computational efficiency for online applications.Recent advances in information technologies and data science have enabled convenient access,storage,and analysis of massive on-site measurements,bringing about a new big-data-driven research paradigm.This paper presents a critical review of data-driven methods,particularly those methods based on larger datasets,for building energy modeling and their practical applications for improving building performances.This paper is organized based on the four essential phases of big-data-driven modeling,i.e.,data preprocessing,model development,knowledge post-processing,and practical applications throughout the building lifecycle.Typical data analysis and application methods have been summarized and compared at each stage,based upon which in-depth discussions and future research directions have been presented.This review demonstrates that the insights obtained from big building data can be extremely helpful for enriching the existing knowledge repository regarding building energy modeling.Furthermore,considering the ever-increasing development of smart buildings and IoT-driven smart cities,the big data-driven research paradigm will become an essential supplement to existing scientific research methods in the building sector.

DeST 3.0:A new-generation building performance simulation platform

Buildings contribute to almost 30%of total energy consumption worldwide.Developing building energy modeling programs is of great significance for lifecycle building performance assessment and optimization.Advances in novel building technologies,the requirements of high-performance computation,and the demands for multi-objective models have brought new challenges for building energy modeling software and platforms.To meet the increasing simulation demands,DeST 3.0,a new-generation building performance simulation platform,was developed and released.The structure of DeST 3.0 incorporates four simulation engines,including building analysis and simulation(BAS)engine,HVAC system engine,combined plant simulation(CPS)engine,and energy system(ES)engine,connected by air loop and water loop balancing iterations.DeST 3.0 offers numerous new simulation features,such as advanced simulation modules for building envelopes,occupant behavior and energy systems,cross-platform and compatible simulation kernel,FMI/FMU-based co-simulation functionalities,and high-performance parallel simulation architecture.DeST 3.0 has been thoroughly evaluated and validated using code verification,inter-program comparison,and case-study calibration.DeST 3.0 has been applied in various aspects throughout the building lifecycle,supporting building design,operation,retrofit analysis,code appliance,technology adaptability evaluation as well as research and education.The new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization.

A preference-based multi-objective building performance optimization method for early design stage

A large number of cases show that the multi-objective optimization method can significantly improve building performance.The method for multi-objective building performance optimization(BPO)design has achieved rapid development in recent years.However,the BPO method still needs to be improved.Specifically,weak interaction between the optimization process and the decision-making process results in low optimization efficiency,which limits the widespread application of the optimization method in early design stage.In this paper,a new interactive BPO mode is explored to strengthen the interaction between the optimization process and decisionmaking process,and a preference-based multi-objective BPO method is proposed to account for designers'decision preferences during the optimization process,making the objective more controllable,improving the optimization efficiency and ensuring the diversity of solutions.Firstly,this paper illustrates the proposed method in detail,defines the concept of performance preference,expounds the flow of the preference-based multi-objective optimization algorithm,and proposes three indicators to evaluate the algorithm,which includes convergence speed,preference satisfaction rate,and diversity measurement.Secondly,through testing and comparison,it is found that the proposed preference-based algorithm has advantages over the non-preference optimization algorithm(represented by the NSGA-II algorithm).The proposed method leads to faster convergence and higher preference satisfaction,so it is more suitable for the BPO process in the early design stage.Specially,the proposed method can achieve 100%preference satisfaction rate with only 2400 simulations,while the non-preference method can only achieve 20%preference satisfaction rate after 5800 simulations.In this paper,a preference-based multi-objective BPO method is proposed to make the optimization process closely interact with the decision-making process and make the design preferences be accounted during the BPO process,thereby improving the optimization efficiency.In addition,this study first proposes two indicators to measure the quality of optimization results:preference satisfaction rate and diversity measurement.This study aims to guide the development of BPO methods towards providing high satisfaction rate and high quality optimization results.

The application of building performance simulation in the writing of architectural history： Analysing climatic design in 1960s Israel

This article presents a methodology for the integration of building performance simulation （BPS） into the writing of architectural history. While BPS tools have been developed mainly for design purposes, their current maturity enables to reliably apply them in simulating the performance of past buildings, even when these buildings have been significantly modified or demolished. The possibility to virtually reconstruct the performance of past buildings can help us to overcome the existing knowledge gap in the understanding of the role played by building performance and building performance research through the history of architecture and can therefore promote the intelligent and successful application of environmental features in contemporary architecture. The potential of the proposed methodology is presented here using a historical case study from 1960s Israel （a university building in Tel Aviv）, in which climatic considerations were an explicit part of the entire design process. The original thermal performance of the building was analysed by employing the EnergyPlus simulation engine, and the simulation results were used for evaluating the climatic impact of certain design decisions, comparing them with the proclaimed design goals and the original intentions of the architects.

The simulation and mapping of building performance indicators based on European weather stations

Due to the climate change debate, a lot of research and maps of external climate parameters are availtabte. However, maps of indoor climate performance parameters are still Lacking. This paper presents a methodology for obtaining maps of performances of similar buitdings that are virtually spread over whole Europe. The produced maps are useful for anaty-zing regional climate influence on building performance indicators such as energy use and indoor climate. This is shown using the Bestest building as a reference benchmark. An important application of the mapping tool is the visualization of potential building measures over the EU. Also the performances of singte building components can be simulated and mapped. It is concluded that the presented method is efficient as it takes less than 15min to simulate and produce the maps on a 2.6GHz/4GB computer. Moreover, the approach is applicable for any type of building.

Plus Energy Buildings:A Numerical Case Study

The feasibility of Plus Energy Building for a sample relevant case is investigated.After a literature review aimed to identify key aspects of this type of buildings,a preliminary evaluation of the thermal performance of a building constructed using conventional material is presented together with a parametric analysis of the impact of typical influential parameters.Solar domestic hot water(SDHW)and photovoltaic systems(PV)are considered in the study.Numerical simulations indicate that for the examined sample case(Beirut in Lebanon)the total annual energy need of conventional building is 87.1 kWh/y.m^(2).About 49%of energy savings can be achieved by improving the building envelope and installing energy efficient technologies.Moreover,about 90%of energy savings in domestic hot water production can be achieved by installing a SDHW system composed of two solar collectors connected in series.Finally,the addition of a grid connected PV array system can significantly mitigate the energy needs of the building leading to an annual excess of energy.

Research on Two Types of Buffer Zone Impact on Surrounding Office Space Environment in Winter in Cold Climate Zone—a Fieldwork in Architectural Design Institute Building of Tsinghua University,Beijing

Building buffer zone space is not only one of essential approaches for better mental quality of interior building space, but also an important factor that may influence interior thermal comfort and energy consumption. This study aims to analyze regulative advantages of buffer zone to the surrounding functional spaces. Based on a fieldwork test in a typical office building in cold climate zone in Beijing,China,the monitor data show interior physical performance in the Winter. The research selects two types of different buffer zones in the same building. One is a south-faced greenhouse which has large dimension with plenty of vegetation,and the other is a simple atrium in the middle of five floor building with mount of skylights. The factors and their influence to surrounding functional spaces and the whole building are found out from the comparisons of collected data by floor to floor monitor test on both buffer zones at the same time. The comparisons of two types of buffer zones conclude that the greenhouse is more effective to air quality regulation but not so clearly wellperformed to thermal buffering as expected due to the dominate active central heating in the Winter. This fieldwork test results for building performance can be helpful for both architects and engineers in the early phase of sustainable design.

New Zealand Advances in Performance-Based Seismic Design

This paper provides a summary of the objectives and principles which underpin the 2004 edition of the New Zealand earthquake design standard, AS/NZS 1170 Part 5. As with many modern earthquake design standards, the New Zealand earthquake design standard recognizes that earthquake resistant design that only addresses life safety goals without addressing both operational continuity of essential facilities and damage control, falls short of public expectations. Such standards not longer meet societal expectations. The paper outlines how these issues have been addressed within New Zealand, and some of the issues addressed when preparing appendices to the standard to provide guidance for materials standard writers to ensure consistency with the proposed approach. Recognizing the significance of non-structural components and parts of buildings in both damage control and operational continuity has been an important step forward in attaining the performance levels required.

Chinese prototype building models for simulating the energy performance of the nationwide building stock

Building energy modeling(BEM)has become increasingly used in building energy conservation research.Prototype building models are developed to represent the typical urban building characteristics of a specific building type,meteorological conditions,and construction year.This study included four residential buildings and 11 commercial buildings to represent nationwide building types in China.With consideration of five climate zones and different construction years corresponding to national standards,a total of 151 prototype building models were developed.The building envelope properties,occupancy and energy-related behaviors,and heating,ventilation,and air-conditioning(HVAC)system characteristics were defined according to the corresponding building energy efficiency design standards,HVAC design standards,and through other sources,such as questionnaire surveys,on-site measurements,and literature,which reflect the real situation of existing buildings in China.Based on the developed prototype buildings,a large database of 9225 models in 270 cities was further developed to facilitate users to simulate building energy in different cities.In conclusion,the developed prototype building models can represent realistic building characteristics and construction practices of the most common residential and commercial buildings in China,serving as an important foundation for BEM.The models can be used for analyses related to building energy conservation research on typical individual buildings,including energy-saving technologies,advanced controls,and new policies,and providing a reference for the development of building energy codes and standards.

Analysis and Evaluation of Thermal-cooling Loads of Office Buildings Using Carrier Software in Iran

The importance and necessity of energy saving in the world have been dis­cussed for many years,but achieving a logical and transparent solution is still one of the main challenges and problems of the world’s economy.The rapid growth of energy consumption in the last two decades has caused the security of the domestic energy supply of buildings to face serious prob­lems.In this research,first by entering parameters such as the type of mate­rials,doors and windows,and the type of soil on the floor connected to the ground,etc.in the heat and cold load calculation software(HAP Carrier)as the design calculations and then in the second step entering the specifica­tions inferred from the Iran’s national building code as a reference for ener­gy saving calculations,calculations are performed and compared as the first criterion,and finally these two outputs are compared.The actual energy consumption and determination of the building energy consumption index are determined as another criterion,as well as the degree of deviation from the actual consumption.The results showed that the theoretical method and the thermal and refrigeration load calculations of the Zanjan Gas Company building have 6%difference in cooling load but the heating load is about 34%different,which means for cooling loads,the theoretical model can be used with high accuracy but for heating loads,the national building code needs fundamental changes.

Performance evaluation of residential buildings in public housing estates in 0gun State, Nigeria： Users＇ satisfaction perspective

This study assessed the performance of residential buildings in public housing estates in urban areas of Ogun State Southwest Nigeria. It was based on the notion that users＇ satisfaction with dwelling units is a measure of the performance of residential buildings in meeting their needs and expectations. A cross sectional survey of 452 household heads in nine public housing estates was conducted in the study area. Data were obtained using structured questionnaire and observation schedule; and were subjected to descriptive statistics and factor analysis. A mean satisfaction score of 3.21 was observed; indicating that the respondents were generally satisfied with the performance of the different components of the buildings. Satisfaction levels were generally higher with privacy and sizes of living and sleeping areas than the availability of water and electricity in the buildings. The type, location and aesthetic appearance as well as size of main activity areas were the most predominant factors that determined satisfaction and indeed the performance of the buildings in meeting users＇ needs and expectations. The paper highlights critical areas where attention is needed in order to improve the performance of residential buildings and users＇ satisfaction with public housing projects in Nigeria.

Green Design Studio: A modular-based approach for high-performance building design

A modular-based Green Design Studio(GDS)platform has been developed in this study for fast and accurate performance analysis for early stage green building design.The GDS platform aims to simplify the design and analysis process by embedding performance parameters into design elements in modules and employing near-real-time model for whole building performance simulation as well as by providing an easy-to-use and intuitive user interface to assist users without extensive knowledge on building physics.The platform consists of building modules as fundamental building blocks,performance predicting models,and a user interface for visualization and interactive design.In the platform,a whole building is composed of modules organized in a hierarchical structure,including spaces,enclosures,service systems,sustainable resource systems and sites.Both physics-based and data-driven models can be used to simulate the building performance and optimize building systems.A simplified physics-based model,the Resistance–Capacitance(RC)model,has been proposed as a generic simulation model for the flows of heat,air,moisture and pollutants,which is significantly faster than conventional simulation tools such as EnergyPlus,and hence more practical for use in real-time design interaction and optimization.A pilot case study is conducted to illustrate the modular-based design approach using a section of an office building.Compared to conventional building performance analysis tools,the GDS platform can provide fast and reliable feedback on performance prediction for early design.The modular approach makes it easier to modify the building design and evaluate the potentials and contributions of various green design features and technologies.

Performance assessment of buildings via post-occupancy evaluation： A case study of the building of the architecture and software engineering departments in Salahaddin University-Erbil, Iraq

Buildings are established to meet the needs and desires of users. The purpose of a building is defeated if its users are not satisfied by the overall buildingl performance. This study determines whether the users of the building of the architectural and software engineering departments at Salahaddin University-Erbil are satisfied with overall performance attributes. Assessment using users as a benchmark shows that the potentiat for improving the performance of a building is tremendous. This paper develops a post-occupancy evaluation （POE） framework that integrates building performance attributes for university buildings and facilities in the Iraqi Kurdistan region based on users＇ satisfaction. The objectives were to identify the concept of POE in relation to building performance, to determine the performance level of an existing building, and to determine correlation between building performance and users＇ satisfaction level. Results showed that 88% of building performance attributes is highly correlated with users＇ satisfaction. The compelling correlational results confirmed the relevance of POE as a building performance tool. The thrust of the findings indicates that the indicators and variables used in assessing the level of building performance are significant in determining levels of users＇ satisfaction in university buildings and facilities.

Parametric study on of green residential the performance buildings in China

The parametric study of the indoor environment of green buildings focuses on the quantitative and qualitative improvement of residential building construction in China and the achievement of indoor thermal comfort at a low leve（ of energy use. This study examines the effect of the adaptive thermal comfort of indoor environment control in hot summer and cold winter （HSCW） zones. This work is based on a field study of the regional thermal assessment of two typical cases, the results of which are compared with simulated results of various scenarios of ＂energy efficiency＂ strategy and ＂healthy housing＂ environmental control. First, the simulated results show that the adaptive thermal comfort of indoor environment control is actuaUy balanced in terms of occupancy, comfort, and energy efficiency. Second, adaptive thermal comfort control can save more energy for heating or cooling than other current healthy housing environmental controls in China＇s HSCW zone. Moreover, a large proportion of energy use is based on the subjective thermal comfort demand of occupants in any building type. Third, the building shape coefficient cannot dominate energy savings. The ratio of the superficial area of a bui[ding to the actual indoor floor area has a significant positive correlation with and affects the efficiency of buiidin~ thermal performance.

Do Well to Dwell Well. Awareness as the Driver for the Behaviour of Tomorrow’s Citizens

Because of the impact of global warming,the Earth’s ecosystems are currently at a critical stage.The European building sector,and the residential element in particular,is responsible for the largest portion of energy enduse.Although we know how to build a perfectly engineered house,it will not work properly if its inhabitants do not know how to run it.“Well-educated”dwellers can really improve energy use.The aim of this research is to optimize the users’role in the energy reduction process,analysing as a case study,Dwell!,the monitoring system designed for“RhOME for denCity”,the housing prototype developed by Roma Tre University and winner of the“Solar Decathlon Europe”competition in 2014.