Building Performance Analysis Research Articles

Multi-objective optimization algorithms for building performance assessment – A benchmark

The increasing development in the computational field that allowed software and hardware advances enables more refined building performance analysis. Simulation-based optimization (SBO) methods allow high standards to be achieved by combining parametric modeling, simulation, and optimization methods. However, SBO methods still need development, especially regarding the correct choice of the optimization algorithm based on the specific characteristics of each problem. This study proposes a multi-objective optimization algorithms benchmark by comparing seven multi-objective optimization algorithms: RBFMOpt, NSGA2, MHACO, NSPSO, MOEA/D, HypE, and SPEA2, across nine building-related problems, including thermal, energy, and daylight simulation. The problems varied from 5 to 18 discrete, continuous, and mixed parameters. The objective functions varied between two and three. We used the hypervolume indicator, IGD+, GD+, and EPS + to compare algorithms’ performance and assess the tendency to reduce computational costs. We also performed the Kruskal-Wallis non-parametric test to analyze the impact of multiple runs on the hypervolume indicator. The results showed that RBFMOpt and HypE perform best across all problems. However, RBFMOpt tends to reduce computational costs since the algorithm requires fewer simulations to obtain the best results.

Design and performance analysis of a net-zero energy building in Owerri, Nigeria

Building cooling load depends on heat gains from the outside environment. Appropriate orientation and masonry materials play vital roles in the reduction of overall thermal loads buildings. A net-zero energy building performance has been analyzed in order to ascertain the optimum orientation and wall material properties, under the climatic conditions of Owerri, Nigeria. Standard cooling load estimation techniques were employed for the determination of the diurnal interior load variations in a building incorporating renewable energy as the major energy source, and compared with the situation in a conventionally powered building. The results show a 19.28% reduction in the building’s cooling load when brick masonry was used for the wall construction. It was observed that a higher heat gain occurred when the building faced the East-West direction than when it was oriented in the North-South direction. Significant diurnal cooling loads variation as a result of radiation through the windows was also observed, with the east facing windows contributing significantly higher loads during the morning hours while the west facing windows contributed higher amounts in the evening. The economic analysis of the net-zero energy building showed an 11.63% reduction in energy cost compared to the conventional building, with a 7-year payback period for the use of Solar PV systems. Therefore, the concept of net-zero energy building will not only help in energy conservation, but also in cost savings, and the reduction of carbon footprint in the built environment.

Selecting suitable passive design strategies for residential high-rise buildings in tropical climates to minimize building energy demand

Passive design strategies (PDS) are a fitting solution to reduce the ever-growing energy cost of residential high-rise buildings in tropical regions. However, PDSs’ building energy saving potential significantly varies with local climate conditions, but it has been sparsely investigated. Hence, this study investigated the energy-saving efficiency of eight common PDSs integrated into a typical residential high-rise building in three sub-climates: extremely hot humid (0A), very hot humid (1A), and warm humid (3A) defined by ASHRAE for the tropical climate. This study developed a Building Performance Analysis (BPA) workflow with a BIM-based simulation framework and local and global sensitivity analyses for the building energy analysis. The global sensitivity analysis revealed that low e-coating on glasses is the most influential PDS for 0A and 1A climates, but it has a negative effect in the sub-climate zone 3A. The low-conducting exterior walls are the most effective PDS in the sub-climate zone 3A, but they are poorly performed in the other two sub-climate zones. Based on the energy calculation and sensitivity analysis, this study proposes the best PDS groups, saving up to 40.1%, 63.5%, and 31.7% of average annual building consumption in the sub-climate zones, 0A, 1A, and 3A climates.

Building Mass Optimization to Reduce Solar Radiation in High Rise Building by Using Parametric Approach

Buildings use 40% of global primary energy, therefore their design and use affect climate change. Building performance analysis can assist architects predict performance before construction with parametric design tools. Radiance can be reduced via a parametric mass, lowering cooling load and energy use. The study uses theoretical and computational research to explain, forecast, and analyze events, whereas parametric design optimizes complicated geometries using mathematical parameters and algorithms. Environmental analysis in Grasshopper with the Ladybug plugin uses Rhinoceros. This plugin provides solar radiation, and climate analysis capabilities. To determine the most energy-efficient building design, the research links independent and dependent variables such solar radiation intensity and building mass. The study uses Surabaya weather data and high rise buildings. The land is formed like a square, with a 15-degree slope to the north and is flanked by low-rise buildings. As a result, the location receives the most direct sunlight during the day. Then, solar radiation analysis. It helps optimize passive solar design solutions. According to the modelling results, solar radiation on the top and west sides are particularly large and dominant in 65.37 and 32.69 kWh/m2. Meanwhile, the north, east and south sides receive very little solar radiation. The following simulation considers the optimal direction, which is to extend west-east and face to the south. A multi-towered megastructure is a high-rise building that responds best to solar radiation. The total solar radiation value is 3,718,100 kWh. It can accommodate large spaces with large mass composition but relatively low total solar radiation values. The building towers provide shade to each other, thereby reducing direct radiation from the sun to the building. The sides of the building's podium are also shaded, so the top of the building is partially red.

Green Building Performance Analysis and Energy-Saving Design Strategies in Dalian, China

Green Building Performance Analysis and Energy-Saving Design Strategies in Dalian, China

Data Quality Assessment for Building Performance Analysis with Pilot Case Study

Data Quality Assessment for Building Performance Analysis with Pilot Case Study

Ten questions concerning environmental architectural design exploration

It is widely recognized that the sustainability of the built environment is one of the key strategies to tackle global crises such as climate change, resource depletion, and human health. An environmentally driven approach to architectural design and urban planning through simulations has been around for many decades. However, architects and planners haven't fully taken advantage of its potential yet due to the complexity of the tasks and the fragmentation of tools and methods in different fields of expertise. This paper aims to demonstrate how the nascent field of environmental architectural design exploration is a viable answer to complex tasks and challenges through the integration of sustainable design, environmental simulations, building performance analysis, and computational procedures leveraging parametric design environments. After defining the context that favored its development, the ten questions answered present the environmental metrics and design parameters, propose a taxonomy of simulation tools and methods, present optimization processes, identify the required data, and introduce a classification of co-simulation and design exploration workflows, emphasizing their potential for the design of sustainable buildings and districts. Then focus is given to the scales and domains of application and to the potential of machine learning methods. The paper concludes by presenting applications in practice and discussing challenges and future opportunities. Strategies and operational procedures emerge from the ten questions. They emphasize the use of holistic approaches and the selection of balanced design solutions allowed by environmental architectural design exploration for the development of a sustainable built environment.

Passive strategies for climate change mitigation in architectural heritage: the case study of Santa Maria in Trastevere Basilica, Rome

ABSTRACT According to the most recent climate projections, urban settings and historic centres will be affected by considerable increases in temperature extremes and heat waves as a result of climate change. For this reason, the issue of energy efficiency and indoor comfort in historic buildings has become a topic of major interest for the significant number of buildings in the national and European territories. The performance redevelopment of architectural heritage, particularly religious buildings, requires accurate design, through a careful assessment of the occupants’ needs and the historic building’s characteristics, to guarantee adequate levels of thermal comfort and ensure an indoor climate suitable for safeguarding the cultural asset. In this regard, the study investigates, through a data-driven approach and building performance analysis, the indoor comfort level of a religious building in the historical centre of Rome that presents phenomena of excessive indoor overheating. The objective is to identify passive cooling strategies, through the optimization of natural ventilation levels and reduction of surface temperatures of the envelope exposed to solar radiation, in order to propose different design scenarios. The results show how a data-driven process in a digital environment can significantly contribute to the identification of optimal and integrated design strategies and solutions.

Feasibility and performance analysis of a net-zero energy residential building in tropical climates: A case of Congo-Brazzaville

Current building techniques in developing countries have become extremely critical. The net-zero energy concept has emerged as an essential strategy for minimising energy consumption and greenhouse gas emissions. However, its implementation, particularly in developing countries, remains a critical challenge. The purpose of this work is to assess the feasibility of achieving a net-zero energy building by combining energy-efficient design practices and renewable energy systems under the climatic conditions of the Republic of Congo. To achieve the stipulated objectives, DesignBuilder software was utilised for building modelling, energy load assessment and multiobjective optimisation of building energy efficiency measures, and the multicriteria energy optimisation was carried out using the HOMER tool. The optimisation results showed that the implementation of energy efficiency measures resulted in 39.15% energy savings, 43.45% thermal load savings and 55.68% discomfort hours reduction. Furthermore, the renewable energy system can provide 100% of the building’s energy load and a total savings of 3341.84 kgCO2eq/year. The system’s levelised cost of energy was estimated at 0.256 $/kWh, with a net present cost of $20,231, while the overall life cycle cost was calculated at 188.91 $/m2.

Data-driven approach enabling post-operation evaluation of air conditioning performance regarding thermal conditions attained indoors

Data-driven approaches become more and more attractive in building performance analysis including performance assessment of heat, ventilation, and air conditioning (HVAC) systems. Their popularity is associated with the increasing availability of large amounts of high-quality building-related measurement data. The study is focused on a data-driven approach that enables post-operation evaluation of AC performance based on indoor air monitoring. It allows for the identification of the classifying solution which recognizes the monitoring data that is representative of thermal conditions during AC operation. The major novelty consists in proposing the classification performance criterion, which is F1w-Score (the weighted F1-Score), and the procedure of weights selection. The procedure utilizes Hellinger distance (H). It is applied to measure the similarity between the binary empirical probability distribution of T and RH (EPDtr), associated with AC operation, and the prediction of this distribution (EPDes), made by the classifier. The approach was tested on three years of data from continuous indoor air monitoring in the IT engineers' room equipped with an AC unit. The best weights of F1w-Score were wPPV = 0.85 and wTPR = 0.15. The best classifying solution was identified using F1w-Score. It involved: Logistic Regression as the classifier and feature vector being Fourier spectrum of 16 min long fragments of RH and T time series. The performance of the best classifying solution was high as indicated by F1w-Score = 0.89 ± 0.05. The corresponding H(EPDtr, EPDes) = 0.17 ± 0.04 pointed at the capability to identify the measurement data that characterizes indoor conditions during AC operation well. This work contributes to the development of data-driven approaches serving diagnostics of HVAC systems. It draws attention to the problem of defining the classification performance criterion which takes into account the ultimate, domain-specific use of the classification results.

Optimization of the Air-Conditioning Energy Performance and Daylight Performance of AResidential Building According to the Bioclimatic Design Principles: An Application to the Moroccan Mediterranean

The bioclimatic architecture concept refers to an approach that takes into account the various characteristics of a building environment to make it more comfortable for its occupants. This work aims to improve the passive design parameters of an air-conditioned residential building located in the north of Morocco, in accordance with bioclimatic principles. The bioclimatic chart diagram is used to select the passive design measures that are the most appropriate for the north Morocco climate characteristics. Then, a set of design parameters are selected for more delimitation in the optimization study. The optimization problem is multi-objective and aims to find the design solution that simultaneously includes the best air-conditioning energy performance and daylight performance. The obtained results showed that the multi-objective optimum design solution is characterized by massive walls and roof, exterior insulation, double window glazing type, and a high summer ventilation rate. Also, a small glazing area with a large sun-shading covering is needed for the east facade. Ultimately, the building performance analysis revealed that the optimum bioclimatic design solution fully meets the requirements establishedby the Moroccan Building Thermal Regulation (MBTR), leading to an energy performance improvement of about 52%.

Assessment and Optimization of Green Buildings in Inpatient Buildings Using EDGE Building Rating (Case Study: Graha Amarilis of Karsa Husada Batu Academic Hospital)

The Graha Amarilis inpatient building has high Energy, Water, and material consumption because it operates 24 hours daily. The building’s performance must be evaluated based on green building standards to ensure the sustainability of the building and the environment surrounding it. This study aims to determine the performance of green buildings and optimize the Graha Amarilis inpatient building. A combined strategy of case studies with simulations is used as research methodology. Field surveys and measurements were carried out on research cases and digitally modeled using Autodesk REVIT. Then, building performance analysis calculations are carried out using the EDGE Building application simulation method, which presents data on green rating of Energy, Water, and Material saving in buildings. The results of this study were obtained on energy and water items that had not reached green building rating in EDGE Building by 20%. So, optimizing energy items at points EEM 18, EEM 07, and EEM 33 and Water at points WEM 01, WEM 02, WEM 14, and WEM 15 is necessary. Finally, after several simulations on that item, Energy saving consumption becomes 20.07 %, Water 34.69%, and Material 23.00%. With these adjustments, the Graha Amarilis inpatient Building can reach the green building standards and become more sustainable and environmentally friendly

Assessing the efficacy of green building design strategies in minimizing energy consumption in commercial buildings of Mumbai: A building performance analysis

This research paper investigates the effectiveness of green building design strategies in minimizing energy consumption in commercial buildings in the bustling metropolis of Mumbai, India. With a rapidly urbanizing and densely populated environment, Mumbai presents a unique setting for assessing green building practices. The research objectives focus on understanding the impact of various green building design features, such as green roofs, solar panels, and floor area optimization, on energy efficiency in commercial structures. The research employs a robust methodology, incorporating regression analysis to analyze data obtained from the Mumbai Municipal Corporation's building energy consumption records. Through this analysis, the study investigates the relationships between green building design parameters, building characteristics, and energy consumption patterns. Key findings indicate that specific green building features, including intensive and biodiverse green roofs and solar panel installations, significantly reduce energy consumption. Additionally, older buildings tend to exhibit lower energy consumption, emphasizing the need for retrofitting existing structures with energy-efficient solutions. The study also underscores the role of occupant density in influencing energy efficiency, with higher occupant rates leading to more efficient space utilization and energy use. The implications of this research are far-reaching, offering insights into tailoring green building strategies to the specific challenges posed by densely populated urban areas. These findings hold significance for sustainable urban development, policy formulation, architectural design, and the global effort to mitigate climate change.

Fire Performance Analysis of Building Integrated Solar System Roofs

Fire Performance Analysis of Building Integrated Solar System Roofs

Development of a fast moisture prediction model based on the moisture buffer value theory

Moisture transfer in buildings significantly affects indoor thermal comfort, energy consumption, and durability of construction materials. It is crucial to predict the moisture storage and transfer in building simulations accurately. However, moisture transfer was neglected in many simulation tools for building performance analysis. In those calculation tools, including a moisture model, moisture transfer has been either estimated by simple approximations or calculated by complex combined heat, air, and moisture transfer (HAMT) models that require orders of magnitude more computing time than simple calculations. In this study, a new moisture prediction model with fast solution time and reasonable accuracy was developed based on the moisture buffer value (MBV) theory. The moisture buffer value was initially designed to quantify the moisture buffering ability of porous building materials. Very little research has been conducted to use MBV for calculating building energy performance directly. This paper first studied the MBVs under different boundary conditions (i.e., square wave and harmonic wave variation of vapour content), and then a time-average MBV was proposed. Experiments were carried out to get the parameters for the new FMBM model. Finally, simulation tests were conducted to compare the FMBM model with other moisture prediction models (e.g. EC, EMPD and HAMT models). The results indicate that the FMBM can provide a fast and reasonably accurate solution for indoor moisture prediction.

Identification of influential factors for combined energy consumption and indoor environmental quality in residential buildings

The development of an overall building performance simulation model requires a multitude of input parameters which can be a challenging and resource-heavy task for building modellers. Furthermore, some parameters have little impact on a building’s overall performance and contribute little towards model prediction accuracy. Feature selection has been employed to identify the most influential input parameters to reduce complexity and computational time. However, previous studies focused mainly on identifying parameters that impact energy consumption in residential buildings, neglecting the important relationship between energy consumption and indoor environmental quality (IEQ). Therefore, this study proposes a novel simulation framework that integrates occupancy-based building archetypes, parametric simulation, and machine learning techniques to develop an overall building performance prediction model. Using this framework, the study generates a synthetic dataset of 40,000 simulations and performed embedded feature selection using two machine learning algorithms, Random Forest (RF) and Gradient Boosting Technique (GBT), to identify parameters that impact heating energy consumption, thermal discomfort hours, and CO2 concentration simultaneously. The results demonstrate that the ranking for importance and the number of required parameters vary depending on the target variable. Also, the set of parameters for combined analysis differs from individual target variable analysis. The GBT algorithm with embedded feature selection provides the most accurate prediction results with lower root mean square error (RMSE) and absolute error (AE) for individual and combined analyses. This study provides valuable insights for accurate parameter selection and analysis of overall building performance.

Numerical safety and performance analysis of a multipurpose building’s structure: case study

This report presents a case study of a multi-use building situated in Brasília-DF. The building's structural model is made up of elements of a spatial portico and four-knot plate, measuring 25.75 by 25.75 m with a height of 11.65 m. The structure is supported by rotating pillars at the base. The ground floor has a ceiling height of 3.25 m, while the other floors have a ceiling height of 2.80 m. The closure is made of bored brick masonry. In this article, numerical analyses were conducted using the SAP2000 structural software to verify the structure's displacement, deformation, and stress. The study followed the ultimate and in-use limit state criteria for the Brazilian standard of reinforced concrete (NBR 6118). The report also presents the building's structural pathologies, detected through visual inspection. The main structural elements and their respective pathologies are described, and numerical tests are shown. Due to the presence of various cracks and other pathologies in the building, an elastic instability analysis was conducted using the Rankine-Marchant analysis model to verify the collapse load factor. After approximately 17 years of use, the building is revisited to assess the durability and performance of the recovered structural components and procedures.

An integrated pipeline for building performance analysis: Daylighting, energy, natural ventilation, and airborne contaminant dispersion

An integrated pipeline for building performance analysis: Daylighting, energy, natural ventilation, and airborne contaminant dispersion

Daylight performance analysis of a residential building in a tropical climate

The present study investigates the effects of visible light transmittance in glazing and window-to-wall ratios on the ground floor daylighting performance in a two-storey residential building in a warm-humid climate. The metrics used to optimize daylighting performance with minimal glare are useful daylight illuminance, annual sunlight exposure, and spatial daylight autonomy. The daylighting performance of a residential building is assessed by empirical method and Design-Builder simulation, focusing on overcast sky situations. The useful daylight illuminance is the primary metric for analysing the amount of daylight throughout the year. Annual sunlight exposure and spatial daylight autonomy complement useful daylight illuminance in evaluating the daylighting performance. A window-to-wall ratio of 16%, a visible light transmittance of 0.62, and a glare of 0.52 can meet the daylighting requirements and standards. A design change in the window position helps to obtain annual sunlight exposure within 10% while maintaining high daylighting performance. When installed in the upper position of the wall with a higher sill and lintel height, glazing with a window-to-wall ratio of 16% and a visible light transmittance of 0.62 functions well without creating glare. The significant findings benefit all stakeholders in improving daylighting strategies in tropical climates and satisfying building standards.

The feeling of comfort in residential settings I: a qualitative model

Building science commonly studies comfort—a subjective concept—through quantitative methods. These methods are often not the most appropriate to study subjective concepts because they struggle to consider non-quantifiable factors that are sometimes relevant in the determination of people’s comfort. Complementing the already used quantitative methods with qualitative ones can help illuminate some of the areas where the former struggle, but this is an uncommon practice in building science. This paper presents the results of a qualitative study that aimed at understanding comfort without the constraints of it being quantifiable. It introduces the feeling of comfort model, which summarises what was found. This model suggests that most building science comfort models ignore more than two out of the three factors that determine people’s comfort. Additionally, it shows that it is potentially possible to make sense of the psychology and subjectivity of comfort in an organised and structured manner. This example of how qualitative methods can be a powerful addition to building science’s comfort research. Practice relevance This paper reports a project that sought to understand an occupant-centred meaning of ‘comfort’ (constrained to what has conventionally been described as thermal, visual and acoustic domains). A qualitative model of the feeling of comfort was developed from the empirical data collated in the study. This model demonstrates that it was possible to make sense of the subjective nature of comfort in a coherent and ordered manner. This study argues that the qualitative and subjective nature of comfort should be embraced within building design and building science practice. Although this model was not meant to predict comfort quantitatively, it can serve as a theoretical basis for informing policymaking, building performance analysis and comfort research. For instance, it can help evaluate the assumptions behind building performance simulation (e.g. questioning whether people will truly open windows in certain scenarios).