Building Design Phase Research Articles

Efficient management and compliance check of HVAC information in the building design phase using Semantic Web technologies

Several OWL ontologies have been developed for the AEC industry to manage domain-specific information, yet they often overlook the domain of building services and HVAC components. The Flow Systems Ontology was recently proposed to address this need, but it does not include HVAC components’ size and capacity-related properties. Also, despite their strengths in representing domain-specific knowledge, ontologies cannot efficiently identify poor data quality in BIM models. A four-fold contribution is made in this research paper to define and improve the data quality of HVAC information by (1) extending the existing Flow Systems Ontology, (2) proposing the new Flow Properties Ontology, (3) proposing an HVAC rule set for compliance checking, and (4), moreover, we use Semantic Web technologies to demonstrate the benefits of efficient HVAC data management when sizing components. The demonstration case shows that we can represent the data model in a distributed way, validate it using 36 SHACL shapes and use SPARQL to determine the pressure and flow rate of fans and pumps.

A Vibration and Crack Assessment on Precast Pre-stressed Hollow-Core Floor

Hollow core concrete floors are usually used in high-rise buildings, shopping malls and parking garages due to their sustainability advantage in the construction industry. However, in certain conditions, hollow core concrete floors can be sensitive towards vibration due to long span. The floor vibration issue is crucial and must be managed properly during the building design phase, as addressing this issue becomes significantly more challenging after the structure has been constructed completely. Thus, this study aims to determine the vibration and crack behaviour of precast hollow core concrete floors. 3D finite element models of the floor were developed using SAP2000 software to obtain the vibration parameters of the hollow core concrete floor subjected to vehicle-induced vibration. The specifications of the floor materials are based on the hollow core concrete floor manufacturer, Eastern Pretech, and the acceleration time history from testing was applied to the analysis. Modal analysis and time history analysis were analysed to investigate the vibration behaviour of the hollow core concrete floor. Modal analysis revealed a fundamental frequency of 23.52 Hz for the floor with actual dimensions. The fundamental frequency of the floor was compared to the standard guideline for human vibration sensitivity, which is 10 Hz. Time history analysis was employed to assess floor deformation based on the vibration waves generated by vehicle movement on the floor.The crack assessment analysis on concrete topping of precast hollow core slab in the warehouse flooring system was carried out. The cracks that appeared on the concrete topping were investigated using vibration testing and finite element analysis. Acceleration data from the damaged area was captured and transformed into the frequency domain using ME’Scope to analyse the natural frequency behaviour. The preliminary finite element analysis was performed by SAP 2000 software. Normal attenuation was observed on the surface with a crack at 50 mm, as the pattern of the time series data at this location was similar to other sensor positions. Analysis of the frequency domain of the wave confirmed this observation, revealing a dominant frequency of 23.741 Hz and no abnormal event occurred during testingon the surface crack.

Geometry optimization in the schematic design phase of low-energy buildings for all European climates through genetic algorithms

The ongoing transition towards resilient and energy-efficient cities highlights the design of new buildings as a critical concern. With the increasing urbanization in Europe and the concurrent need for energy reduction and decarbonization, it is crucial to address energy efficiency in the construction sector, as by the recently adopted European Energy Performance of Building Directive. In this context, the article focuses on the role of geometry optimization in the schematic design phase of low-energy buildings, by considering it among different European climates. Indeed, this study aims to propose a multi-objective optimization approach (using a genetic algorithm) to optimize the “genes” of the building, e.g., shape, proportions, orientation and window-to-wall ratio of residential buildings in the early design phase, to cut off a significant portion of energy consumptions. The objective is thus to minimize heating and cooling energy needs based on the best combination of the above-mentioned genes. The research investigates optimal solutions across various European climates based on the Köppen-Geiger classification, comparing the results for 19 European cities with varying climate. The findings confirm that the energy needs of buildings are strongly influenced by the climate conditions of their location. The study, which comprehends almost 250.00 different configurations, assesses, as expected, the strong effect of climate conditions on the energy needs and highlights the cross-shaped buildings as the best performing in 17 over 19 sites investigated. The optimal solution for each site leads to total energy needs that are comprised between 4.58 kWh m-2 y-1 in Porto and 19.84 kWh m-2 y-1 in Goteborg, with an average across all cities of 12.45 kWh m-2 y-1. The research provides valuable insights for professional in the construction sector, aiding them in making informed decisions during the schematic design phase to achieve low-energy buildings that are adapted to specific climates.

Is the Traditional Rural Architecture in the Periphery of Istanbul Climate-Friendly? The Case Study of Şile, Gökmaslı

Nowadays, the decrease in available resources due to excessive use and the deterioration of ecological balance haverevealed the necessity of developing approaches compatible with nature for the whole world. The effects of theseapproaches have been seen for a long time in the construction industry, which constitutes a significant part of energyconsumption, and therefore in the field of architecture. There is an increasing environmental awareness not only ofthe design and implementation phases of new buildings but also of reconsidering existing historical rural settlementsbuilt according to natural and climatic conditions in the past. This paper aims to verify/falsify the theory that it wouldbe beneficial to protect and sustain the traditional rural architectural heritage in combating the negative effects of theclimate crisis, which is widely accepted in the literature. These criteriawere questioned in-depth on a case, which have rural heritage value. The existing physical environment in the Gökmaslı rural settlement of Şile on urban periphery of Istanbul was examined in terms of ecological sustainability, and the possible contributions of the preservation of historical settlements to climate adaptation studies are discussed.

BIM Legal: Implementation of a standard for Cadastral Registration of Apartment Complexes in 3D

Abstract. The potential of Building Information Models (BIM) to establish rights and responsibilities for multi-level building complexes in cadastral registrations has been explored in many previous researches. However, the implementation of BIM-based cadastral registrations in practice remains limited due to the complex interplay between technical potentials and legal implications as well as uncertainty about the additional complexity of a BIM model and the extra work that will be required to generate the BIM Legal model. In collaboration with Netherlands Kadaster, we have investigated the data requirements for a BIM Legal model that will support the 3D cadastral registration of apartment complexes and that aligns with BIM creation processes in practice. The BIM Legal model aims to visualise the spatial aspects of apartment complexes and to align the cadastral registration to the 3D data that is generated in the design and construction phase of new buildings. The BIM Legal file will be submitted when an apartment complex is being registered and is based on IFC, the open standard established by BuildingSMART International and used in the BIM domain. To make the implementation of BIM Legal feasible legally, technically, and economically, we apply a 3-phase approach. This paper presents the BIM Legal model as defined in Phase 1, which enables to generate a BIM Legal model compliant with current legislation frameworks with no/minimal manual interaction from BIM models as commonly generated in design processes. The paper describes the 3-phase approach, the context of Phase 1, the data requirement analyses, the defined BIM Legal data model, as well the questions that emerged during the specification process that need to be answered to further improve the implementation of Phase 1 and to further develop BIM Legal for Phases 2 and 3.

Tracer Observation of Queuing Behavior During New Year’s Visits to Shrines/Temples Using GPS Log Data

Crowd behavior during customary New Year's visits to shrines/temples in Japan was investigated. During these mass gatherings, visitors form a queue along the approach to the Main Hall of the shrines/temples. The unidirectional flow of the queue as the visitors approach the Main Hall to perform rituals is managed by police. The author observed the queuing behavior of visitors by joining the procession and tracked his position over time using a GPS logger. The author also observed the surrounding geometrical features and the procedures for guiding the crowd. Control methods, such as cordons and preparation of extra queuing space, were examined based on the observational data and compared with those of building/fire evacuations. The “everyone is welcome” aspect of New Year's visits required not only cordons in front of bottlenecks such as gates, stairs, and praying areas, but also alteration of the queuing space to accommodate for expansion of the crowd size. In contrast, considering building/fire evacuations, occupancy can be estimated or controlled by ticket quantity or density. Therefore, the accumulation of evacuees at bottlenecks can be predicted and should be considered in the building design phase. Different events or facilities require distinct crowd management approaches.

Simulation Study on Student Residential Energy Use Behaviors: A Case Study of University Dormitories in Sichuan, China

Studying the energy use behavior of occupants is crucial for accurately predicting building energy consumption. However, few studies have considered the impact of occupant behaviors on energy consumption in university dormitories. The objective of this study is to establish an agent-based model of energy consumption for university dormitories based on energy use behavior. The dormitories of a typical university in Sichuan, China, were subdivided into three clusters using a two-step cluster analysis. Subsequently, the energy use behaviors of occupants in each type of dormitory were characterized to establish a stochastic energy use behavior model. On the basis of the above, NETLOGO was used to construct an agent-based model for dormitories’ energy consumption to dynamically simulate energy use behavior. The accuracy of the model was verified by comparing the simulated values with the measured data. Finally, a building-energy-friendly retrofit scheme was proposed, and it was found that the optimized dormitory reduced energy consumption by 16.07%. Therefore, the results can provide information support for energy-saving decisions during the early design and retrofit phases of buildings. With the popularity of centralized supply, the research methodology may provide an extensive reference for energy management policies and sustainable strategies in the building sector.

Predictive models of embodied carbon emissions in building design phases: Machine learning approaches based on residential buildings in China

As one of the major architectural forms, residential building construction consumes considerable resources, and it has been regarded as a crucial factor for the implementation of carbon peaking and neutrality targets. Estimation of carbon emissions is essential for making informed decisions regarding building design and carbon reduction measures. Some studies have established predictive models for building operational carbon emissions. However, there are relatively few studies concerning the prediction of embodied carbon emissions. This study established a dataset containing 850 residential building samples. Based on the trade-offs and combinations of different explanatory variables, including building features and material use, this study developed two-phase models. These models, incorporating six scenarios, predicted embodied carbon intensities using twelve machine learning algorithms. For the planning design phase, an extremely randomized tree model using the building height, structural form, seismic fortification intensity, delivery form, geographical region, and material cost as inputs was favored considering R2 as 0.821 on the testing dataset. For the preliminary design phase, an extreme gradient boosting model using both building features and material intensities provided superior performance with R2 and MAPE values of 0.917 and 0.038, respectively. The optimal models and relevant feature importance analysis can be helpful for efficiently predicting embodied carbon emissions, and therefore, facilitate low-carbon designs.

A Work Breakdown Structure for Estimating Building Life Cycle Cost Aligned with Sustainable Assessment—Application to Functional Costs

The tools used for budgeting in the building design phase are still insufficient to address the life cycle of the building in terms of environmental and cost impacts. The main objective of this research is to define a model for extending existing cost databases to accommodate life cycle sustainability assessment. For this, current classification systems are reviewed and a case study has been analysed using the new approach. To this end, a new system of classification of construction information is proposed for the evaluation of early design costs, when data are scarce and the only information available refers to the gross interior area and the plot. The classification organizes the costs in a similar way to the sustainability assessment in EN-15643. A subcategory has been added for revenue, developer costs, and taxes at all stages of the lifecycle. The resulting classification is applied to the functional elements of a secondary school project. In the case study, construction costs represent 21% while the use stage accounts for 72% in a 100-year lifespan. The results show that, starting from generic cost bases, more complex costs and functional costs can be defined at different stages of the life cycle and adjusted to sustainability assessment standards.

Economic optimization of exterior wall insulation in Chinese office buildings by coupling artificial neural network and genetic algorithm

Envelope insulation is an essential measure to reduce building energy consumption and is the focus of many building energy codes. In China, the current standard (GB 55015-2021) only specified limit values for the thermal conductivity (U) of the exterior walls, and it ignored variations in building characteristics and internal parameters. Therefore, it is difficult for architects to quickly determine the exterior wall U-value in building design and retrofit. To address this issue, the exterior wall U-values of office buildings in China were economically optimized by TRNSYS, ANN, and GA. To begin with, the effect of enhancing exterior wall insulation on the heating and cooling energy consumption of office buildings was investigated by TRNSYS software, taking into account variations in building characteristics. Moreover, the exterior wall U-values of office buildings were optimized by coupling ANN and GA. The results showed that the design values of the GB 55015-2021 did not achieve the optimal results in China, and the most economical exterior wall U-value was 0.24 W/(m2·K) in Harbin, 0.24 W/(m2·K) in Beijing, 0.42 W/(m2·K) in Changsha, 1.82 W/(m2·K) in Guangzhou, 0.66 W/(m2·K) in Kunming. Compared with the pre-optimization, the annual life cycle cost of building heating and cooling reduced by 0.96 % in Harbin, 2.07 % in Beijing, 1.44 % in Changsha, 1.68 % in Guangzhou, and 7.37 % in Kunming. In addition, variations in building parameters should be considered in the design phase of new buildings or in the renovation of old buildings, such as internal heat gain, which may lead to different optimal results.

Integrating BIM and machine learning to predict carbon emissions under foundation materialization stage: Case study of China's 35 public buildings

For the significant energy consumption and environmental impact, it is crucial to identify the carbon emission characteristics of building foundations construction during the design phase. This study would like to establish a process-based carbon evaluating model, by adopting Building Information Modeling (BIM), and calculated the materialization-stage carbon emissions of building foundations without basement space in China, and identifying factors influencing the emissions through correlation analysis. These five factors include the building function type, building structure type, foundation area, foundation treatment method, and foundation depth. Additionally, this study develops several machine learning-based predictive models, including Decision Tree, Random Forest, XGBoost, and Neural Network. Among these models, XGBoost demonstrates a relatively higher degree of accuracy and minimal errors, can achieve the RMSE of 206.62 and R2 of 0.88 based on testing group feedback. The study reveals a substantial variability carbon emissions per building's floor area of foundations, ranging from 100 to 2000 kgCO2e/m2, demonstrating the potential for optimizing carbon emissions during the design phase of buildings. Besides, materials contribute significantly to total carbon emissions, accounting for 78%–97%, suggesting a significant opportunity for using BIM technology in the design phase to optimize carbon reduction efforts.

A Quality Management Method for Prefabricated Building Design Based on BIM and VR-Integrated Technology

Quality management in the design phase is crucial for determining the overall quality of prefabricated buildings. However, traditional design methods can no longer meet the complex design, component, and nodal requirements of prefabricated buildings. This study proposes a quality management framework for the prefabricated building design phase based on building information modeling (BIM) and virtual reality (VR) technologies to enhance design precision and satisfaction. Applying this framework to a prefabricated building project in Shenzhen, China, it was found that compared to traditional 2D drawing methods, the design issues feedback during drawing reviews decreased by 41.35%. Compared to solely using BIM technology, the number of design collisions identified through collision detection increased by 28.35%, and feedback on design issues during drawing reviews decreased by 15%. Furthermore, the framework was tested to prove its usability, effectiveness, and functionality. The framework, integrating the rich architectural information of BIM with the immersive experience of VR, contributes to focusing on the design process, improving design tools, optimizing design workflows, significantly reducing design errors, and enhancing the quality of prefabricated buildings.

Machine learning techniques for diagrid building design: Architectural–Structural correlations with feature selection and data augmentation

Artificial intelligence (AI) and machine learning (ML) techniques are transforming building engineering. This work goes through the critical role of architectural parameters in influencing the structural responses of tall buildings, with a special focus on diagrid structures. The main aim of this study is to demonstrate how ML can improve the early design phase of diagrid buildings. Using a small, initially collected data set, enhanced through data augmentation, the classification of diagrid buildings in terms of design feasibility is investigated. This study identifies key architectural and structural parameters, employing various filter and wrapper methods for feature selection. The results show that our methods are effective in producing high-quality synthetic data, maintaining stable learning accuracies, and establishing accurate and robust relationships between architectural parameters and structural responses in diagrid buildings. These insights are crucial for facilitating more effective design processes in the realm of high-rise diagrid building design.

Optimizing Insulation Material Selection in Conceptual Building Design: A Simulation-Based Study on Lifecycle Cost and Carbon Emissions

Insulation materials play a crucial role in reducing a building’s energy demand and carbon emissions. To optimize building lifecycle costs and reduce carbon emissions, this study developed an energy consumption simulation method specifically for the conceptual design phase of buildings to assess the impact of insulation material selection. Through this method, the study obtained the energy performance of buildings and calculated the lifecycle cost and carbon emissions data. A comparative analysis of different design schemes and material choices was then conducted. The results indicate that a rational selection of insulation materials can significantly reduce related costs by 75% and carbon emissions by 81%. The significant variations in cost and carbon emissions among different conceptual design styles further emphasize the importance of using simulation methods in the early stages of building design to optimize both cost and carbon emissions.

Exploring building component thermal storage performance for optimizing indoor thermal environment – A case study in Beijing

Optimizing the thermal storage of building components is crucial for improving indoor thermal conditions and reducing heating energy consumption. However, existing studies often overlook the effect of the substantial thermal mass in common building components, each storing different levels of heat. This study finds that considering this thermal mass and its energy during the building design phase can significantly save insulation material costs and heating energy consumption.Our work is built upon the analysis of the thermal behaviors of real buildings. We collected data from 43 representative rooms in cold regions and utilized Multiple Linear Regression models to examine how solar radiation and outdoor temperatures affect thermal mass in external walls, internal walls, and floors. We also used Probabilistic Density Distribution models to study heat transfer within these components. Subsequently, we applied Conduction Transfer Functions with just a 2.08% error rate to derive an optimal passive design strategy for year-round use of building thermal mass.Experimental results show that our strategy saves more energy by 0.78 kWh/m2 without increasing the insulation material cost, exceeding current standards. In cold regions, our study suggests focusing on mitigating the negative effects of building thermal mass, which offers greater energy savings than exploiting its positive aspects. Moreover, our findings can be easily integrated into the optimization of physical properties like thermal capacity and insulation for either improving stock buildings or designing new buildings, further enhancing their energy and material efficiency.

Computational Segmentation of Timber Slabs with Free Column Placement

Modular floor slabs must be subdivided into prefabricable, transportable segments. This slab segmentation process conventionally uses a rectangular pattern, particularly for timber buildings. Regular segmentation patterns and strict column grids are ideal for rectangular building shapes, but restrict timber buildings to only some architectural uses, and are unideal for urban infill. Unfortunately, planning and constructing multi-storey wood buildings without a strict grid is still challenging. There is therefore a conflict between the desired column placement and the constraints imposed by building systems. This article investigates novel methods for segmenting timber floors supported by irregular column layouts. It proposes six different segmentation methods that are informed through Co-Design by structural, material waste, and transportation requirements. Co-Design allows for the direct integration and automated feedback of such diverse criteria into the early building design phase. These methods are based on three well-known computational approaches: Single-Objective Optimisation, Parametric Modelling, and Agent-Based Modelling. They could also be applied to other non-timber prefabricated floor systems. The segmentation methods are demonstrated on two example floor slabs with irregular column layouts, one with a rectilinear and the other with an irregular outline. The methods are compared using quantitative proxies for cost, fabrication time, architectural adaptability, and assembly complexity. More benchmark testing is needed, but initial results showed that the most efficient segmentations cannot adapt to irregular layouts, emphasising the need for a more adaptable approach to modular timber construction.

A study to depict challenges and opportunities building industry professionals face when designing inclusive and accessible buildings

Inclusive Design has been widely promoted in the fields of product, engineering, and user experience design. Despite the educational efforts made by scientists, practitioners, and institutions to raise awareness about accessibility and inclusion, Inclusive Design has not been widely embraced in architectural design practice, where it is often associated with design for disability. This multidisciplinary study, spanning behavioural science, ergonomics, and the social sciences of architecture, explores the challenges architectural design practitioners face when designing inclusively, and identifies opportunities to promote the adoption of Inclusive Design. The results of a questionnaire completed by 114 architectural design practitioners underscore the lack of client awareness of the benefits of inclusive design, highlight the important role practitioners can play in advocating for Inclusive Design, and emphasize the need to develop practices and tools that enhance the design and post-design phases of buildings to ensure inclusion, diversity, equity, and accessibility.

Rethinking building envelope design: Machine learning approaches to evaluate its impact on indoor ozone exposures

Ozone is widely recognized as an ambient air contaminant that causes acute and chronic health effects. However, there is a limited number of studies investigating indoor exposures to ozone in occupied houses and linking design variables to the predictive power of indoor ozone levels. This study focuses on typical envelope airflow paths used in residences in the Philadelphia area in the United States. The model development draws from the field data, including indoor and outdoor ozone concentration, environmental parameters, and building characteristics from four building envelopes. Five machine learning algorithms (i.e., support vector machine, lasso regression, random forest, Bayesian bridge regression, and gradient boosting) are employed, with indoor ozone concentration as the dependent variable, as it indicates how the hot and sunny weather that might lead to the possibility of indoor air quality (IAQ) alerts due to ozone. The results showed that gradient boosting model based on all field measurements had the highest R-squared value of 0.974 and low enough root mean square error (RMSE) and mean absolute error (MAE) which are 1.182 and 0.788, respectively. We conclude that indoor ozone forecasting model based on inputting environmental survey (ES) in addition to either design variables or indoor environment characteristics can effectively predict and can therefore be used at the building design phase to improve healthy living environments.

Enhancing energy efficiency and cost-effectiveness while reducing CO2 emissions in a hospital building

Global population growth drives fossil fuel usage, surpassing natural greenhouse gas emissions and causing climate change, higher temperatures, floods, and agricultural erosion. The study underscores the significance of appropriate material selection and meticulous building design to establish a healthy living environment and mitigate energy consumption. The research is dedicated to the reduction of CO2 emissions. Hospitals, due to their constant energy requirements, require optimal temperature and comfort management for patients, necessitating careful design to avoid disruptions and power outages. The principal objective of this research is to enhance energy efficiency in the design phase of hospital buildings in Turkey and to develop an energy-efficient hospital model. This objective is achieved by evaluating different insulation materials, building orientations, lighting efficiency, and window-to-wall ratios. The methodology involves creating a reference structure for energy load calculations using Revit software and utilizing the Green Building Studio (GBS) program to conduct energy analyses in 7 different cities across Turkey. The study found that the utilization of building parameters with renewable energy sources reduced energy consumption by 57.5%, total costs by 16.24%, and CO2 emissions by 26.3%. The fundamental contribution of this study is to demonstrate the feasibility of reducing energy consumption, costs, and CO2 emissions through design adjustments. The novelty of this research lies in its comprehensive approach to optimizing energy efficiency and CO2 emissions in hospital buildings in Turkey. These findings underline the significance of energy-efficient design, particularly considering the impact of increased energy usage and CO2 emissions during the COVID-19 pandemic.

VENTILATION SOLUTIONS TO THE OVERHEATING PROBLEM IN THE ATRIUM: TRAKYA UNIVERSITY VOCATIONAL SCHOOL OF TECHNICAL SCIENCES BUILDING

Atriums are architectural solutions that are addressed during the design phase of buildings, aiming to make the outdoor lighting conditions feel inside the building, thanks to their large glass surfaces. In addition to the aesthetic appearance it gives to the buildings, it provides maximum use of daylight functionally. However, if the correct glass type is not used and does not contain sufficient shading elements, overheating, glare, etc. brings problems. When this situation becomes to affect the comfort conditions of the individual's indoor environment, it begins to significantly affect the learning and working performance, especially in educational buildings. If appropriate glass is not used during the production phase of the glass building, which creates a greenhouse effect, in other words, it is difficult to produce a permanent and sustainable solution to this effect in the building with the measures taken afterwards, and even in some cases it is not possible. In this case, turning to mechanical solutions emerges as an option that helps to idealize indoor comfort conditions. In this study, it is aimed to reduce the greenhouse effect created by the atrium of Trakya University Technical Sciences Vocational School with passive cooling strategies within the building and construction elements in terms of summer comfort. The thermal comfort problems of this building, which was renovated within the scope of the Scientific Research Project, were examined, the mutual cross-ventilation effect, which requires low cost, and the reflective coating application on the glass components on the roof, reflecting the incoming solar energy and preventing the excessive heat gain in the summer months due to the sunlight of the building envelope, eaves, blinds, etc. Developing additional add-ons by determining the appropriate angle, solution suggestions were tried. However, all these solutions ensured that the building was cooled by a maximum of 10 degrees, and a mechanical cooling solution was deemed necessary for the cooling of the building. In this study, mechanical ventilation solutions are presented to prevent the greenhouse effect created by the atrium of Trakya University Technical Sciences Vocational School. Although its high cost in terms of energy consumption and initial investment is disadvantageous, mechanical ventilation is considered to be an effective suggestion in solving the problem.