With climate change, the indoor built environment is expected to influence the occupant's safety and well-being significantly. A novel multi-criteria thermal resilience certification scheme for indoor built environments during extreme heat events is proposed in this paper. The certification scheme considers overheating, thermal comfort, heat stress, and hygrothermal discomfort in built environments. These criteria are quantified using key performance indicators like indoor overheating degree, hours of exceedance, wet-bulb globe temperature, and heat index, respectively. This scheme is developed based on existing best practices like standards, rating systems, and literature. The scheme is implemented on a benchmark building energy performance model for detached post-World War II dwellings in Belgium as a case study using weather data measured from the City of Brussels. The indoor overheating in the reference dwelling is assessed with a static threshold of 27°C for the bedrooms and adaptive thresholds for other areas. The analysis found that the building performance is within the defined threshold levels throughout the heat wave duration for all criteria. Therefore, the reference dwelling got a maximum attainable score of four points and is rated five-star for thermal resilience during heat waves. The proposed certification scheme is intended as a standardized framework and highlights the need for further revisions in building performance policies and guidelines.

The demand for temporary housing for refugees and displaced communities has led to the exploration of earthbag buildings. While these structures are affordable and sustainable, they often struggle with thermal discomfort in extreme climates. This study aims to examine the integration of phase change materials (PCM) into earthbag walls to improve thermal performance. The research involved incorporating paraffin wax and microencapsulated PCM into scaled-down earthbag walls, with their performance evaluated in a controlled environment. The results were validated against a numerical simulation model developed in EnergyPlus. The study revealed significant thermal improvements with PCM integration. Wall-2, with paraffin wax A31, demonstrated a surface temperature reduction of up to 1.9°C, while Wall-3, with microencapsulation Inertek26, showed a decrease of 2.40°C compared to the reference wall. A parametric analysis highlighted the importance of PCM layer thickness. Specifically, Wall-2 with a 6 cm paraffin wax layer achieved a maximum reduction of 4.0°C compared to the base case. The study identified the transition temperature of PCM as a critical factor in thermal performance, with paraffin wax A31 emerging as the optimal choice. Placing the PCM layer on the interior surface of the wall was more effective than exterior placement. Overall, PCM integration in earthbag walls offers a promising solution to enhance thermal comfort in temporary housing, addressing the critical needs of refugees and displaced communities. This research fills existing gaps in thermal comfort in temporary housing and demonstrates the potential of PCM as an innovative passive design strategy.

Indoor air quality significantly enhances employee productivity and well-being in offices. Existing models and guidelines emphasize wind-driven natural ventilation for air exchange and thermal comfort but often overlook detailed airflow patterns. Understanding airflow dynamics is crucial for designing healthy offices, and offering insights into air exchange processes. This information is particularly valuable in mitigating the impact of CO2 and droplet release from multiple occupants, contributing to the creation of healthier office environments. This study, thus, employs a validated CFD model to investigate the impact of geometrical parameters on wind-driven ventilation in offices. With about 150 cases representing alterations in parameters for single-sided (SV) and double-sided (DV) ventilation, a sensitivity analysis identifies key contributors to airflow patterns. Eventually, while five major categories for the airflow patterns can be identified in the DV cases (i.e., (1) without a weak zone (WZ), (2) with a dominant WZ, (3) with a WZ on bottom side, (4) with a WZ on upper side, and (5) with two WZs on upper and bottom sides), a generic airflow pattern can be barely seen in the SV cases. Moreover, in the DV cases, velocity magnitude is crucial for classification of the outputs. The leeward window geometry influences DV natural ventilation more than the windward window. Furthermore, the room dimensions impact ACH more than SF6 concentration and velocity. In the SV cases, location of the infected occupant dominates air changes per hour (ACH), and theta significantly impacts average velocity in contrast to the DV scenarios.

Recent research focuses on optimal design of thermal energy storage (TES) systems for various plants and processes, using advanced optimization techniques. There is a wide range of TES technologies for diverse thermal applications, each with unique technical and economic characteristics. Matching an application with the most suitable TES system remains challenging. This study proposes an eight-step design methodology guiding the process from describing the thermal process to defining the most appropriate TES based on constraints and requirements. The steps include specifying the thermal process, system design parameters, storage characteristics, integration parameters, key performance indicators, optimization method, tools, and design robustness. Seven already-designed TES systems are evaluated to assess the methodology's effectiveness, where the design procedures have been adapted to the proposed steps. Case studies involve various applications with both sensible and latent TES systems, demonstrating the applicability of the proposed design procedure. A significant diversity exists among the design cases regarding the design objective, input, design, and output parameters. Nevertheless, the design procedure in each case can be deconstructed into the outlined design steps. The last design step has been excluded from all case studies due to insufficient information regarding the robustness of the design process. The paper demonstrates how a methodical approach can be applied to examine the TES design and the integration. The design steps proposed in this study can serve as a foundation for developing a more systematic approach for designing TES systems in future works, resulting in simplifying the design process.

The data indicate that merely improving energy efficiency within energy-efficient buildings (EEBs) is insufficient to significantly reduce the energy demand of the building sector. To achieve substantial reductions, strategies must also focus on increasing the number of EEBs within the existing building stock. However, research in this area remains limited. Therefore, this study aims to explore the current market demand and barriers for EEBs, examine the impact of various design decisions on housing prices, identify the factors influencing the marketability of residential buildings, and analyze customer purchasing decisions in Turkey (T & uuml;rkiye). For this purpose, a comprehensive literature review was first made. It was observed that factors such as macroeconomic conditions, sales price, housing opportunities, location, brand, customer demographics, energy efficiency, housing features, and aesthetics were frequently discussed in the literature. Based on the literature review and preliminary study results, among other factors, aesthetic appreciation is considered the most applicable design strategy, and windows and balconies are identified as building components that can simultaneously affect energy efficiency, marketability, and aesthetics. Then, as a preliminary study to determine major marketing strategies, the housing marketing strategies were surveyed and analyzed from the real estate sector in different cities as provided in the advertisements posted on their websites. Furthermore, a comprehensive e-mail survey was conducted with 351 different real estate companies amongst 22 cities of T & uuml;rkiye. Based on the findings, enhancing architectural designs could potentially elevate the perceived value of energy-efficient homes by up to 18% among consumers and this can increase the marketability.

The increasing demand for temporary housing in many developing countries necessitate the use of sus-tainable and affordable construction options. Earthbag units have the potential to be integrated into such housings as they are inexpensive, sustainable, and straightforward material options for building struc-tures. Nevertheless, due to their thermal characteristics, earthbag units cannot provide a thermally com-fortable environment.Thus, the present study focuses on developing an environmentally and sustainable earthbag unit inte-grated with phase change materials (PCM) to convert severely harsh indoor spaces to moderately harsh ones. For the design and development of earthbag blocks, several units are developed with varying amounts of PCM encapsulated in expanded perlite (EP) and expanded graphite (EG) within each unit, including block A (reference), Block B (PCM 2.2% of sample weight), C (4.3%), and D (6.5%). An experimen-tal study is then conducted to understand the microstructural properties of the embedded PCM compos-ite in soil. Following this initial study, practical differential techniques, including differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscope (SEM), thermal con-ductivity, and Oozing circle test, have been employed over the developed units to measure their thermal characteristics. Test results from DSC and TGA show good thermal stability of PCM and PCM composites, while SEM results indicated that PCM is well distributed within the pores of EP at 50%EP of the PCM weight. The study found the average indoor surface temperatures by block B, block C, and block D to drop compared to the reference block about 1.2 degrees C, 3.3 degrees C, and 4.1 degrees C, respectively. This clearly shows the ben-efit of integrating phase change materials in an earthbag unit.(c) 2023 Elsevier B.V. All rights reserved.

Although outdoor thermal comfort is extensively investigated in urban areas, the measures are barely focused to determine the walkability through these spaces. Therefore, a space with a high level of thermal comfort can experience a low level of pedestrian agglomeration while a space with a low level of thermal comfort can be massively used by inhabitants. Therefore, the solution to urban design and planning can be significantly altered if both dimensions are simultaneously taken into the account. This study investigates the relationship between spatial configuration and thermal comfort potential to evaluate the effect of spatial configuration on outdoor environmental quality. For this purpose, a framework is developed to understand the impact of built urban areas on thermal comfort and space syntax performance using a high-resolution spatial model to simulate the correlation of thermal comfort and betweenness centrality of a case study neighbourhood in the hot and humid climate area of Al-Khobar in Saudi Arabia. The mixed-use neighbourhood is analysed by the universal thermal comfort index and several space syntax metrics. The presented study uses Grasshopper environment and Ladybug and Decoding Spaces tools. The simulation study expressed that significant changes in orientation and buildings heights have a remarkable effect on improving OTC and space syntax in the urban neighbourhood.

In the last few years, the renovation and refurbishment of existing buildings have been recognized as one of the main strategies to achieve energy efficiency and sustainability goals. However, the current studies have mainly focused on the retrofit, life cycle assessment (LCA), and Life Cycle Cost (LCC) of buildings in isolation without envisaging the impact of microclimate and the surrounding buildings on the outcome of energy simulation. Specifically, many energy simulation software needs to include the environmental responses when buildings are treated with outdoor conditions based on weather data from the nearest metrological site. Therefore, this study aims to investigate the impact of microclimate on retrofit and LCC of a community of buildings rather than a single isolated building. For this purpose, a coupling method is developed to integrate building energy simulation (BES) and computational fluid dynamics (CFD), which exchange parameters on a dynamic time step basis using Envi-met to create weather files from microclimate parameters and use it on energy simulation through DesignBuilder software. Furthermore, this study interlinks the life cycle cost assessment and retrofit strategies on a community scale. A case study of Amman – Jordan, is selected in this paper by one a residential building with two floors and an area of 450. At the same time , the retrofit strategy is considered as implementing green roofs for community areas, which are implemented in the context around the buildings. In addition, this study calculates the net present value and the pack period regarding the life cycle cost study. The initial result shows that there is an impact for microclimate parameters on the temperatures gained on the building's envelope as a result of the effect of airflow through context parameters, which in turn affect the value of energy consumption used for cooling inside the buildings. Moreover, this paper demonstrates that using green roofs on one of the neighbourhood buildings will decrease energy consumption by 28% in the simulated time while the payback period is 9.5 years.

Experimental investigations using wind and water tunnels have long been a staple in fluid mechanics research. These experiments often choose a specific physical process to be investigated, whereas studies involving multiscale and multiphysics processes are rare. In the era of climate change, there is increasing interest in innovative experimental studies in which fluid (wind and water) tunnels are used in the modeling of multiscale, multiphysics phenomena of the urban climate. Fluid tunnel measurements of urban-physics-related phenomena are also required to facilitate the development and validation of advanced multiphysics numerical models. As a repository of knowledge for modeling these urban processes, we cover the fundamentals, experimental design guidelines, recent advances, and outlook of eight selected research areas, i.e., (i) absorption of solar radiation, (ii) inhomogeneous thermal buoyancy effects, (iii) influence of thermal stratification on land-atmosphere interactions, (iv) indoor and outdoor natural ventilation, (v) aerodynamic effects of vegetation, (vi) dispersion of pollutants, (vii) outdoor wind thermal comfort, and (viii) wind flows over complex urban sites. Three main challenges are discussed, i.e., (i) the modeling of multiphysics, (ii) the modeling of anthropogenic processes, and (iii) the combined use of fluid tunnels and scaled outdoor and field measurements for urban climate studies.

More accurate tools are required to replicate urban climates to achieve healthy and comfortable urban environments. To this end, this study implements a novel high-resolution simulation framework to improve the OTC modelling by dynamic coupling of convective fluxes calculated by computational fluid dynamic (CFD) model, and dynamic building energy simulation (BES) for analyzing outdoor surface temperature of buildings. In addition, radiative fluxes emitted from building surfaces are coupled with latter models. The workflow is applied at the Grasshopper platform based on the results of ANSYS Fluent as the CFD and EnergyPlus as the BES tools. This framework is tested within a generic case study representing an urban neighbourhood. As a result of this framework, tempo-spatial values for OTC are achieved at each time-step of simulation and then compared with the OTC values from the traditional OTC modelling approach. Statistical analysis of results shows that the OTC valued predicted using the coupled method can change considerably compared to OTC results from traditional methods at the neighbourhood scale.

Airborne transmission is an important route of spread of viral diseases (e.g., COVID-19) inside the confined spaces. In this respect, computational fluid dynamics (CFD) emerged as a reliable and fast tool to understand the complex flow patterns in such spaces. Most of the recent studies, nonetheless, focused on the spatial distribution of airborne pathogens to identify the infection probability without considering the exposure time. This research proposes a framework to evaluate the infection probability related to both spatial and temporal parameters. A validated Eulerian-Lagrangian CFD model of exhaled droplets is first developed and then evaluated with an office case study impacted by different ventilation strategies (i.e., cross- (CV), single- (SV), mechanical- (MV) and no-ventilation (NV)). CFD results were analyzed in a bespoke code to calculate the tempo-spatial distribution of accumulated airborne pathogens. Furthermore, two indices of local and general infection risks were used to evaluate the infection probability of the ventilation scenarios. The results suggest that SV has the highest infection probability while SV and NO result in higher dispersions of airborne pathogens inside the room. Eventually, the time history of indices reveals that the efficiency of CV and MV can be poor in certain regions of the room.

Pathogen droplets released from respiratory events are the primary means of dispersion and transmission of the recent pandemic of COVID-19. Computational fluid dynamics (CFD) has been widely employed as a fast, reliable, and inexpensive technique to support decision-making and to envisage mitigatory protocols. Nonetheless, the airborne pathogen droplet CFD modeling encounters limitations due to the oversimplification of involved physics and the intensive computational demand. Moreover, uncertainties in the collected clinical data required to simulate airborne and aerosol transport such as droplets' initial velocities, tempo-spatial profiles, release angle, and size distributions are broadly reported in the literature. There is a noticeable inconsistency around these collected data amongst many reported studies. This study aims to review the capabilities and limitations associated with CFD modeling. Setting the CFD models needs experimental data of respiratory flows such as velocity, particle size, and number distribution. Therefore, this paper briefly reviews the experimental techniques used to measure the characteristics of airborne pathogen droplet transmissions together with their limitations and reported uncertainties. The relevant clinical data related to pathogen transmission needed for postprocessing of CFD data and translating them to safety measures are also reviewed. Eventually, the uncertainty and inconsistency of the existing clinical data available for airborne pathogen CFD analysis are scurtinized to pave a pathway toward future studies ensuing these identified gaps and limitations.

When evaluating the outdoor environment, it is essential to improve the accuracy of outdoor thermal comfort (OTC) modelling by investigating the simultaneous interactions of both convective and radiative fluxes. The majority of the existing models, however, employed to evaluate thermal comfort, do not consider these co-effects. This study aims to develop a novel and comprehensive framework for OTC modelling while using non-isothermal airflow and surface temperatures within street canyons. For this purpose, a dynamically coupled building energy simulation (BES) and computational fluid dynamics (CFD) model, previously developed by authors, is used to provide detailed analysis of convective fluxes. These values in addition to the simulated radiative heat fluxes are then utilized to calculate the OTC at a neighbourhood case study during a typical hot day. The results show substantial changes (6.5% higher) in the OTC results using the newly developed coupled model in comparison to traditional (standalone) approaches. For example, in the coupled approach, the OTC values experience a wider range which peaks to at noon . Moreover, physiological equivalent temperature (PET) values are higher which shows higher level of discomfort and heat stress range compared to the standalone models.

COVID19 pathogens are primarily transmitted via airborne respiratory droplets expelled from infected bio-sources. However, there is a lack of simplified accurate source models that can represent the airborne release to be utilized in the safe-social distancing measures and ventilation design of buildings. Although computational fluid dynamics (CFD) can provide accurate models of airborne disease transmissions, they are computationally expensive. Thus, this study proposes an innovative framework that benefits from a series of relatively accurate CFD simulations to first generate a dataset of respiratory events and then to develop a simplified source model. The dataset has been generated based on key clinical parameters (i.e., the velocity of droplet release) and environmental factors (i.e., room temperature and relative humidity) in the droplet release modes. An Eulerian CFD model is first validated against experimental data and then interlinked with a Lagrangian CFD model to simulate trajectory and evaporation of numerous droplets in various sizes (0.1 mu m-700 mu m). A risk assessment model previously developed by the authors is then applied to the simulation cases to identify the horizontal and vertical spread lengths (risk cloud) of viruses in each case within an exposure time. Eventually, an artificial neural network-based model is fitted to the spread lengths to develop the simplified predictive source model. The results identify three main regimes of risk clouds, which can be fairly predicted by the ANN model.

Symmetry is one of the key parameters in aesthetic judgement, and development of computational aesthetic approaches. Various experimental, statistical, and machine learning-based methods have been developed to parametrically measuring the symmetry, yet mathematical symmetry measurement models were barely studied. The development of mathematical symmetry measurement models can contribute to the development of symmetry-related models, computational aesthetic approach, and architectural design review. Accordingly, this research aims 1) to develop a mathematical model (symmetry index), and 2) to investigate the relationship between symmetry and aesthetic judgment. For this purpose, two surveys were conducted amongst 337 participants, the symmetry and aesthetic of 13 building images were evaluated, and the survey results were compared to the developed symmetry index. According to the findings, a positive correlation between symmetry and aesthetic appreciation was found and the influence of demographic differences on the symmetry, and aesthetic perception was discussed. The developed model successfully predicts the symmetry of studied buildings' images.

Urban heat island (UHI) has multiple negative impacts on cities from heat related morbidities to excessive energy demands by buildings. Hence, better understanding of the contributing factors on its formation ensues ene efficient mitigation of these adverse effects. Previous studies demonstrate a significant correlation between the vertical elevation of urban morphology and UHI, however, topological parameters are barely considered. This study aims to improve the surface UHI prediction by integrating the impact of land surface elevation using a novel parameter of terrain factor (TF), which is integrated with other morphological parameters to develop an artificial neural network (ANN) model to predict the spatial distribution of UHI indicated by land surface temperature (LST). Morphological parameters were derived from two case studies representing areas with high terrain variation and relative flat terrain in Illinois, USA. The developed model was utilized to predict the LST for parts of the city, not initially included in the training process. Integration of TF significantly improves the LST predictions for high terrain variation areas, as the average root mean square error decreased from 1.26 to 0.90(circle)C and R-2 increased from 0.74 to 0.81. In conclusion, TF has significant impact on the surface UHI in areas with a significant surface relief variation.

Computational fluid dynamics (CFD) technique is well-known for its powerful capability of modelling the cross-ventilation. CFD is broadly coupled with energy simulation programmes, such as EnergyPlus, to expand its application in building energy calculation. During the coupling process, iterative calculation is required to improve the accuracy of the coupling method, which means the scale of the model should be designed with extra care so that the simulation can be practical in terms of computational cost. A coarse-resolution mesh (here denoted as CFD c ) cannot properly represent the required local environment to study the underlying physics. However, a fine-resolution CFD microclimate model (here denoted as CFD f ), which includes both indoor and outdoor spaces, always requires a large number of cells to capture the complexities of environment; this makes the coupling procedure a challenging problem. This study aims to propose an innovative, high-resolution and computationally cost-effective CFD f -CFD c model to overcome this gap. The full-scale CFD f works in an off-line manner at the preliminary simulation stage and generates detailed flow parameters at the interfaces for CFD c . At the dynamic stage of the simulation, CFD c participates in the coupling procedure with the other tools, for example, building energy simulation (BES) tool (e.g. EnergyPlus). The coupling of CFD f -CFD c -BES is about 200 times faster than an ordinary coupled CFD f -BES method with a significantly quicker and more stable achievement in the convergence.

Cross-ventilation flow in buildings is dominantly impacted by the characteristics of their surrounding built environment, specifically in highly-dense urban areas. Cross-ventilation in highly-dense urban configurations is studied using validated computational fluid dynamics models using the large eddy simulation approach. Mean flow properties, turbulent statistics, wind pressure, and crossing airflow rate are compared against different planar area ratios of 0≤λp≤0.6 and approaching wind angles of 0°≤α≤90° for a generic building model surrounded by nine identical building models. The transient airflow rate is analyzed considering different airflow definitions based on the time-averaged and fluctuating velocity decomposition. It is found that the difference between the time-averaged and instantaneous airflow rate is not negligible in a highly-dense urban configuration where the velocity is generally weak, but the flow direction is highly fluctuating. Furthermore, it is shown that time-averaged airflow rate calculations are not suitable for accurate prediction of cross-ventilation in sheltered buildings in medium and highly-dense urban configurations; this is because of the averaging procedure cancels out the velocity fluctuation and periodic flows through the openings. Moreover, it is proposed that the accumulative instantaneous ventilation rate can be more suitable for airflow rate calculations as it includes the instantaneous airflow exchanges.