Buildings In Zones Research Articles

Aerodynamic and codification study of low-rise buildings: Part II – Partially elevated structures

This study constitutes part II of an extensive study where the aerodynamics of elevated buildings is investigated using large-scale wind tunnel testing. Part II focuses on the case of elevated buildings with partially enclosed spaces beneath the elevated floor. For this purpose, four 1:10 scaled models of elevated single-story gable-roof buildings were selected, three of which were partially elevated with enclosed regions covering areas ranging from 19% to 54% of the model footprint. The tests aimed to examine the effect of the enclosed regions below the floor on the distribution of the localized peak pressure coefficients on the walls, floor, and roof surfaces of the models. Furthermore, the study evaluates the ASCE 7–22 provisions and the proposed provisions, presented by the authors in Part I, for estimating external wind pressure coefficients acting on the floor, roof, and walls of elevated buildings. The results indicate that enclosed regions below the floor significantly alter the aerodynamics of elevated low-rise buildings and could increase the wind-induced loads on the roof and walls of such structures, with the increase in some cases exceeding 80%. Furthermore, the results align well with the proposed modifications by the authors in Part I to the ASCE 7 provisions for estimating the external pressure coefficients for the various zones of low-rise buildings, addressing the underestimation issues previously identified within the current ASCE standard.

Unlocking solar potential in high-latitude urban areas: A study of morphological indicators and zero energy potential of Glasgow

The complexity of urban form can have a significant impact on the utilization of solar energy. While numerous studies have examined the influence of urban form on solar potential, the optimization of solar energy use in cities located at high latitudes remains a challenging subject. In this study, we focus on the high-latitude city of Glasgow, using residential buildings in urban grid cells as our sample. We calculate solar potential and urban form indicators for these buildings using the Digimap database and the ArcGIS Pro platform. Employing eight machine learning algorithms, we analyze the data and extract eight key morphological indicators that affect the solar potential of urban grid cells. Among these indicators, we select four indicators—roof slope, building density, plot ratio, and building perimeter shape factor—for cluster analysis, enabling us to classify urban building forms into five types based on their characteristics and solar potential. Our calculations demonstrate that effective utilization of solar energy offers significant zero energy potential for Glasgow. The findings of this research can provide valuable guidance in the early stages of urban planning and design, assisting policymakers in rationalizing the use of solar energy resources for sustainable urban development. Furthermore, the results help urban stakeholders identify variations in the solar potential of different building forms, aiding them in selecting appropriate building types and zones to maximize solar energy utilization.

Predictive building energy management with user feedback in the loop

Retrofitting buildings with predictive control strategies can reduce their energy demand and improve thermal comfort by considering their thermal inertia and future weather conditions. A key challenge is minimizing additional infrastructure, such as sensors and actuators, while ensuring user comfort at all times. This study focuses on retrofitting with intelligent software, incorporating the users’ feedback directly into the control loop. We propose a predictive control strategy using an optimization-based energy management system (EMS) to control thermal zones in an office building. It uses a physically motivated grey-box model to predict and adjust thermal demand, with individual zones modelled using an RC-approach and parameter estimation handled by an unscented Kalman filter (UKF). This reduces deployment effort as the parameters are learned from historical data. The objective function ensures user comfort, penalizes undesirable behaviour and minimizes heating and cooling costs. An internal comfort model, automatically calibrated with user feedback by another UKF, further improves system performance. The practical case study is an office building at the ”Innovation District Inffeld”. Operation of the system for one year yielded significant results compared to conventional control. Thermal comfort was improved by 12% and thermal energy consumption for heating and cooling was reduced by about 35%.

Urban Heat Island Differentiation and Influencing Factors: A Local Climate Zone Perspective

With the acceleration of urbanization, the urban heat island (UHI) effect has become a major environmental challenge, severely affecting the quality of life of residents and the ecological environment. Quantitative analysis of the factors influencing urban heat island intensity (UHII) is crucial for precise urban planning. Although extensive research has investigated the causes of UHI effects and their spatial variability, most studies focus on macro-scale analyses, overlooking the spatial heterogeneity of thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, this study took the central urban area of Chengdu, constructing a LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze the spatial clustering effects of UHI across different LCZs. By constructing Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models, the study further explored the influencing factors within these climate zones. The results showed that: (1) Chengdu’s built and natural environments had comparable proportions, with the scattered building zone comprising the highest proportion at 22.12% in the built environment, and the low vegetation zone accounting for 21.8% in the natural environment. The UHII values in this study ranged from 10.2 °C to −1.58 °C, based on specific measurement conditions. Since UHII varied with meteorological conditions, time, seasons, and the selection of rural reference points, these values represented dynamic results during the study period and were not constant. (2) Chengdu’s urban spatial morphology and UHII exhibited significant spatial heterogeneity, with a global Moran’s I index of 0.734, indicating a high degree of spatial correlation. The highest local Moran’s I value was found in the proportion of impervious surfaces (0.776), while the lowest is in the floor area ratio (0.176). (3) The GWR model demonstrated greater explanatory power compared to the OLS model, with a fit of 0.827. The impact of spatial morphological factors on UHII varied significantly across different environments, with the most substantial difference observed in the sky view factor, which has a standard deviation of 13.639. The findings provide precise recommendations for ecological spatial planning, aiming to mitigate the UHI effect and enhance the quality of life for urban residents.

Zone-based many-objective building decarbonization considering outdoor temperature and occupation uncertainty

Operational building decarbonization is challenging due to complex weather conditions and occupation uncertainty. This paper introduces a precise optimization framework integrating the building information modelling technique and intelligent algorithms to dynamically predict multi-scenario building carbon emissions and optimize the building emissions performance considering building zones and weather conditions. Firstly, the on-site data and building information modeling-supported building emissions simulation data are collected for model training. Secondly, using intelligent algorithms, zone-based hourly carbon emissions and multi-scenario carbon emissions prediction are conducted simultaneously. Thirdly, the optimal decarbonization strategies are conducted using intelligent algorithms under various weather conditions. This framework has been verified for decarbonization in a high-rise operational building. The results reveal that: (1) The carbon emissions prediction is highly consistent with the ground truth after considering the sub-zone correlations; the R2 for the west, south, and east zones are 0.900, 0.900, and 0.942, respectively; (2) The surrogate models can accurately predict carbon emissions and thermal comforts with all R2 are higher than 0.912. The optimization rate of the building reaches 59.2 % while the outdoor temperature is above 35 °C. (3) In the many-objective optimization model, considering occupation uncertainty makes the strategy close to the actual situation, reaching the decarbonization by 6815.23 kg compared to the empirical operation for the cooling period. This work provides a new path for operational building precise management and control-oriented optimization decarbonization.

Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building

Climate change has made energy management a global priority. In France, the Grenelle Environment has set very ambitious progress targets for positive-energy buildings, particularly in terms of reducing and managing energy consumption. However, effective energy management in multi-zone buildings presents significant challenges, particularly when considering the inter-zone dynamics and heat transfer. This study examines multi-zone heating control, using a data-driven model for predictive indoor temperature modeling in intelligent buildings taking into account the influence of interconnected adjacent zones. The research methodology uses dynamic thermal simulation, parallel predictive models based on multiple linear regressions, and a multi-objective non-dominated sorting genetic algorithm II (NSGA-II) for the optimization process, which evaluates various generated heating strategies. This research introduces an approach to improve building energy efficiency by considering inter-zone dynamics and reducing heating-related energy consumption compared to a conventional heating strategy. By applying this model predictive control on a simulated case, a reduction in energy consumption due to heating is observed while respecting thermal comfort. This work contributes by implementing a method that independently controls temperatures in different building zones simultaneously while applying distinct constraints to each zone. This approach empowers occupants to manage heating consumption based on their preferences, ensuring personalized comfort. In addition, a comparison was made using a model that did not account for inter-zone interactions. This comparison demonstrates that incorporating these interactions into the predictive model enhances the effectiveness of the model predictive control approach. The multi-zone approach was also validated experimentally by using real experimental data, demonstrating significant reductions in energy consumption.

Segmentation of 3D Point Clouds of Heritage Buildings Using Edge Detection and Supervoxel-Based Topology.

This paper presents a novel segmentation algorithm specially developed for applications in 3D point clouds with high variability and noise, particularly suitable for heritage building 3D data. The method can be categorized within the segmentation procedures based on edge detection. In addition, it uses a graph-based topological structure generated from the supervoxelization of the 3D point clouds, which is used to make the closure of the edge points and to define the different segments. The algorithm provides a valuable tool for generating results that can be used in subsequent classification tasks and broader computer applications dealing with 3D point clouds. One of the characteristics of this segmentation method is that it is unsupervised, which makes it particularly advantageous for heritage applications where labelled data is scarce. It is also easily adaptable to different edge point detection and supervoxelization algorithms. Finally, the results show that the 3D data can be segmented into different architectural elements, which is important for further classification or recognition. Extensive testing on real data from historic buildings demonstrated the effectiveness of the method. The results show superior performance compared to three other segmentation methods, both globally and in the segmentation of planar and curved zones of historic buildings.

Thermal conditions and daylight availability in different zones of courtyard buildings; a study in Iran

ABSTRACT Passive design strategies enhance indoor thermal comfort and reduce energy consumption in buildings located in hot climates. Thus, exploring the various zones of a house’s yard can yield valuable insights for devising a plan that achieves high energy and lighting efficiency. This study examines the climate-responsive design strategies of 20 traditional courtyard buildings in Birjand’s hot and dry climate. These courtyard houses informed modelling a new hypothetical house in DesignBuilder. Two main orientations (45° = NE–SW, and 315° = NW–SE) were used for comparing their impact on indoor air temperature, solar gain and daylight factor across various courtyard zones. The findings indicate that during winter, the interiors of courtyard houses maintain a temperature higher than the exterior, while in summer, they remain cooler than outside conditions. Concerning the influence of orientation on indoor climates, the NE–SW orientation yielded the greatest solar gains for windows in the northern and western zones. Conversely, in the NW–SE orientation, the most substantial solar gains were recorded for windows in the northern and eastern zones. Additionally, the study noted a marginal variation in the daylight factor across different zones of the courtyard houses when comparing the two orientations.

OPTIMIZING ELECTROCHROMIC SMART GLASS WINDOWS PERFORMANCE WITH SOLAR CONTROL FOR SUSTAINABLE OFFICE ENVIRONMENTS IN THE HOT AND HUMID CLIMATE OF SAUDI ARABIA

ABSTRACT Energy-saving strategies are of paramount importance, especially in office buildings located in hot-humid climates. This study explores the potential for energy savings and assesses visual comfort in such environments by introducing Electrochromic (EC) smart glass in the window glazing. To bolster credibility and provide essential information, we employ a state-of-the-art building simulation tool. The research focuses on evaluating the energy performance and visual comfort of EC glass windows when controlled by solar controllers. Through meticulous simulations, we pinpoint the optimal setpoint radiation levels for EC glass windows across all building orientations. The results conclusively indicate that deploying EC glass windows with solar controllers, each set to the recommended radiation levels, leads to remarkable energy savings, up to 20%. Importantly, these savings are achieved without compromising visual comfort in any of the building's zones, regardless of orientation. This research underscores the potential for EC glass windows to significantly improve energy efficiency in office buildings, emphasizing their applicability in hot-humid climates. The findings call for further exploration in different building types and climate zones, as the practical implications of these results could revolutionize energy-efficient building design and retrofits.

Combined Effects of Thermal Buoyancy, Wind Action, and State of the First-Floor Lobby Entrance on the Pressure Difference in a High-Rise Building

The stack effect in high-rise buildings, stemming from an inside/outside temperature difference, may produce a significant pressure difference on the elevator doors, potentially causing elevator malfunctions. This effect can also be influenced by wind action and human behaviors, e.g., opening/closing of building entrances. In this study, a wind tunnel test was conducted to determine the real wind pressure distribution on a high-rise building in northern China. A numerical simulation utilizing the Conjunction of Multizone Infiltration Specialists software (COMIS) was carried out to investigate the pressure difference of elevator doors under the effects of thermal buoyancy, wind action, and opening/closing of the first-floor lobby entrance. An alternative solution of a locally strengthened envelope is proposed and validated for the studied building zone. The study reveals that the opening of the first-floor lobby entrance increases the pressure difference regardless of the environmental conditions, and the increase of wind speed tends to increase the pressure difference in winter but decrease it in summer. The proposed countermeasure combination, involving using revolving doors instead of swing doors, increasing additional partitions, and strengthening the local building envelope, was found to be synergistic and effective in reducing the pressure difference inside the building. The research findings offer practical engineering solutions for mitigating elevator door pressure challenges in high-rise buildings.

Reconfigurable supply-based feedback control for enhanced energy flexibility of air-conditioning systems facilitating grid-interactive buildings

Air-conditioning systems have great potential to provide energy flexibility services to the power grids of high-renewable penetration, due to their high power consumption and inherent energy flexibilities. Direct load control by switching off some operating chillers is the simplest and effective means for air-conditioning systems in buildings to respond to urgent power reduction requests of power grids. However, the implementation of this approach in today's buildings, which widely adopt demand-based feedback controls, would result in serious problems including disordered cooling distribution and likely extra energy consumption. This study, therefore, proposes a reconfigurable control strategy to address these problems. This strategy consists of supply-based feedback control, incorporated with the conventional demand-based feedback control, a control loop reconfiguration scheme and a setpoint reset scheme, facilitating effective control under limited cooling supply and smooth transition between supply-based and demand-based feedback control modes. The proposed control strategy is deployed in a commonly-used digital controller to conduct hardware-in-the-loop control tests on an air-conditioning system involving six AHUs. Test results show that the reconfigurable control achieves commendable control performance. Proper chilled water distribution enables even thermal comfort control among the building zones during demand response and rebound periods. Temperature deviation of the building zones is controlled below 0.2 K most of the time. 11.6 % and 27 % of power demand reductions are achieved during demand response and rebound periods respectively, using the proposed reconfigurable control compared with that using conventional controls.

Heuristic model predictive control implementation to activate energy flexibility in a fully electric school building

This paper presents a heuristic model predictive control (MPC) methodology to activate energy flexibility in fully electric school buildings in cold climates to reduce electricity demand during peak demand periods of the electric grid. To streamline the implementation of MPC, the proposed approach employs grey-box archetypes, a clustering of weather conditions to identify typical scenarios and a limited number of possible setpoint profiles. A data-driven grey-box approach is used to create archetype models for different thermal zones in a typical school building; this approach enables rapid development and requires much less calibration data than black-box models. A third-order resistance-capacitance thermal network for zones with convective heating and a fourth-order model for zones with radiant floor heating are developed and calibrated using measured data from an all-electric school building in Québec, Canada. The weather data are clustered into several categories, representing different weather conditions (6 clusters representing two ambient temperature ranges and three solar radiation ranges). The heuristic MPC strategy uses predefined optimal setpoint profiles for each cluster and weather prediction one day ahead to shift the building load from on-peak to off-peak hours. For each heuristic MPC scenario, the model runs a simulation using forecast weather data to quantify and activate energy flexibility in response to grid requirements. The developed MPC framework was implemented in the school used as the case study. Ten classrooms are investigated, with six using the MPC and four as a reference case with the reactive control system and default zone setpoint profiles. Results indicate that the school building can provide between 47% and 95% energy flexibility (load shifting relative to reference) during on-peak hours and up to 44% electricity cost reduction while satisfying acceptable temperature constraints. By implementing the proposed MPC, energy flexibility of 32 W/m2 of floor area for the zones with a convective heating system and 65 W/m2 of floor area for the zones with radiant heating can be achieved during a demand response event. The proposed strategy can be generalized and replicated in other school buildings.

Evaluation of using hardening soil model for predicting wall deflections caused by deep excavation: A case study at the Ho Chi Minh metro line 1, Vietnam

The goal of this study is to assess the application of the Hardening soil model in predicting the deformation of retaining walls of excavations in 2D and 3D finite element analysis at the Ho Chi Minh Metro project. Designed as the deepest underground station in the first metro line built in Ho Chi Minh City (HCMC), Opera House station is located in an area with a dense building zone and close to historical buildings. A summary of the input soil properties is provided using data from site investigations, in-situ tests, and laboratory tests. By numerical simulation using the Hardening soil model, the parameters of the soil stiffness modulus value are verified based on the Standard Penetration Test (SPT), and Pressuremeter test (PMT). The obtained results of the numerical analysis by 2D and 3D finite element methods, and field observations indicate that applying the Hardening soil model with soil stiffness modulus obtained in situ tests gives reasonable results on the displacement of the retaining wall at the final phase. The relationship between the SPT value and the stiffness modulus of HCMC sand is a function of depth. This correlation is obtained through the comparison of wall deformation between the simulation and monitoring at the construction site. The results of the difference between 2D and 3D finite element analysis also are discussed in this study.

Analysis and prediction of ground deformation in Yinxi Industrial Park based on time-series InSAR technology.

Monitoring ground deformation in industrial parks is of great importance for the economic development of urban areas. However, limited research has been conducted on the deformation mechanism in industrial parks, and there is a lack of integrated monitoring and prediction models. Therefore, this study proposes a comprehensive monitoring and prediction model for industrial parks, utilizing time-series Interferometry Synthetic Aperture Radar (InSAR) technology and the Whale Optimization Algorithm-Back Propagation (WOA-BP) neural network algorithm. Taking Yinxi Industrial Park in Baiyin District as a case study, we used 68 scenes of Sentinel-1A ascending and descending orbit data from June 2018 to April 2021. The Stanford Method for Persistent Scatterers-Permanent Scatterers (StaMPS-PS) and the Small Baseline Subsets-Interferometry Synthetic Aperture Radar (SBAS-InSAR) technologies were employed to obtain the surface deformation information of the park. The deformation information obtained by the two technologies was cross-validated in terms of temporal and spatial distribution, and the vertical and east-west deformation of the park was obtained by combining the ascending and descending orbit data. The results show that the deformation feature points in the line of sight (LOS) direction obtained by the two technologies have a high consistency in spatial distribution, using the ascending orbit data as an example. Additionally, the SBAS-InSAR technology was used to obtain the east-west and vertical deformation results of the park after merging the ascending and descending orbit data for the same period. It was found that the park is mainly affected by vertical deformation, with a maximum subsidence rate of 14.67mm/yr. The subsidence areas correspond to the deformation positions observed in field survey photos. Based on the ascending orbit deformation data, the two technologies were validated with 585 points of the same latitude and longitude, and the coefficient of determination R2 was found to be 0.82, with a root mean square error (RMSE) of 2.20mm/a. The deformation rates were also highly consistent. Due to the 47% increase in the number of sampling points provided by the StaMPS-PS technique compared to the SBAS-InSAR technique, the former was found to be more applicable in the industrial park. Based on the ground deformation mechanism in the park, we combined the StaMPS-PS technique with the WOA-BP neural network to construct a deformation zone prediction model. We conducted predictive studies on the deformation zones of buildings and roads within the park, and the results showed that the WOA-optimized BP neural network achieved higher accuracy and lower overall error compared to the unoptimized network. Finally, we analyzed and discussed the geological conditions and inducing factors of ground deformation in the park, providing a reference for a better understanding of the deformation mechanism and early warning of disasters in the industrial park.

Experimental study of buoyancy-driven ventilation with a single opening between two adjacent building zones

In adjacent building zones connected by a single opening, a thermal plume produces a buoyant layer accumulating in the upper space of the experimental zone. The pressure difference between inside and outside the chamber will lead to air flowing in from outside and buoyant fluid flowing out from inside. This study aims to examine the effect of the vertical opening combination on flow regimes in adjacent building zones. The findings indicate that there may be three different flow regimes depending on the relative positions of the opening in the shared wall and the neutral level. The steady flow in two regimes with double stratification formed in the two zones is modeled separately and the theoretical prediction is compared with the experimental results. The flow regime of natural ventilation in the adjacent zones is only related to the height of the outlet, heat source height and effective opening area of the ventilation zones, but not to the buoyancy flux. The interface changes linearly with the height of the heat source at first until the nozzle is immersed in the buoyancy layer, and then the interface height remains constant. The relative size of the openings will also affect the volume flow rate through them, and keeping the areas of the openings along the flow passage equal will maximize the ventilation rate. These research results can provide layout guidelines for building doors and windows and will help designer improve the natural ventilation effect of adjacent building zones.

Examination of Wind Impacts on RCC Frame Structures in Different Wind Zones

Reinforced refers to a structurally sound assemblage of carefully joined slabs, beams, columns, and foundation components. Through the use of this complex network, loads are systematically transferred from slabs to beams, then to columns, converge at the foundation, and finally travel to the soil beneath. This structural analysis offers a thorough investigation of load-carrying dynamics by examining multiple scenarios for the same structure while accounting for varying wind speeds. A G+9 storey building is subjected to a comparative evaluation in three different wind zones (I, II, and III) with corresponding wind speeds of 33 m/s, 39 m/s, and 44 m/s. The structural behaviour is carefully modelled and examined under the impact of dead load, live load, and wind load using sophisticated STAAD Pro software. This thorough analysis clarifies the structure’s unique reactions to different wind speeds. In order to determine the design loads of a multistorey building, this paper gives a comparative assessment of wind load. Then, using the fundamental wind speed and other local characteristics, the wind load in that zone may also be calculated. The wind speed is time-dependent and random, though. The current study uses the IS 875 code to analyse wind loads in different zones of a multistorey building. The design wind speed of that zone, with a variance, is used to estimate the wind loads.

Dynamic Impact of Urban Built Environment on Land Surface Temperature Considering Spatio-Temporal Heterogeneity: A Perspective of Local Climate Zone

Thermal environment deterioration has seriously threatened urban habitat quality and urban sustainable development. The evolution of the urban built environment (UBE) is an important cause for urban thermal environment variation. However, the dynamic effect of the UBE on the land surface temperature (LST) is rarely studied by combining the local climate zone (LCZ) theory and spatio-temporal heterogeneity. Based on a case study of Beilin District in Xi’an, China, this paper identified LCZ types of Beilin District in 2010, 2015, and 2020 using the GIS method. It also analyzed the spatial–temporal characteristics of the LST in summer based on the remote sensing retrieval method and explored the effects of the built environment on the LST by Geodetector and geographically weighted regression (GWR). The results showed the following: (1) The area share of dense building zones in Beilin District was greater than that of open building zones and natural surface zones, while the share of mid- and high-rise dense building zones continued to increase and the share of low-rise dense building zones continued to decrease during the study period. (2) The LST of different LCZ types in Beilin District was obviously different, and the LST of dense building zones was generally higher than that of open building zones and natural surface zones. Meanwhile, the LST of mid- and low-rise dense building zones increased gradually, and the LST of high-rise open building zones decreased gradually, but the overall warming area was obviously more than the cooling area. (3) The effects of the UBE factors on the LST varied greatly, with their interaction having an enhancement effect. The direct and interactive influence of the two-dimensional (2D) UBE indicators on the LST were greater than those of the three-dimensional (3D) indicators, but there was a gradual decrease in the force of the 2D indicators and a simultaneous diminution, enhancement, and invariance of the force of the 3D indicators. (4) Vegetation cover (VC) and floor area ratio (FAR) acted negatively, and the building height (BH) was changing from a positive to a negative role, with the average action intensity of VC changing from −0.27 to −0.15, FAR from −0.20 to −0.16, and BH from 0.05 to −0.04. The impervious surface area (ISA), building area (BA), and space congestion (SC) acted positively, with the average action intensity of the ISA changing from 0.12 to 0.20, BA from 0.12 to 0.19, and SC was stable at 0.04. The framework enables a deeper portrayal of LST changes in different LCZs, reflecting the direct and interactive effects of different UBE indicators on LST, as well as local variations in the impact effects and provides a basis for urban managers or planners to improve urban heat resilience.

Transient Computational Fluid Dynamics Analysis of Passive Cooling in a Building with Diurnal Radiative Cooling Material Coated onto Its Rooftop

Building cooling loads, which continue to increase with increasing global temperatures, are responsible for large quantities of greenhouse gas emissions. Radiative cooling (RC), whereby structures are cooled by emitting radiation in the atmospheric window, from 8–13 μm, to outer space, is a promising clean technology that can be used to meet ever‐increasing building cooling demands. However, the effects of using RC on the airflow velocity and temperature distributions within the occupied zone of buildings are yet to be investigated. Herein, computational fluid dynamics simulations are performed to study the transient airflow velocity and temperature distributions in buildings that are cooled using RC material on their rooftops. For idealized conditions when the thermal mass of the house is neglected, the results show that when the cooling power provided by the RC material is , and the average temperature of the occupied zone in the building is reduced from 295 K to about 293 and 289.7 K after two minutes, respectively. These rapid cooling rates were attained without exceeding head‐to‐ankle temperature differences of about 2.7 °C and with air flow velocities maintained below 19.0 cm s−1, which is consistent with a comfortable environment.

Simulation of a Building with Hourly and Daily Varying Ventilation Flow: An Application of the Simulink S-Function

This paper presents an application of the Simulink stvmgain S-function for the thermal modelling of a building zone based on the resistance–capacitance scheme of EN ISO 13790. That model in the form of the state-space matrix with time-varying elements was used in simulations of a building with hourly and, suggested in that standard, daily averaged ventilation airflow in five European cities. The following two ventilation schedules were used: occupancy-based; and wind-dependent. Comparative simulations were conducted in EnergyPlus. In general, the results obtained for the annual heating and cooling demand were better for hourly than daily averaged ventilation with an error below 10%. However, in several cases of cooling, the error was above 30%. When considering hourly indoor air temperatures, the proposed method provided very good results with MAE of up to 0.52 °C and 0.46 °C, RMSE < 0.69 °C and 0.62 °C, and CV(RMSE) < 3.09% and 2.75% for the daily averaged and hourly ventilation flow, respectively. For wind-driven ventilation, the temperatures were as follows: MAE < 0.49 °C and 0.48 °C; RMSE < 0.69 °C and 0.68 °C; and CV(RMSE) < 3.01% and 2.97%.

Thermal performance study of buildings and their corresponding scale models with identical constructions and geometrical similarity

Small-scale physical model testing can be applied to calibrate a computational building energy model based on the acquired reliable thermal performance data. The calibration approach using a small-scale physical model is a rigorous and cost effective means in order to do an accurate full-scale building energy simulation. It is meaningful to reveal the correlation of the thermal performance between a full-scale building and its scale model, so that the data from a small-scale model testing can be scalable to predict the performance of a full-scale building. The purpose of the research is to investigate the correlations reflecting the comparative thermal performance of a full-scale building against its scale model with identical constructions and geometrical similarity. More than ninety thousand scenarios about the typical target building zones and their corresponding scale models were generated via the parametric energy modeling and simulation approach. Then, the typical thermal performance indicator of each building zone, i.e. the zone mean air temperature (ZMAT), was obtained. The result shows that the zone mean air temperature difference between the target building and its scale model is a time dependent variable with the diurnal cycle. Compared with a fixed scale model, the bigger building causes the larger variation of zone mean air temperature difference. Furthermore, it also indicates that the zone mean air temperature difference can be approximated by a logarithmic regression function as ALn(SF/d)+B, where A and B are empirical coefficients associated with climate, building form, material and construction, as well as window-to-wall ratio. In engineering practice, the outcomes of the research are applicable for thermal performance estimation and energy model calibration of full-scale buildings, especially for a planned building with the available material and construction samples, but without the determined or reliable thermal performance data for the building.