Advances in Building Simulation

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Air air	-	-	2023	15.0 days *	CHF 1000
Applied Sciences applsci	2.5	5.3	2011	17.8 Days	CHF 2400
Buildings buildings	3.1	3.4	2011	17.2 Days	CHF 2600
Energies energies	3.0	6.2	2008	17.5 Days	CHF 2600
Modelling modelling	1.3	2.7	2020	21.2 Days	CHF 1000
Solar solar	-	-	2021	27.4 Days	CHF 1000
Fluids fluids	1.8	3.4	2016	22.1 Days	CHF 1800

27 pages, 3884 KiB

Open AccessArticle

Optimizing the View Percentage, Daylight Autonomy, Sunlight Exposure, and Energy Use: Data-Driven-Based Approach for Maximum Space Utilization in Residential Building Stock in Hot Climates

by Tarek M. Kamel, Amany Khalil, Mohammed M. Lakousha, Randa Khalil and Mohamed Hamdy

Energies 2024, 17(3), 684; https://doi.org/10.3390/en17030684 - 31 Jan 2024

Cited by 7 | Viewed by 2457

Abstract

This paper introduces a comprehensive methodology for creating diverse layout generation configurations, aiming to address limitations in existing building optimization studies that rely on simplistic hypothetical buildings. This study’s objective was to achieve an optimal balance between minimizing the energy use intensity (EUI) [...] Read more.

This paper introduces a comprehensive methodology for creating diverse layout generation configurations, aiming to address limitations in existing building optimization studies that rely on simplistic hypothetical buildings. This study’s objective was to achieve an optimal balance between minimizing the energy use intensity (EUI) in kWh/m², maximizing the views percentages to the outdoor (VPO), achieving spatial daylight autonomy (sDA), and minimizing annual sunlight exposure (ASE). To ensure the accuracy and reliability of the simulation, the research included calibration and validation processes using the Ladybug and Honeybee plugins, integrated into the Grasshopper platform. These processes involved comparing the model’s performance against an existing real-world case. Through more than 1500 iterations, the study extracted three multi-regression equations that enabled the calculation of EUI in kWh/m². These equations demonstrated the significant influence of the window-to-wall ratio (WWR) and space proportions (SP) on the EUI. By utilizing these multi-regression equations, we were able to fine-tune the design process, pinpoint the optimal configurations, and make informed decisions to minimize energy consumption and enhance the sustainability of residential buildings in hot arid climates. The findings indicated that 61% of the variability in energy consumption can be attributed to changes in the WWR, as highlighted in the first equation. Meanwhile, the second equation suggested that around 27% of the variability in energy consumption can be explained by alterations in space proportions, indicating a moderate correlation. Lastly, the third equation indicated that approximately 89% of the variability in energy consumption was associated with changes in the SP and WWR, pointing to a strong correlation between SP, WWR, and energy consumption. The proposed method is flexible to include new objectives and variables in future applications. Full article

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17 pages, 2652 KiB

Open AccessArticle

Advancing Fault Detection in Building Automation Systems through Deep Learning

by Woo-Hyun Choi and Jung-Ho Lewe

Buildings 2024, 14(1), 271; https://doi.org/10.3390/buildings14010271 - 19 Jan 2024

Viewed by 1719

Abstract

This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine learning algorithms and outlier detection techniques, this model is capable [...] Read more.

This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine learning algorithms and outlier detection techniques, this model is capable of monitoring and learning anomaly patterns in real-time. The primary aim of this paper is to enhance the reliability and efficiency of buildings and industrial facilities, offering solutions applicable across diverse industries such as manufacturing, energy management, and smart grids. Our findings reveal that the developed algorithm detects mechanical faults and security vulnerabilities with an accuracy of 96%, indicating its potential to significantly improve the safety and efficiency of building automation systems. However, the full validation of the algorithm’s performance in various conditions and environments remains a challenge, and future research will explore methodologies to address these issues and further enhance performance. This research is expected to play a vital role in numerous fields, including productivity improvement, data security, and the prevention of human casualties. Full article

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45 pages, 4684 KiB

Open AccessReview

From White to Black-Box Models: A Review of Simulation Tools for Building Energy Management and Their Application in Consulting Practices

by Amir Shahcheraghian, Hatef Madani and Adrian Ilinca

Energies 2024, 17(2), 376; https://doi.org/10.3390/en17020376 - 12 Jan 2024

Cited by 4 | Viewed by 2769

Abstract

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings [...] Read more.

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings and their energy systems, and they are widely used in building energy management. These simulation tools can be categorized into white-box and black-box models based on the level of detail and transparency of the model’s inputs and outputs. This review publication comprehensively analyzes the white-box, black-box, and web tool models for building energy simulation tools. We also examine the different simulation scales, ranging from single-family homes to districts and cities, and the various modelling approaches, such as steady-state, quasi-steady-state, and dynamic. This review aims to pinpoint the advantages and drawbacks of various simulation tools, offering guidance for upcoming research in the field of building energy management. We aim to help researchers, building designers, and engineers better understand the available simulation tools and make informed decisions when selecting and using them. Full article

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20 pages, 4825 KiB

Open AccessArticle

Analysis of Pedestrian Behavior for the Optimization of Evacuation Plans in Tall Buildings: Case Study Santiago, Chile

by Rodrigo Ternero, Juan Sepúlveda, Miguel Alfaro, Guillermo Fuertes, Manuel Vargas, Juan Pedro Sepúlveda-Rojas and Lukas Soto-Jancidakis

Buildings 2023, 13(12), 2907; https://doi.org/10.3390/buildings13122907 - 22 Nov 2023

Cited by 5 | Viewed by 1855

Abstract

Countries located in the Pacific Ring of Fire, such as Chile, require robust evacuation plans for tall buildings to manage the ongoing threat of natural disasters. This study presents a methodology for developing evacuation plans by conducting pedestrian movement simulations with agents that [...] Read more.

Countries located in the Pacific Ring of Fire, such as Chile, require robust evacuation plans for tall buildings to manage the ongoing threat of natural disasters. This study presents a methodology for developing evacuation plans by conducting pedestrian movement simulations with agents that have a model of their surroundings. This approach allows us to assess different scenarios and choose the best option based on the specific characteristics of the site. The method combines simulation and data analysis, using the Monte Carlo method to improve emergency evacuations. Initially, Pathfinder software was employed to simulate the evacuation of a tall building. This involved modeling pedestrian movements using a multiagent system. These agents were programmed to behave like real pedestrians and make decisions during evacuation scenarios, providing valuable information. The effectiveness of two evacuation strategies was then evaluated using the simulation data. The proposed methodology was validated using a case study. The simulations showed that the best strategy depends on factors such as the distribution of people, the capacity of the exits, and the time available for evacuation. Finally, the model includes a training process that uses virtual reality technology to improve situational awareness. Full article

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16 pages, 4501 KiB

Open AccessArticle

Research on Representative Volume Element Fex-Cy High-Temperature Mechanical Model Based on Response Surface Analysis

by Shining Lyu, Youshan Gao, Aihong Wang and Yiming Hu

Appl. Sci. 2023, 13(20), 11531; https://doi.org/10.3390/app132011531 - 21 Oct 2023

Viewed by 1027

Abstract

In this research, a multi-scale representative volume element method is introduced that combines the temperature and stress fields to analyze the force field distribution around microcracks in low-carbon steel using a combination of molecular dynamics and finite element analysis. Initially, an orthogonal experimental [...] Read more.

In this research, a multi-scale representative volume element method is introduced that combines the temperature and stress fields to analyze the force field distribution around microcracks in low-carbon steel using a combination of molecular dynamics and finite element analysis. Initially, an orthogonal experimental design was used to design the molecular dynamics simulation experiments. Next, a nano-level uniaxial tensile test model for mild steel was established based on the experimental design, and the uniaxial tensile behavior of low-carbon steel was investigated using molecular dynamics. Lastly, mathematical models of the modulus of elasticity E and yield strength Q of mild steel at a high temperature were obtained statistically using the response surface methodology. Meanwhile, a finite element model with a coupled temperature–stress field was established to investigate the force field distribution around the microscopic defects, and the microscopic crack stress concentration coefficient K was revised. The results indicate that regardless of the location of microcracks within the structure, the stress distribution due to size effects should be considered under high-temperature loading. Full article

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17 pages, 3057 KiB

Open AccessArticle

Simulation Modelling for the Promotion of Green Residence Based on the Theory of Sustainability—Taking Jiangsu Province as an Example

by Hao Xu, Jun Zhang, Xizhen Xu, Zewei Zeng, Yuzhu Xu, Jiawei You and Jing Li

Buildings 2023, 13(10), 2635; https://doi.org/10.3390/buildings13102635 - 19 Oct 2023

Viewed by 1384

Abstract

Green residences have enormous potential for energy savings, emission reduction, and other comprehensive benefits, and their growth is crucial to achieving China’s carbon neutrality and carbon peaking targets. Nevertheless, at the moment, the national green residence is impacted by complicated factors at several [...] Read more.

Green residences have enormous potential for energy savings, emission reduction, and other comprehensive benefits, and their growth is crucial to achieving China’s carbon neutrality and carbon peaking targets. Nevertheless, at the moment, the national green residence is impacted by complicated factors at several levels, including government agencies, green residence builders, and green residence consumers, which results in the low-quality development of domestic green residences overall. As of 2020, 94% of all labeled green residences are design-label residences that can only be achieved during the design stage, while less than 10% are operational-label residences with stronger energy and emission-saving benefits. This causes the phenomenon of “green residences on the planning” to be serious. In order to accomplish the promotion of high-quality development of green residences and to promote green residences in China, this paper analyzes the influencing factors of green residence promotion from the multi-level perspective of macro-landscape signals, meso-collective agent green residences, and micro-individual agent consumers, based on the multi-level perspective (MLP) framework of sustainability theory. The paper subsequently builds a simulation model of green residence promotion using the agent-based system dynamics modeling method. Additionally, Jiangsu Province’s green residence promotion data are chosen for analogue simulation experiments, and the simulation results are also used to analyze the success conditions as well as the path to green residence promotion. This study demonstrates that (1) the agent-based simulation model of dynamics for the green residence promotion system has high reference value for the simulation of the promotion of green residences, and the model can clearly simulate the impact of micro-individual agent–consumer factors on the promotion of green residences; (2) in order to promote green residences, exterior landscape signals must be continuously improved; the stronger the landscape signals, the quicker the development of operationally labeled green residences; (3) priority is given to the development of two-star design-labeled green residences before 2035, and three-star operationally labeled residences will occupy the majority of the market after 2040. Meanwhile, the duration of landscape signals and the change in behavioral preferences of individual agents must be maintained for a long time. Full article

(This article belongs to the Topic Advances in Building Simulation)

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13 pages, 2876 KiB

Open AccessArticle

Simulation-Based Model-Updating Method for Linear Dynamic Structural Systems

by Özge Şahin and Naci Caglar

Appl. Sci. 2023, 13(18), 10494; https://doi.org/10.3390/app131810494 - 20 Sep 2023

Viewed by 1254

Abstract

The dynamic characteristics of buildings and their behavior under various dynamic loads play a crucial role in civil engineering applications, particularly for earthquake-resistant structural design. Employing a precise mathematical model of the structural system makes it possible to accurately predict the actual structural [...] Read more.

The dynamic characteristics of buildings and their behavior under various dynamic loads play a crucial role in civil engineering applications, particularly for earthquake-resistant structural design. Employing a precise mathematical model of the structural system makes it possible to accurately predict the actual structural performance under dynamic loads, such as winds and earthquakes. Given this perspective, finite element model-updating approaches in structural systems have gained significant attention in recent decades. This paper proposes a simulation-based model-updating technique that utilizes measured free vibration responses to the correct structural parameters of multi-degree-of-freedom systems. A five-degree-of-freedom building model is subjected to shaking table tests to demonstrate the effectiveness of the proposed method. The experimental data for this method consists of the dynamic behavior of the system under the seismic excitation of the El Centro 1940 earthquake and the results of the free vibration tests. The MATLAB/Simulink parameter estimation tool is employed to establish a correlation between the analytical model and the measured dynamic response from the building model. Compared to the measured structural responses, the updated analytical model, which incorporates the proposed simulation-based model-updating technique, demonstrates high accuracy in predicting the responses through effective corrections of stiffness and damping coefficients. Full article

(This article belongs to the Topic Advances in Building Simulation)

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16 pages, 15912 KiB

Open AccessArticle

A Methodology to Improve Energy Efficiency and Sustainability in Urban Environments

by Martina Giorio and Rossana Paparella

Appl. Sci. 2023, 13(17), 9745; https://doi.org/10.3390/app13179745 - 29 Aug 2023

Viewed by 1460

Abstract

This paper presents a methodology to improve energy efficiency and sustainability in urban environments. The ongoing climate change is causing increasingly important consequences for cities and their inhabitants. Temperatures are rising and human thermal comfort conditions are becoming worse. For this reason, it [...] Read more.

This paper presents a methodology to improve energy efficiency and sustainability in urban environments. The ongoing climate change is causing increasingly important consequences for cities and their inhabitants. Temperatures are rising and human thermal comfort conditions are becoming worse. For this reason, it is essential to evaluate how parts of cities react to these phenomena and how they could improve their behavior. To do this, the area of interest has to be analyzed from various aspects, starting with an assessment of the microclimatic conditions. Through these analyses, it is possible to observe the interactions between climate and the urban context on a macro-scale. The actual results, such as surface temperature and air temperature, will be useful for hypothesizing where different paved surfaces need to be restored with mitigative actions. Another aspect that needs to be considered for a comprehensive analysis of the area’s potential concerns the study of solar potential. We will describe how this topic was approached, making in-depth evaluations of the quality of the results obtained through the analysis of simplified models. The portability of these data within a spatial domain was also evaluated, integrating the values on a territorial database. Another important topic that needs to be analyzed to plan an improvement of an area in terms of energy production is the installation of new solar active production systems. The appropriate inclusion of photovoltaic panels could lead to the near self-sustainability of buildings by decreasing the external energy demand. The results obtained by applying the methodology in a case study highlight that all these aspects must be taken into account simultaneously to improve the existing conditions of entire city areas, leading to a more sustainable urban environment. Full article

(This article belongs to the Topic Advances in Building Simulation)

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22 pages, 4089 KiB

Open AccessArticle

Predicting the Energy Consumption of Commercial Buildings Based on Deep Forest Model and Its Interpretability

by Guangfa Zheng, Zao Feng, Mingkai Jiang, Li Tan and Zhenglang Wang

Buildings 2023, 13(9), 2162; https://doi.org/10.3390/buildings13092162 - 25 Aug 2023

Cited by 1 | Viewed by 2216

Abstract

Building energy assessment models are considered to be one of the most informative methods in building energy efficiency design, and most of the current building energy assessment models have been developed based on machine learning algorithms. Deep learning models have proved their effectiveness [...] Read more.

Building energy assessment models are considered to be one of the most informative methods in building energy efficiency design, and most of the current building energy assessment models have been developed based on machine learning algorithms. Deep learning models have proved their effectiveness in fields such as image and fault detection. This paper proposes a deep learning energy assessment framework with interpretability to support building energy efficiency design. The proposed framework is validated using the Commercial Building Energy Consumption Survey dataset, and the results show that the wrapper feature selection method (Sequential Forward Generation) significantly improves the performance of deep learning and machine learning models compared with the filtered (Mutual Information) and embedded (Least Absolute Shrinkage and Selection Operator) feature selection algorithms. Moreover, the Deep Forest model has an R² of 0.90 and outperforms the Deep Multilayer Perceptron, the Convolutional Neural Network, the Backpropagation Neural Network, and the Radial Basis Function Network in terms of prediction performance. In addition, the model interpretability results reveal how the features affect the prediction results and the contribution of the features to the energy consumption in a single building sample. This study helps building energy designers assess the energy consumption of new buildings and develop improvement measures. Full article

(This article belongs to the Topic Advances in Building Simulation)

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23 pages, 6679 KiB

Open AccessFeature PaperArticle

Predicting Building Energy Demand and Retrofit Potentials Using New Climatic Stress Indices and Curves

by Rosa Francesca De Masi, Gerardo Maria Mauro, Silvia Ruggiero and Francesca Villano

Energies 2023, 16(16), 5861; https://doi.org/10.3390/en16165861 - 8 Aug 2023

Viewed by 898

Abstract

Building energy requalification in Italy and Europe has been much discussed in recent years due to the high percentage of existing buildings with poor energy performance. In this context, it is useful to obtain a user-friendly and fast tool to predict the thermal [...] Read more.

Building energy requalification in Italy and Europe has been much discussed in recent years due to the high percentage of existing buildings with poor energy performance. In this context, it is useful to obtain a user-friendly and fast tool to predict the thermal energy demand (TED) for space conditioning and the related primary energy consumption (PEC) as a function of climatic stress. In this study, the SLABE methodology (simulation-based large-scale uncertainty/sensitivity analysis of building energy performance) is used to simulate representative Italian buildings, varying parameters such as geometry, envelope and HVAC (heating, ventilating and space conditioning) systems. MATLAB^® in combination with EnergyPlus is used to analyze 200 buildings belonging to two structural types (multi-family buildings and apartment blocks) built in 1961–1975. Nine scenarios (as-built scenarios and eight retrofit ones) are investigated in 63 climatic locations. A regression analysis shows that the classical HDDs (heating degree days) approach cannot give an accurate prediction of TED because solar radiation is not accounted for. Thus, new climatic indices are developed alongside solar radiation, including the heating stress index (HSI), the cooling stress index (CSI) and the yearly climatic stress index (YCSI). The purpose of our work is to obtain climatic stress curves for the prediction of TED and PEC. Testing of this novel approach is performed by comparison with another building energy simulation tool, showing a low discrepancy, i.e., the coefficient of variation of the root mean square error is between 12% and 28%, which confirms certain reliability of the approach here proposed. Full article

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21 pages, 5614 KiB

Open AccessReview

Review of the Interfacial Bonding Properties between Ultrahigh-Performance Concrete and Normal Concrete

by Liying Xu, Yong Yao, Yuxiang Li, Jiazhan Su and Yingxiong Wu

Appl. Sci. 2023, 13(11), 6697; https://doi.org/10.3390/app13116697 - 31 May 2023

Cited by 6 | Viewed by 2513

Abstract

As a high-quality building material exhibiting excellent toughness and durability, ultrahigh-performance concrete (UHPC) is increasingly being used in the construction industry and as building reinforcement. During the reinforcement of existing concrete structures with UHPC, their interface is the weakest part of a structure. [...] Read more.

As a high-quality building material exhibiting excellent toughness and durability, ultrahigh-performance concrete (UHPC) is increasingly being used in the construction industry and as building reinforcement. During the reinforcement of existing concrete structures with UHPC, their interface is the weakest part of a structure. Interface bonding ensures the operation of two types of materials together. However, existing studies rarely report the bonding of the UHPC–normal concrete (NC) interface. Herein, the existing test methods and interface bonding mechanisms are summarized. Subsequently, the differences among relevant design codes are investigated by comparing different theoretical formulas. Important influencing factors of the reinforcement method, namely, interface roughness, fiber type and content, interface agent type and content, moisture content, existing concrete strength, cementitious material content, curing conditions, freeze–thaw cycles, and chloride ions, are also considered. Further, the enhancement mechanism of the characteristics of the UHPC–NC interface is clearly described. Finally, the shortcomings and application prospects of the interfacial bonding properties are highlighted. Full article

(This article belongs to the Topic Advances in Building Simulation)

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29 pages, 12112 KiB

Open AccessArticle

Research on Air-Conditioning Cooling Load Correction and Its Application Based on Clustering and LSTM Algorithm

by Honglian Li, Li Shang, Chengwang Li and Jiaxiang Lei

Appl. Sci. 2023, 13(8), 5151; https://doi.org/10.3390/app13085151 - 20 Apr 2023

Cited by 1 | Viewed by 1914

Abstract

Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai [...] Read more.

Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai and the corresponding average heat island intensity data were analyzed. Using the CRITIC objective weighting method and K-means clustering analysis, the hourly change coefficient, β, of dry bulb temperature was calculated, and the LSTM algorithm was used to predict the changing trends in β. Finally, the air conditioning load model for a hospital was established using DeST (version DeST3.0 1.0.2107.14 20220712) software, and the air conditioning cooling load in summer was calculated and predicted. The results show that, compared with the original design days, regional differences in the new design days are more obvious, the maximum temperature and time have changed, and the design days parameters are more consistent with the local meteorological conditions. Design day temperatures in Shanghai are expected to continue rising for some time to come, while those in Beijing are expected to gradually return to previous levels. Among hospital buildings, the cooling load of outpatient buildings in Beijing and Shanghai will decrease by 0.69% and increase by 12.61% and by 12.12% and 15.51%, respectively, under the influence of the heat island effect. It is predicted to decrease by 1.35% and increase by 29.75%, respectively, in future. The cooling load of inpatient buildings in Beijing and Shanghai increased by 0.27% and 6.71%, respectively, and increased by 7.13% and 8.09%, respectively, under the influence of the heat island effect, and is predicted to decrease by 0.93% and increase by 16.07%, respectively, in future. Full article

(This article belongs to the Topic Advances in Building Simulation)

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17 pages, 2369 KiB

Open AccessArticle

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

by Jun L. Mata, Jerson N. Orejudos, Joel G. Opon and Sherwin A. Guirnaldo

Buildings 2023, 13(1), 107; https://doi.org/10.3390/buildings13010107 - 31 Dec 2022

Cited by 4 | Viewed by 7179

Abstract

In the event of a typhoon, the majority of houses suffer from large amounts of damage because they were not built with typhoon resilience in mind. For instance, the Philippines is one of the world’s most vulnerable countries to typhoons. Often, roof structures [...] Read more.

In the event of a typhoon, the majority of houses suffer from large amounts of damage because they were not built with typhoon resilience in mind. For instance, the Philippines is one of the world’s most vulnerable countries to typhoons. Often, roof structures are ripped off during typhoons with average or more vigorous wind gustiness, and houses are easily ruined. This situation led us to search for the appropriate building orientation and roof angle of single-family residential houses through simulations using MATLAB’s genetic algorithm (GA) and SolidWorks’ computational fluid dynamics (CFD). The GA provides the set of design points, while CFD generates a fitness score for each design point. The goal of the optimization is to determine the orientation and roof angle while minimizing the drag force along the direction of a constant wind speed (315 km/h). The lower and upper bounds for house orientation are 0

^{\circ}

and 90

^{\circ}

, respectively; the roof angle is between 3

^{\circ}

and 60

^{\circ}

. After 100 generations, the GA converged to values equal to an 80

^{\circ}

orientation and 11

^{\circ}

roof angle. The final results provide a good standpoint for future experiments on physical structures. Full article

(This article belongs to the Topic Advances in Building Simulation)

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15 pages, 3665 KiB

Open AccessArticle

Dynamic Heat Transfer Calculation for Ground-Coupled Floor in Emergency Temporary Housing

by Pei Ding, Jin Li, Mingli Xiang, Zhu Cheng and Enshen Long

Appl. Sci. 2022, 12(22), 11844; https://doi.org/10.3390/app122211844 - 21 Nov 2022

Cited by 5 | Viewed by 1682

Abstract

Generally, ground-coupled floor heat transfer is supposed as annual periodic, which is reasonable for conventional buildings. However, for emergency housing with a short life cycle, the influence of initial soil temperature needs to be considered. In a previous study, the Wiener–Hopf technique was [...] Read more.

Generally, ground-coupled floor heat transfer is supposed as annual periodic, which is reasonable for conventional buildings. However, for emergency housing with a short life cycle, the influence of initial soil temperature needs to be considered. In a previous study, the Wiener–Hopf technique was introduced to solve the two-dimensional transient heat transfer equation with mixed Dirichlet and Robin boundary conditions. Based on that, an analytical solution of the dynamic heat transfer equation with initial soil temperature conditions was obtained. Since the solution was in the form of a double integral, its numerical evaluation method was also analyzed to improve computational efficiency. The accuracy and efficiency of the solution were validated by the finite volume method. Then, the effects of initial soil temperatures in different seasons, soil heat conductivities, and floor insulation on ground-coupled heat transfer were discussed. Results showed significant temperature differences between the current solution and the annual periodic solutions (long-time solutions), especially in hot and cold climates. Moreover, the larger the thermal capacity of the soil, the bigger temperature differences occurred. Therefore, this study is expected to provide a theoretical foundation for the indoor environment prediction and optimization design of emergency temporary housing. Full article

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