Journal articles: 'Building thermal models'

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Zhu, Jingwei, Olaf Wysocki, Christoph Holst, and Thomas H. Kolbe. "Enriching Thermal Point Clouds of Buildings using Semantic 3D building Models." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W5-2024 (June 27, 2024): 341–48. http://dx.doi.org/10.5194/isprs-annals-x-4-w5-2024-341-2024.

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Abstract. Thermal point clouds integrate thermal radiation and laser point clouds effectively. However, the semantic information for the interpretation of building thermal point clouds can hardly be precisely inferred. Transferring the semantics encapsulated in 3D building models at Level of Detail (LoD)3 has a potential to fill this gap. In this work, we propose a workflow enriching thermal point clouds with the geo-position and semantics of LoD3 building models, which utilizes features of both modalities: model point clouds are generated from LoD3 models, and thermal point clouds are co-registered by coarse-to-fine registration. The proposed method can automatically co-register the point clouds from different sources and enrich the thermal point cloud in facade-detailed semantics. The enriched thermal point cloud supports thermal analysis and can facilitate the development of currently scarce deep learning models operating directly on thermal point clouds.

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Adán, Antonio, Blanca Quintana, Juan García Aguilar, Víctor Pérez, and Francisco Javier Castilla. "Towards the Use of 3D Thermal Models in Constructions." Sustainability 12, no. 20 (October 15, 2020): 8521. http://dx.doi.org/10.3390/su12208521.

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The use of point clouds in architecture and civil engineering has, to date, been limited almost exclusively to functional geometric features. Nevertheless, hardly any works have attempted to process and explore 3D thermal models for buildings. This paper presents a method for the visualisation and exploration of 3D thermal models (3D-T) of building interiors. A 3D-T model consists of a thermal point cloud, which has been generated with a 3D thermal-scanner platform. Given a 3D-T of a building at a specific time, the user can visualise and navigate through different room models and each room can, in turn, be segmented into its architectonic components (walls, ceilings and floors), from which thermal orthoimages can be generated. When the building is sensed at different times, a 3D temporal-thermal (3D-TT) model is integrated. The temporal-thermal evolution of these structural components, along with selected zones of them, can then be analysed by performing a new type of thermal characterisation. This method has successfully been tested using real building-related data.

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Sun, Xuemei, Saihong Zhu, Hengxuan Zhu, Runze Duan, and Jin Wang. "Comparison and analyses of two thermal performance evaluation models for a public building." Open Physics 17, no. 1 (December 31, 2019): 916–26. http://dx.doi.org/10.1515/phys-2019-0089.

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Abstract Recently, investigations on building thermal inertia are mainly involved with the materials of the building envelope. Usually, other influencing factors are ignored, such as room ventilation, indoor heat storage, indoor cold source, indoor heat source and human behavior. In this paper, two models based on thermodynamics are given to evaluate building thermal performance. One is thermal mass model, and the other one is thermal reserve coefficient model. Based on thermal response testing data in a non-heating season, the thermal mass model was adopted to classify the envelope type, and the delay rules between the indoor temperature and the outdoor meteorological parameters are analyzed. In a heating season, the delay rules among the outdoor temperature, indoor temperature and supply water temperature are obtained by changing the supply water temperature. Thermal performance of the targeted building is evaluated with the thermal reserve coefficient model. For the same public building, two evaluation models tend to be consistent. These two evaluation models presented in this paper can be applied for the optimal design of buildings envelope.

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Cîrstolovean, Lucian, and Paraschiva Mizgan. "Validation of Building Energy Modeling Tools for a Residential Building in Brasov Area-Romania." Ovidius University Annals of Constanta - Series Civil Engineering 20, no. 1 (December 1, 2018): 43–50. http://dx.doi.org/10.2478/ouacsce-2018-0004.

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Abstract A building energy model is a simulation tool which calculates the thermal loads and energy use in buildings. Building energy models provide valuable insight into energy use in buildings based on architecture, materials and thermal loads. In addition, building energy models also must account for the effects of the building’s occupants in terms of energy use. In this paper we discuss building energy models and their accuracy in predicting energy use. In particular, we focus on two types of validation methods which have been used to investigate the accuracy of building energy models and on how they account for their effects on occupants. The analyzed building is P + M located in the climatic zone 4, Sânpetru / Braşov. We have carried out a detailed and exemplary energy needs analysis using two methods of analysis.

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Nageler, Peter, Thomas Mach, Richard Heimrath, Hermann Schranzhofer, and Christoph Hochenauer. "Generation Tool for Automated Thermal City Modelling." Applied Mechanics and Materials 887 (January 2019): 292–99. http://dx.doi.org/10.4028/www.scientific.net/amm.887.292.

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Constructing dynamic building models of entire urban districts or cities is a time consuming effort. An automation process is required to shorten the considerable time needed for manual input and to parameterize simulation tools. This paper presents a generation tool for fully automated thermal city modelling that generates dynamic building models with detailed heating systems. The tool is an interface between a PostgreSQL database and the dynamic building energy simulation environment IDA ICE. Tests show that up to 300 automated generated buildings with a simple geometry and 70 buildings each with a heating system can be simulated per CPU.

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Okazawa, Kazuki, Naoya Kaneko, Dafang Zhao, Hiroki Nishikawa, Ittetsu Taniguchi, Francky Catthoor, and Takao Onoye. "Evaluation of Deep Learning-Based Non-Intrusive Thermal Load Monitoring." Energies 17, no. 9 (April 24, 2024): 2012. http://dx.doi.org/10.3390/en17092012.

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Non-Intrusive Load Monitoring (NILM), which provides sufficient load for the energy consumption of an entire building, has become crucial in improving the operation of energy systems. Although NILM can decompose overall energy consumption into individual electrical sub-loads, it struggles to estimate thermal-driven sub-loads such as occupants. Previous studies proposed Non-Intrusive Thermal Load Monitoring (NITLM), which disaggregates the overall thermal load into sub-loads; however, these studies evaluated only a single building. The results change for other buildings due to individual building factors, such as floor area, location, and occupancy patterns; thus, it is necessary to analyze how these factors affect the accuracy of disaggregation for accurate monitoring. In this paper, we conduct a fundamental evaluation of NITLM in various realistic office buildings to accurately disaggregate the overall thermal load into sub-loads, focusing on occupant thermal load. Through experiments, we introduce NITLM with deep learning models and evaluate these models using thermal load datasets. These thermal load datasets are generated by a building energy simulation, and its inputs for the simulation were derived from realistic data like HVAC on/off data. Such fundamental evaluation has not been done before, but insights obtained from the comparison of learning models are necessary and useful for improving learning models. Our experimental results shed light on the deep learning-based NITLM models for building-level efficient energy management systems.

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Haghighat, F., and M. Chandrashekar. "System-Theoretic Models for Building Thermal Analysis." Journal of Solar Energy Engineering 109, no. 2 (May 1, 1987): 79–88. http://dx.doi.org/10.1115/1.3268196.

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A method for computer simulation of thermal analysis and energy consumption in buildings is described. This method is based on the system-theoretic approach which has been used to formulate and solve the set of equations for dynamic thermal analysis of buildings. The technique is well suited for computer formulation and the solution of repetitive structures. The resulting set of equations is sparse and can be solved very efficiently on a computer. The algebraic-differential equations are derived for an example using the system-theoretic approach. A large scale example is also presented.

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Boskic, Ljuboslav, and Igor Mezic. "Control-Oriented, Data-Driven Models of Thermal Dynamics." Energies 14, no. 5 (March 7, 2021): 1453. http://dx.doi.org/10.3390/en14051453.

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We investigate data-driven, simple-to-implement residential environmental models that can serve as the basis for energy saving algorithms in both retrofits and new designs of residential buildings. Despite the nonlinearity of the underlying dynamics, using Koopman operator theory framework in this study we show that a linear second order model embedding, that captures the physics that occur inside a single or multi zone space does well when compared with data simulated using EnergyPlus. This class of models has low complexity. We show that their parameters have physical significance for the large-scale dynamics of a building and are correlated to concepts such as the thermal mass. We investigate consequences of changing the thermal mass on the energy behavior of a building system and provide best practice design suggestions.

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Rasku, Topi, Raimo Simson, and Juha Kiviluoma. "Sensitivity of a Lumped-Capacitance Building Thermal Modelling Approach for Energy-Market-Scale Flexibility Studies." Buildings 14, no. 6 (June 1, 2024): 1614. http://dx.doi.org/10.3390/buildings14061614.

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Despite all the literature on building energy management, building-stock-scale models depicting its impact for energy-market-scale optimisation models are lacking. To address this shortcoming, an open-source tool called ArchetypeBuildingModel.jl has been developed for aggregating building-stock-level data into simplified lumped-capacitance thermal models compatible with existing open-source energy-system modelling frameworks. This paper aims to demonstrate the feasibility of these simplified thermal models by comparing their performance against dedicated building simulation software, as well as examining their sensitivity to key modelling and parameter assumptions. Modelling and parameter assumptions comparable to the existing literature achieved an acceptable performance according to ASHRAE Guideline 14 across all tested buildings and nodal configurations. The most robust performance was achieved with a period of variations above 13 days and interior node depth between 0.1 and 0.2 for structural thermal mass calibrations, and with external shading coefficients between 0.6 and 1.0 and solar heat gain convective fractions between 0.4 and 0.6 for solar heat gain calibrations. Furthermore, three-plus-node lumped-capacitance thermal models are recommended when modelling buildings with structures varying in terms of thermal mass. Nevertheless, the ArchetypeBuildingModel.jl performance was found to be robust against uncertain key parameter assumptions, making it plausible for energy-market-scale applications.

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Boodi, Abhinandana, Karim Beddiar, Yassine Amirat, and Mohamed Benbouzid. "Building Thermal-Network Models: A Comparative Analysis, Recommendations, and Perspectives." Energies 15, no. 4 (February 11, 2022): 1328. http://dx.doi.org/10.3390/en15041328.

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The development of smart buildings, as well as the great need for energy demand reduction, has renewed interest in building energy demand prediction. Intelligent controllers are a solution for optimizing building energy consumption while maintaining indoor comfort. The controller efficiency on the other hand, is mainly determined by the prediction of thermal behavior from building models. Due to the development complexity of the models, these intelligent controllers are not yet implemented on an industrial scale. There are primarily three types of building models studied in the literature: white-box, black-box, and gray-box. The gray-box models are found to be robust, efficient, of low cost computationally, and of moderate modeling complexity. Furthermore, there is no standard model configuration, development method, or operation conditions. These parameters have a significant influence on the model performance accuracy. This motivates the need for this review paper, in which we examined various gray-box models, their configurations, parametric identification techniques, and influential parameters.

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Macher, H., M. Boudhaim, P. Grussenmeyer, M. Siroux, and T. Landes. "COMBINATION OF THERMAL AND GEOMETRIC INFORMATION FOR BIM ENRICHMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (August 23, 2019): 719–25. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-719-2019.

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<p><strong>Abstract.</strong> In the context of building renovation, infrared (IR) cameras are widely used to perform the energy audit of buildings. They allow analysing precisely the energetic performances of existing buildings and thermal analyses represent a key step for the reduction of energy consumption. They are also used to assess the thermal comfort of people living or working in a building. Building Information Models (BIM) are widespread to plan the rehabilitation of existing buildings and laser scanning is now commonly used to capture the geometry of buildings for as-built BIM creation. The combination of thermographic and geometric data presents a high number and variety of applications (Lagüela and Díaz-Vilariño, 2016). However, geometric and thermal information are generally acquired separately by different building stakeholders and thermal analyses are performed with independence of geometry. In this paper, the combination of thermal and geometric information is investigated for indoor of buildings. The aim of the project is to create 3D thermographic point clouds based on data acquired by a laser scanner and a thermal camera. Based on these point clouds, BIM models might be enriched with thermal information through the scan-to-BIM process.</p>

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Mavromatidis, Lazaros. "Constructal Evaluation of Polynomial Meta-Models for Dynamic Thermal Absorptivity Forecasting for Mixed-Mode nZEB Heritage Building Applications." Energies 16, no. 1 (December 30, 2022): 429. http://dx.doi.org/10.3390/en16010429.

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The intelligent and appropriate regulation of indoor temperatures within heritage buildings is crucial for achieving nearly Zero-Energy Building (nZEB) standards, since the technical improvement of the envelope and the overall shape of heritage buildings should be very limited in order to preserve the buildings’ authenticity. Thermal comfort is a very important factor that influences the energy performance of a building and the wellbeing of its end users. The present paper focuses on the development of a dynamic thermal human stress model that aimed to accurately predict the necessary garment insulation within a typical high-inertia heritage building. Two different statistical approaches (a Hoke D6 design and a composite factorial design) were employed for the development of this meta-model adapted to a typical mixed-mode heritage building seeking to obtain nZEB classification. Thermal human stress was modeled through the prediction of the thermal absorptivity (b) in accordance with the updated ASHRAE 55 model. Physically measured indoor climate parameters, outdoor meteorological data, and building operational information were coupled to the subjective sensorial dimensions of the problem with the aim of identifying the necessary garment insulation levels within heritage buildings composed of high-thermal-mass materials (for example, stone, concrete, and ceramic tiles). Our investigation focused on the parameter directly linked to the cold/warm sensations experienced due to clothing insulation: thermal absorptivity (b). In brief, the present paper proposes a third-order regression polynomial model that facilitates the calculation of thermal absorptivity, relying on adaptive thermal comfort concepts. The meta-model was then evaluated using Adrian Bejan’s constructal law after conducting entropy analysis. The constructal evaluation of the meta-model revealed the characteristic size of the domain regarding variable thermal absorptivity (b) and identified the necessary evolution of the model in order to increase its forecasting capacity. Thus, the model provided accurate forecasting for thermal absorptivity values greater than 50 Ws−1/2 m−2K and will be developed further to improve its absolute location accuracy for scenarios wherein the thermal absorptivity value is lower than 50 Ws−1/2 m−2K.

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Martínez Comesaña, Miguel, Lara Febrero-Garrido, Francisco Troncoso-Pastoriza, and Javier Martínez-Torres. "Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks." Applied Sciences 10, no. 21 (October 23, 2020): 7439. http://dx.doi.org/10.3390/app10217439.

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Accurate prediction of building indoor temperatures and thermal demand is of great help to control and optimize the energy performance of a building. However, building thermal inertia and lag lead to complex nonlinear systems is difficult to model. In this context, the application of artificial neural networks (ANNs) in buildings has grown considerably in recent years. The aim of this work is to study the thermal inertia of a building by developing an innovative methodology using multi-layered perceptron (MLP) and long short-term memory (LSTM) neural networks. This approach was applied to a public library building located in the north of Spain. A comparison between the prediction errors according to the number of time lags introduced in the models has been carried out. Moreover, the accuracy of the models was measured using the CV(RMSE) as advised by AHSRAE. The main novelty of this work lies in the analysis of the building inertia, through machine learning algorithms, observing the information provided by the input of time lags in the models. The results of the study prove that the best models are those that consider the thermal lag. Errors below 15% for thermal demand and below 2% for indoor temperatures were achieved with the proposed methodology.

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Lim, Hong Soo, and Gon Kim. "Development of Regression Models considering Time-Lag and Aerosols for Predicting Heating Loads in Buildings." Advances in Civil Engineering 2018 (2018): 1–19. http://dx.doi.org/10.1155/2018/4878021.

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Building automation systems is becoming more vital, especially in regard to reduced building energy consumption. However, the accuracy of such systems in calculating building thermal loads is limited as they are unable to predict future thermal loads based on prevailing environmental factors. The current paper therefore seeks to improve the understanding of the interactions between outdoor meteorological data and building energy consumption through a statistical analysis. Using weather data collected by the Korean Meteorological Agency (KMA) over a period of three years (2011–2014), prediction models that are able to predict heating thermal loads considering the time-lag phenomenon are developed. In addition, the study develops different prediction models for buildings of different sizes. The results confirm the existence of the time-lag phenomenon: the heating load experienced by a building at a given time is better explained by a regression model developed using the climatic conditions that existed two hours before. As such, conventional building simulation programs must endeavor to include time-lag as well as Aerosol Optical Depth (AOD) data as important factors in the prediction of building heating loads.

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Haj Hussein, M., S. Monna, A. Juaidi, A. Barlet, M. Baba, and D. Bruneau. "Effect of thermal mass of insulated and non-insulated walls on building thermal performance and potential energy saving." Journal of Physics: Conference Series 2042, no. 1 (November 1, 2021): 012159. http://dx.doi.org/10.1088/1742-6596/2042/1/012159.

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Abstract The presented study aims to evaluate the effect of thermal mass in heavyweight construction in residential buildings in Palestine on indoor thermal environment using a building performance simulation tool. The most used residential building types, shapes and sizes were used as typical models for indoor environment performance simulation. The paper used a sensitivity analysis for four different scenarios according to the location of thermal insulation in the wall for two climatic zones, when no heating and cooling was used. The building material’s thermal properties, infiltration, activities, time schedule, electric lighting and glazing selection were based on onsite studies. The results show that the internal thermal mass of the studied buildings influences their thermal performance and future potential energy demand for heating and cooling. Buildings with insulation positioned on the outside, with high thermal mass and high thermal time constant showed the best thermal performance for different climatic zones, whereas buildings without thermal insulation or with insulation from the inside showed the worst thermal performance. The position of thermal insulation will affect potential energy demand for heating and cooling in the residential buildings.

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Korobkov, S., A. Gnyrya, and V. Terekhov. "Aerodynamic and thermal interference between two building models." IOP Conference Series: Materials Science and Engineering 775 (April 18, 2020): 012140. http://dx.doi.org/10.1088/1757-899x/775/1/012140.

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Lomas, K. J., D. P. Bloomfield, A. Cole, F. Parand, and A. A. Pinney. "Dynamic thermal models: Reliability for domestic building design." Building Services Engineering Research and Technology 12, no. 4 (November 1991): 115–28. http://dx.doi.org/10.1177/014362449101200401.

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Maurer, Christoph, Christoph Cappel, and Tilmann E. Kuhn. "Simple models for building-integrated solar thermal systems." Energy and Buildings 103 (September 2015): 118–23. http://dx.doi.org/10.1016/j.enbuild.2015.05.047.

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Muhy Al-Din, Salar Salah, Hourakhsh Ahmad Nia, and Rokhsaneh Rahbarianyazd. "Enhancing Sustainability in Building Design: Hybrid Approaches for Evaluating the Impact of Building Orientation on Thermal Comfort in Semi-Arid Climates." Sustainability 15, no. 20 (October 23, 2023): 15180. http://dx.doi.org/10.3390/su152015180.

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The evaluation of human thermal comfort inside buildings plays a pivotal role in reducing energy consumption and enhancing sustainability in the built environment. The estimation of thermal comfort is based on objective (physical factors) and subjective (psychological factors) aspects. This study aimed to find a hybrid way to evaluate more accurate thermal comfort in the buildings as per their orientations. This study assessed the effect of building orientation on thermal comfort conditions in row houses in semi-arid climates, based on a synthesis of the predictive mean vote (PMV) model and the thermal sensation vote (TSV). For this purpose, row houses were selected in the region of this study. This study concluded that the PMV model calculates a lower thermal comfort level than the TSV method, and that the thermal comfort demand within the houses was higher than ASHRAE Standard 55. The occupants inside the houses had a lower thermal tolerance. This implied that the residents of these buildings can consume more energy during the summer, typically the harshest season. This study presented new mathematical models for occupants’ thermal comfort evaluation in the study region, depending on the building’s orientation. In both models, for assessing thermal performance during both the summer and winter seasons, east-facing buildings consistently ranked as the second-best orientation. This suggested that, overall, east-facing buildings can be considered the best choice throughout the entire year in terms of thermal comfort. This study suggested a novel indicator to evaluate the optimum building orientation in the study area in terms of thermal performance.

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García, Juan, Blanca Quintana, Antonio Adán, Víctor Pérez, and Francisco J. Castilla. "3D-TTA: A Software Tool for Analyzing 3D Temporal Thermal Models of Buildings." Remote Sensing 12, no. 14 (July 14, 2020): 2250. http://dx.doi.org/10.3390/rs12142250.

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Many software packages are designed to process 3D geometric data, although very few are designed to deal with 3D thermal models of buildings over time. The software 3D Temporal Thermal Analysis (3D-TTA) has been created in order to visualize, explore and analyze these 3D thermal models. 3D-TTA is composed of three modules. In the first module, the temperature of any part of the building can be explored in a 3D visual framework. The user can also conduct separate analyses of structural elements, such as walls, ceilings and floors. The second module evaluates the thermal evolution of the building over time. A multi-temporal 3D thermal model, composed of a set of thermal models taken at different times, is handled here. The third module incorporates several assessment tools, such as the identification of representative thermal regions on structural elements and the comparison between real and simulated (i.e., obtained from energy simulation tools) thermal models. The potential scope of this software and its applications within the field of energy efficiency are presented in various case studies at the end of the paper.

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González, Vicente Gutiérrez, Lissette Álvarez Colmenares, Jesús Fernando López Fidalgo, Germán Ramos Ruiz, and Carlos Fernández Bandera. "Uncertainy’s Indices Assessment for Calibrated Energy Models." Energies 12, no. 11 (May 31, 2019): 2096. http://dx.doi.org/10.3390/en12112096.

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Building Energy Models (BEMs) are a key element of the Energy Performance of Buildings Directive (EPBD), and they are at the basis of Energy Performance Certificates (EPCs). The main goal of BEMs is to provide information for building stakeholders; they can be a powerful market tool to increase demand for energy efficiency solutions in buildings without affecting the comfort of users, as well as providing other benefits. The next generation of BEMs should value buildings in a holistic and cost-effective manner across several complementary dimensions: envelope performances, system performances, and controlling the ability of buildings to offer flexible services to the grid by optimizing energy consumption, distributed generation, and storage. SABINA is a European project that aims to look for flexibility to the grid, targeting the most economic source possible: existing thermal inertia in buildings. In doing so, SABINA works with a new generation of BEMs that tend to mimic the thermal behavior of real buildings and therefore requires an accurate methodology to choose the model that complies with the requirements of the system. This paper details our novel extensive research on which statistical indices should be chosen in order to identify the best model offered by the calibration process developed by Fernandez et al. in a previous paper and therefore is a continuation of that work.

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Albatayneh, Aiman, Dariusz Alterman, Adrian Page, and Behdad Moghtaderi. "The Impact of the Thermal Comfort Models on the Prediction of Building Energy Consumption." Sustainability 10, no. 10 (October 10, 2018): 3609. http://dx.doi.org/10.3390/su10103609.

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Building energy assessment software/programs use various assumptions and types of thermal comfort models to forecast energy consumption. This paper compares the results of using two major thermal comfort models (adaptive thermal comfort and the predicted mean vote (PMV) adjusted by the expectancy factor) to examine their influence on the prediction of the energy consumption for several full-scale housing experimental modules constructed on the campus of the University of Newcastle, Australia. Four test modules integrating a variety of walling types (insulated cavity brick (InsCB), cavity brick (CB), insulated reverse brick veneer (InsRBV), and insulated brick veneer (InsBV)) were used for comparing the time necessary for cooling and heating to maintain internal thermal comfort for both models. This research paper exhibits the benefits of adopting the adaptive thermal model for building structures. It shows the effectiveness of this model in helping to reduce energy consumption, increasing the thermal comfort level for the buildings, and therefore reducing greenhouse emissions.

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Deconinck, An-Heleen, and Staf Roels. "Is stochastic grey-box modelling suited for physical properties estimation of building components from on-site measurements?" Journal of Building Physics 40, no. 5 (February 12, 2017): 444–71. http://dx.doi.org/10.1177/1744259116688384.

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In current energy requirements, the thermal performance of buildings is assessed with simplified energy models. A performance label is calculated based on thermal properties of the constituent components of the building envelope. These properties, however, do not include factors such as workmanship issues, or moisture or airflow influences which might affect the thermal performance as designed. To have a better view on the actual thermal quality of building components, a reliable thermal characterisation method of building components on-site is required. The typically used semi-stationary measurement methods have an application that is seasonally bounded or can require long measurement periods. Because of these drawbacks, dynamic parameter estimation methods have gained interest. In this article, the physical interpretability of a typical stochastic grey-box model used to thermally characterise building components is assessed. The identifiability of this model structure is examined by observing the profile likelihood of its parameters for typical measurements. The results allow identification of the extent to which models can estimate the thermal properties of building components in a robust way. A comparison of both analyses allows to define indications for physically interpretable parameters.

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Erişen, Serdar. "A Systematic Approach to Optimizing Energy-Efficient Automated Systems with Learning Models for Thermal Comfort Control in Indoor Spaces." Buildings 13, no. 7 (July 19, 2023): 1824. http://dx.doi.org/10.3390/buildings13071824.

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Energy-efficient automated systems for thermal comfort control in buildings is an emerging research area that has the potential to be considered through a combination of smart solutions. This research aims to explore and optimize energy-efficient automated systems with regard to thermal comfort parameters, energy use, workloads, and their operation for thermal comfort control in indoor spaces. In this research, a systematic approach is deployed, and building information modeling (BIM) software and energy optimization algorithms are applied at first to thermal comfort parameters, such as natural ventilation, to derive the contextual information and compute the building performance of an indoor environment with Internet of Things (IoT) technologies installed. The open-source dataset from the experiment environment is also applied in training and testing unique black box models, which are examined through the users’ voting data acquired via the personal comfort systems (PCS), thus revealing the significance of Fanger’s approach and the relationship between people and their surroundings in developing the learning models. The contextual information obtained via BIM simulations, the IoT-based data, and the building performance evaluations indicated the critical levels of energy use and the capacities of the thermal comfort control systems. Machine learning models were found to be significant in optimizing the operation of the automated systems, and deep learning models were momentous in understanding and predicting user activities and thermal comfort levels for well-being; this can optimize energy use in smart buildings.

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Gölzhäuser, Simon, and Lilli Frison. "Comparison of different deep neural networks for system identification of thermal building behavior." Journal of Physics: Conference Series 2600, no. 7 (November 1, 2023): 072008. http://dx.doi.org/10.1088/1742-6596/2600/7/072008.

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Abstract Having accurate information available about future thermal building behavior can help to make good decisions in various heating control tasks. However, creating precise mathematical models for many different buildings is a complex and time-consuming task, owing to the heterogeneity of the building stock and the behavior of its occupants. In this paper, we propose a DNN-based system identification approach for predicting the room temperature inside a building based on past information and future weather forecasts. We evaluate various state-of-the-art and custom-built DNN architectures for TSF. Besides prediction performance, storage space and inference speed as measures for the respective model’s complexity are also taken into account. Our main contribution is demonstrating the effectiveness of these models in predicting the room temperature for differently parameterized simulated buildings. By using several distinct buildings for training, validation and testing, we additionally show that these models are capable to generalize in a way such that the room temperature for different buildings can be predicted by a single model, without any changes or adaptions.

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Peng, Bo, and Sheng-Jen Hsieh. "Cyber-Enabled Optimization of HVAC System Control in Open Space of Office Building." Sensors 23, no. 10 (May 18, 2023): 4857. http://dx.doi.org/10.3390/s23104857.

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Thermal comfort is crucial to well-being and work productivity. Human thermal comfort is mainly controlled by HVAC (heating, ventilation, air conditioning) systems in buildings. However, the control metrics and measurements of thermal comfort in HVAC systems are often oversimplified using limited parameters and fail to accurately control thermal comfort in indoor climates. Traditional comfort models also lack the ability to adapt to individual demands and sensations. This research developed a data-driven thermal comfort model to improve the overall thermal comfort of occupants in office buildings. An architecture based on cyber-physical system (CPS) is used to achieve these goals. A building simulation model is built to simulate multiple occupants’ behaviors in an open-space office building. Results suggest that a hybrid model can accurately predict occupants’ thermal comfort level with reasonable computing time. In addition, this model can improve occupants’ thermal comfort by 43.41% to 69.93%, while energy consumption remains the same or is slightly reduced (1.01% to 3.63%). This strategy can potentially be implemented in real-world building automation systems with appropriate sensor placement in modern buildings.

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Krstic-Furundzic, Aleksandra, and Vesna Kosoric. "Improvement of energy performances of existing buildings by application of solar thermal systems." Spatium, no. 20 (2009): 19–22. http://dx.doi.org/10.2298/spat0920019k.

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Improvement of energy performances of the existing buildings in the suburban settlement Konjarnik in Belgrade, by the application of solar thermal systems is the topic presented in this paper. Hypothetical models of building improvements are created to allow the benefits of applying solar thermal collectors to residential buildings in Belgrade climate conditions to be estimated. This case study presents different design variants of solar thermal collectors integrated into a multifamily building envelope. The following aspects of solar thermal systems integration are analyzed in the paper: energy, architectural, ecological and economic. The results show that in Belgrade climatic conditions significant energy savings and reduction of CO2 emissions can be obtained with the application of solar thermal collectors.

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Korobkov, S. V., A. I. Gnyrya, and V. I. Terekhov. "DYNAMIC AND THERMAL INTERFERENCE EFFECTS ON TWO NEIGHBOURING BUILDING MODELS." Vestnik Tomskogo gosudarstvennogo arkhitekturno-stroitel'nogo universiteta. JOURNAL of Construction and Architecture 21, no. 5 (October 29, 2019): 138–50. http://dx.doi.org/10.31675/1607-1859-2019-21-5-138-150.

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The paper considers the dynamic and thermal interference effects on two neighbouring building models in the form of square prisms arranged at a short distance from each other. It is shown how relative positions of the models affect the specific phenomena caused by the airflow interactions.The aim of this paper is to experimentally study the dynamic and thermal interference of a tandem of two building models in the form of square prisms depending on their relative position.The phenomenon of wind loads on buildings and structures has always attracted great interest among engineers and researchers. With the accumulation of knowledge and technical capabilities, the potential for likely ways to study wind flows and their impact on different objects increased. In recent years, the world science has accumulated an extensive knowledge base on wind impacts on objects of various shapes, such as prisms, pyramids, cylinders, etc. Studies are carried out for their mutual impact of several objects on changes in both the wind load and heat exchange. Their mutual effect on the air motion and turbulence is considered.There are two main areas in the field of the wind impact. The first impact is the force load on building, the second is the wind as a source of convective heat exchange. The object of this study is the interference parameters allowing to assess the influence on the field of pressure and heat recoil of disturbances evoked in front of the barriers.At the first stage, physical models help to study the pressure field on different facets and ratios of the local and medium heat exchange under the forced convection conditions. The next step is to jointly consider the wind (dynamic) load and heat flows, attempting to detect the total contribution to changes depending on the reciprocal model arrangement. All experiments are performed in the aerodynamic tube, at the TSUAB department. It is shown that the dynamic and thermal interference ratios vary greatly in two building models. At the same time, the thermal interference is very conservative compared to the dynamic. Using the interference parameters, it is easy to analyze the extreme pressure and the heat flow on the model surface depending on a large number of factors, including their arrangement.

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Park, Herie, and Sang-Bong Rhee. "IoT-Based Smart Building Environment Service for Occupants’ Thermal Comfort." Journal of Sensors 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/1757409.

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This paper presents an Internet of Things (IoT) platform for a smart building which provides human care services for occupants. The individual health profiles of the occupants are acquired by the IoT-based smart building, which uses the accumulated knowledge of the occupants to provide better services. To ensure the thermal comfort of the occupants inside the building, we propose a dynamic thermal model of occupants. This model is based on the heat balance equation of human body and thermal characteristics of the occupants. We implement this model in two smart building models with heaters controlled by a temperature and thermal comfort index using MATLAB/Simulink®. The simulation results show that the thermal comfort-based control is more effective to maintaining occupants’ thermal satisfaction and is therefore recommended for use providing human care services using IoT platforms in smart buildings.

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Deng, Kun, Siddharth Goyal, Prabir Barooah, and Prashant G. Mehta. "Structure-preserving model reduction of nonlinear building thermal models." Automatica 50, no. 4 (April 2014): 1188–95. http://dx.doi.org/10.1016/j.automatica.2014.02.009.

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Kramer, Rick, Jos van Schijndel, and Henk Schellen. "Simplified thermal and hygric building models: A literature review." Frontiers of Architectural Research 1, no. 4 (December 2012): 318–25. http://dx.doi.org/10.1016/j.foar.2012.09.001.

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Ahmad, Q. T. "Review paper: Validation of building thermal and energy models." Building Services Engineering Research and Technology 19, no. 2 (May 1998): 61–66. http://dx.doi.org/10.1177/014362449801900201.

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Jiménez, M. J., and H. Madsen. "Models for describing the thermal characteristics of building components." Building and Environment 43, no. 2 (February 2008): 152–62. http://dx.doi.org/10.1016/j.buildenv.2006.10.029.

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Boyer, H., J. P. Chabriat, B. Grondin-Perez, C. Tourrand, and J. Brau. "Thermal building simulation and computer generation of nodal models." Building and Environment 31, no. 3 (May 1996): 207–14. http://dx.doi.org/10.1016/0360-1323(96)00001-7.

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Xi, Hongyan, Qilin Zhang, Zhiyi Ren, Guangchen Li, and Yixing Chen. "Urban Building Energy Modeling with Parameterized Geometry and Detailed Thermal Zones for Complex Building Types." Buildings 13, no. 11 (October 24, 2023): 2675. http://dx.doi.org/10.3390/buildings13112675.

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Urban building energy modeling (UBEM) has attracted wide attention to the requirement for global carbon emission reduction. This paper presents a UBEM tool, AutoBPS-Param, to generate building energy models (BEMs) with parameterized geometry and detailed thermal zones, especially for complex building types, considering the shading effect from surrounding buildings simultaneously. Three building number scales and four scenarios were analyzed in the hotel-related buildings in Changsha, China. For the prototype modeling of Scenario 1, eighteen prototype building energy models for six building types in three vintages were created, and their simulation results were aggregated based on their representative floor areas. For AutoBPS-Param of Scenario 4, the method created one EnergyPlus (Version: 9.3.0) model for each building. The geometry of the prototype model was scaled and modified based on the target building’s length, width, and number of stories. The surrounding buildings were also added to the AutoBPS-Param simulation to better capture the urban dynamic impact. The results showed that the annual electricity and natural gas energy use intensity (EUI) of the pre-2005 HotelOffice prototype model was 172.25 and 140.45 kWh/m2. In contrast, with the AutoBPS-Param method, the annual electricity EUIs of 71 HotelOffice buildings constructed before 2005 ranged from 159.51 to 213.58 kWh/m2 with an average of 173.14 kWh/m2, and the annual gas EUIs ranged from 68.02 to 229.12 kWh/m2 with an average of 108.89 kWh/m2. The proposed method can better capture the diversity of urban building energy consumption.

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Lin, Chen, Qiu Xia Wang, and Xiao Tong Peng. "Parameter Analysis on Energy-Saving Behavior of a Steel Residential Building." Applied Mechanics and Materials 361-363 (August 2013): 235–38. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.235.

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The steel residential building has been widely used for its good seismic performances. In order to study the energy-saving behavior of the existing steel residential building, an on-site test on envelope structure of a typical steel building in cold region is conducted. Based on that, a simplified numerical model is established in which dynamic energy theories, solar radiations and indoor thermal disturbances are considered. The model is verified through testing data. Parameter analyses including 6 series sum up to 38 models are carried out on 6 main influential factors. The results show that improving thermal behavior of building envelope, adopting flexible sunshade schemes in different seasons, using even and simple building configuration and adopting different window-wall ratios for windows with different orientation are effective ways to decrease the energy consumption of buildings. The thermal design recommendations for steel residential buildings are also produced.

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Sigalingging, Roy Candra P. "Studi Dampak Penggunaan Insulasi pada Bangunan Rumah Tinggal Terhadap Konsumsi Energi Pendingin Ruangan." Journal of Science and Applicative Technology 5, no. 2 (December 12, 2021): 418. http://dx.doi.org/10.35472/jsat.v5i2.610.

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The global warming issue has become a concern for environmentalists activists, including many governments. This concern is due to the increasing attention to reducing the use of fossil energy because fossil energy has significantly exacerbated global warming. To minimize the use of fossil energy, especially the housing sector that is one of the extensive energy users. Building performance's analysis is done by creating changes to the case study's building envelope material. Case study buildings were simulated in energy analysis software. Preliminary analysis shows how the performance of the case study building is still far from the standard of thermal comfort. Air conditioning (AC) usage in the room will give comfort in terms of temperature. But, even though with the AC, the humidity level of the room was still high. Two building models are then created in the software to see the performance of the building by making changes to the building envelope material. With the settings on air-conditioning (AC) and environmental conditions in both models, the results indicate differences in the building performance of the two buildings. The results show that the building with insulation are using less energy and can provide optimal comfort for building users. Comfort is not only in terms of the building's temperature but including building relative humidity. In buildings with insulation, the temperature and humidity of the building are relatively stable throughout the year.

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Schwan, Lukas, Jakob Hahn, Michael Barton, Ronja Anders, and Christian Schweigler. "Development of Reference Buildings to Analyze the Potential for Energy-Efficient Refurbishment of Buildings." Civil and Environmental Engineering Reports 29, no. 4 (December 1, 2019): 198–217. http://dx.doi.org/10.2478/ceer-2019-0055.

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Abstract The building sector offers the largest potential for a significant reduction of greenhouse gas emissions. Based on own preliminary investigations for the State of Bavaria, a complete renovation of the building envelope of the current residential building stock would result in a reduced demand for final thermal energy for space heating and domestic hot water by about 70 %. The present study analyzes different existing reference buildings and reference methods. Based on a general literature review, specific criteria will be developed for reference models to represent the thermal energy consumption of the residential building stock for the regional domain under investigation. The objective is to represent the building stock with a limited amount of reference buildings. The method for the development of a reference building will be shown exemplarily for one category.

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Behrouzi, Fatemeh, Adi Maimun Abdul Malik, Nor Azwadi Che Sidik, Mehdi Nakisa, and Afiq Muhammad Yazid Witri. "Numerical Prediction of Thermal Effect on Flow Field around a High-Rise Building Model." Applied Mechanics and Materials 554 (June 2014): 680–85. http://dx.doi.org/10.4028/www.scientific.net/amm.554.680.

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Recently, CFD (Computational Fluid Dynamics) is being more and more used in the investigation of the flow and thermal around high-rise buildings. In this study, prediction of thermal effect on flow pattern around high-rise buildings model located in the surface boundary layer was carried out using k-e turbulence model. Investigation of thermal effect on flow pattern behind the building and comparison between isothermal and non-isothermal building using standard k-e showed that the surface temperature of building wall led to a strong upward motion close to heating wall and decreased the reattachment length behind it. The model sittings of validation study was accomplished by comparing the simulation of wind flow around building models with the experimental data of Architectural Institute of Japan (AIJ) that results showed in weak wind region, standard k-e has good agreement with experimental.

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Zhou, Ao, Kwun-Wah Wong, and Denvid Lau. "Thermal Insulating Concrete Wall Panel Design for Sustainable Built Environment." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/279592.

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Air-conditioning system plays a significant role in providing users a thermally comfortable indoor environment, which is a necessity in modern buildings. In order to save the vast energy consumed by air-conditioning system, the building envelopes in envelope-load dominated buildings should be well designed such that the unwanted heat gain and loss with environment can be minimized. In this paper, a new design of concrete wall panel that enhances thermal insulation of buildings by adding a gypsum layer inside concrete is presented. Experiments have been conducted for monitoring the temperature variation in both proposed sandwich wall panel and conventional concrete wall panel under a heat radiation source. For further understanding the thermal effect of such sandwich wall panel design from building scale, two three-story building models adopting different wall panel designs are constructed for evaluating the temperature distribution of entire buildings using finite element method. Both the experimental and simulation results have shown that the gypsum layer improves the thermal insulation performance by retarding the heat transfer across the building envelopes.

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Álvarez, José Antonio, Juan Ramón Rabuñal, Dolores García-Vidaurrázaga, Alberto Alvarellos, and Alejandro Pazos. "Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks." Advances in Civil Engineering 2018 (November 28, 2018): 1–10. http://dx.doi.org/10.1155/2018/7612623.

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Increasing the energy efficiency of buildings is a strategic objective in the European Union, and it is the main reason why numerous studies have been carried out to evaluate and reduce energy consumption in the residential sector. The process of evaluation and qualification of the energy efficiency in existing buildings should contain an analysis of the thermal behavior of the building envelope. To determine this thermal behavior and its representative parameters, we usually have to use destructive auscultation techniques in order to determine the composition of the different layers of the envelope. In this work, we present a nondestructive, fast, and cheap technique based on artificial neural network (ANN) models that predict the energy performance of a house, given some of its characteristics. The models were created using a dataset of buildings of different typologies and uses, located in the northern area of Spain. In this dataset, the models are able to predict the U-opaque value of a building with a correlation coefficient of 0.967 with the real U-opaque measured value for the same building.

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Lecomte, V., H. Macher, and T. Landes. "COMBINATION OF THERMAL INFRARED IMAGES AND LASERSCANNING DATA FOR 3D THERMAL POINT CLOUD GENERATION ON BUILDINGS AND TREES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W1-2022 (December 8, 2022): 129–36. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w1-2022-129-2022.

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Abstract. The thermal infrared study of urban environments is of growing interest. It allows to observe the variations of surface temperatures on objects over time and therefore the microclimate at the scale of a street. To facilitate the analysis of thermal interactions between urban elements, it is necessary to provide a 3D visualization of the thermography of a street. For this purpose, 3D thermal models combining geometric and thermal infrared (TIR) measurements are required. The chosen format for 3D thermal models is a point cloud with a temperature attribute. In our approach, two types of urban components are considered: buildings and trees. The geometric data of each component are acquired with a static laser scanner and the surface temperature is acquired with a thermal handheld camera. For the building, the approach consists in georeferencing TIR images and colorize the point cloud by projection. For trees, the approach consists of the colorization of each laser scan prior to the registration. The spherical panoramic images acquired with the Terrestrial Laser Scanning (TLS) are used as references to automatically georeferenced the TIR and thus to save time. The 3D thermal models obtained highlight the impact of sunlight on buildings and trees. At building scale, this thermal representation also helps to emphasize thermal bridges, as well as the shadow generated by surrounding trees. At tree scale, this representation is useful for monitoring the temporal and spatial variability of trunk’s and leave’s temperatures. Obviously, the thermal models underline the impact of trees on the urban environment.

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Iwaszczuk, D., and U. Stilla. "Alignment of 3D Building Models and TIR Video Sequences with Line Tracking." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 17–24. http://dx.doi.org/10.5194/isprsannals-ii-1-17-2014.

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Thermal infrared imagery of urban areas became interesting for urban climate investigations and thermal building inspections. Using a flying platform such as UAV or a helicopter for the acquisition and combining the thermal data with the 3D building models via texturing delivers a valuable groundwork for large-area building inspections. However, such thermal textures are useful for further analysis if they are geometrically correctly extracted. This can be achieved with a good coregistrations between the 3D building models and thermal images, which cannot be achieved by direct georeferencing. Hence, this paper presents methodology for alignment of 3D building models and oblique TIR image sequences taken from a flying platform. In a single image line correspondences between model edges and image line segments are found using accumulator approach and based on these correspondences an optimal camera pose is calculated to ensure the best match between the projected model and the image structures. Among the sequence the linear features are tracked based on visibility prediction. The results of the proposed methodology are presented using a TIR image sequence taken from helicopter in a densely built-up urban area. The novelty of this work is given by employing the uncertainty of the 3D building models and by innovative tracking strategy based on a priori knowledge from the 3D building model and the visibility checking.

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Ignjatovic, Marko, Bratislav Blagojevic, Mirko Stojiljkovic, Dejan Mitrovic, Aleksandar Andjelkovic, and Milica Ljubenovic. "Sensitivity analysis for daily building operation from the energy and thermal comfort standpoint." Thermal Science 20, suppl. 5 (2016): 1485–500. http://dx.doi.org/10.2298/tsci16s5485i.

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Improving energy performance of buildings is one of the most important tasks for reaching sustainability. Assessing building energy consumption is performed more often with specialized simulation tools. Sensitivity analysis proved to be a valuable tool for creating more reliable and realistic building energy models and better buildings. This paper briefly describes the methodology for running global sensitivity analysis and tools that can be used, and presents the results of such an analysis conducted for winter period, daily, on input variables covering a real building's operation, control and occupant related parameters that affect both thermal comfort and heating energy consumption. Two sets of inputs were created. The only difference between these sets is an addition of clothing insulation and occupant heat gain as input variables. The reference building was simulated for three distinctive winter weeks. Two additional input variables have an effect especially on thermal comfort, but they do not disturb the relative order of other influential input variables. The common influential variables for both energy consumption and thermal comfort were identified and are: air handling unit sup-ply temperature and airflow rate and control system related parameters. This can help in future research into implementing the simulation-assisted optimized operation in real buildings.

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Jeong, Bonghoon, Donghyun Kim, Joosang Lee, and Taeyeon Kim. "Development of Virtual Human Agents with Different Thermal Preferences for Energy and Thermal Comfort Simulation." E3S Web of Conferences 396 (2023): 01050. http://dx.doi.org/10.1051/e3sconf/202339601050.

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Researchers have used building energy simulation tools such as EnergyPlus to evaluate building energy and occupant thermal preference. EnergyPlus is a powerful tool for modeling buildings, However, when controlling the indoor set temperature using EnergyPlus, it is common to assume that all occupants’ thermal preference is same. Therefore, it is difficult to know dynamic personal thermal preferences and to implement occupant centric set-point control. In this study, we propose the various human agents with different thermal preference to realize the reliability of the simulation. First, we make an agent generation algorithm by referring the characteristics of various existing individual thermal preference models. And then, create agents with a virtual thermal preference to suit our needs. Through that, it is expected to allow human agents to feel different preference in one space during simulation. The final significance of the study is to contribute to the evaluation of building energy and thermal comfort closer to reality through the agent created in this method.

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USMAN HARUNA, IBRAHIM, IBRAHIM AHMAD RUFAI, and DALHATU BALARABE YAHAYA. "THERMAL COMFORT MODEL DEVELOPMENT FOR OFFICE BUILDINGS WITH HYBRID DOWNDRAFT EVAPORATIVE COOLERS IN BAYERO UNIVERSITY KANO." BIMA JOURNAL OF SCIENCE AND TECHNOLOGY (2536-6041) 6, no. 01 (April 30, 2022): 41–49. http://dx.doi.org/10.56892/bimajst.v6i01.312.

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The numerous thermal comfort models developed for air-conditioned and free-running spaces areunsuitable for accurate prediction of thermal comfort of buildings equipped with hybrid downdraftevaporative cooling (HDEC) systems. This study attempts to develop a thermal comfort model foroffice buildings equipped with the HDEC in the new campus of Bayero University Kano. Thewindows of the office buildings were optimized using Taguchi analysis. The 3D model of thebaseline office building using the optimum window-to-wall ratio (WWR) of 25% was developedand numerically analyzed using DesignBuilder CFD simulation. The numerical PMVopt resultswere employed for training the thermal comfort model using the statistical software packageMinitab 19. The validation shows a good agreement between the predicted results and theexperimental data. The developed model could help building designers and engineers to makeappropriate decisions at design stage regarding the thermal comfort of office buildings to beequipped with the HDEC systems.Keywords: Thermal comfort, CFD simulation, Experimental study, Predicted mean vote, Thermalcomfort model

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Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprsannals-iii-1-3-2016.

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Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.

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Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprs-annals-iii-1-3-2016.

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Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.

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Lomas, K. J. "Availability of monitored hourly building performance data for validating dynamic thermal models of buildings." Building Services Engineering Research and Technology 12, no. 2 (May 1991): 71–74. http://dx.doi.org/10.1177/014362449101200203.

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Maistrenko, A. V. "Building structures thermal calculation." Advanced Engineering Research 21, no. 3 (October 18, 2021): 260–67. http://dx.doi.org/10.23947/2687-1653-2021-21-3-260-267.

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Introduction. The thermal calculation of a volumetric structure using the finite element method is considered. According to the plans of the Ministry of Energy of the Russian Federation, a powerful wind energy industry will be created in the country in the coming years. In this regard, calculations in the production of building structures of wind power plants are currently becoming a challenge. The production of such fiberglass structures is a complex thermochemical process, including the polymerization of the binder under strictly specified thermal conditions. The work objective is to develop a method for three-dimensional finite element calculation of the non-stationary heating mode of a complexshaped composite structure.Materials and Methods. The determination of the temperature fields of a complex-shaped structure made of inhomogeneous materials causes using numerical methods and, first of all, the finite element method. The finite element modeling of the behavior of composite materials under molding is still incomplete. For its partial solution, the well-known heat conduction equation is adapted for a specific problem based on the first law of thermodynamics. New finite element models describing the thermal fields in the structure during its manufacture are proposed. The accuracy of modeling thermal processes is specified. Numerical simulation of heating is carried out.Results. The solution to the problem was performed in the multifunctional software complex ANSYS with the implementation of the calculation method in the parametric programming language APDL. The temperature fields of the blade elements of wind power plants at the stage of their manufacture were calculated, which made it possible to identify the characteristic features of the production process of these structures and to obtain recommendations for clarifying the process of their gluing.Discussion and Conclusions. The results obtained can be used in thermal calculations of elements of complex layered structures made of composite materials in wind power, mechanical engineering, aircraft, shipbuilding, instrumentation, etc.

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Journal articles on the topic 'Building thermal models'

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