An artificial intelligence-based method to efficiently bring CFD to building simulation

Mazuroski, Walter; Berger, Julien; Oliveira, Ricardo C. L. F.; Mendes, Nathan

doi:10.1080/19401493.2017.1414880

Cited by 15 publications

(5 citation statements)

References 23 publications

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“…That being said, the avenue of optimizing coupling methods to make the co-simulations computationally practical, has been a primary focus of research studies in the field. 27,32,35,57 Various studies have evaluated the pros and cons of the possible methods that can be used to interchange data between BES and CFD. 19,58 The various coupling strategies may be classified under the two main categories of internal and external coupling.…”

Section: Resolution Of Challengesmentioning

confidence: 99%

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A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions

Singh

Sharston

2021

Building Services Engineering Research and Technology

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The paper presents a review of existing literature in the field of coupling Computational Fluid Dynamics (CFD) with Building Energy Simulations (BES) to better predict indoor environmental conditions and building energy implications. CFD is capable of providing a detailed analysis of airflow profile and temperature gradients in the space as well as better prediction of heat transfer involving convection and radiation. Whereas BES can provide dynamically changing boundary conditions to CFD to facilitate a precise transient analysis. Combining the two simulations provides a powerful framework to accurately predict building performance parameters. The review examines the variables exchanged between the two simulations and establishes that the Convective Heat Transfer Coefficient (CHTC) as the most important exchanged variable that can significantly improve the accuracy of energy simulations. Issues regarding the application of co-simulation mechanism are then discussed in terms of simulation discontinuities, along with strategies adopted by researchers to overcome the same. In the later sections, the review evaluates the applicability of co-simulation from the perspective of year-long building energy simulations and presents an overview of methods used in research to implement the same. Finally, the conclusions are discussed and the scope for future research in the field is presented. Practical implication: The review presents a critical analysis of essentially all major coupling strategies that can be used to perform a BES-CFD coupled analysis along with their strengths, limitations and possible application scenarios. Additionally, the problems associated with establishing the co-simulation are examined and various adopted solutions are presented along with methods implemented towards extending the practical applicability of such an analysis to encapsulate year-long simulations.

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Section: Resolution Of Challengesmentioning

confidence: 99%

“…Mazuroski et al. 57 utilized FMI to perform a co-simulation using Domus for BES and ANSYS CFX for CFD analysis. One major limitation of the FMI standard is that only the programs that support FMI and have a built-in interface can participate in the co-simulation process.…”

Section: Resolution Of Challengesmentioning

confidence: 99%

A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions

Singh

Sharston

2021

Building Services Engineering Research and Technology

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“…Data-driven methods have emerged in building energy modelling to overcome time, cost, and effort obstacles. In addition, data-driven techniques for better energy performance prediction use different methods such as autoregressive models [14], artificial neural networks [19,21,22], support vector regression [23] etc. Furthermore, suppose a more detailed and accurate assessment of building performance is desired.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, suppose a more detailed and accurate assessment of building performance is desired. In that case, a co-simulation can be performed (i.e., BES tools connected with computational fluid dynamics tool for advanced physics numerical analysis) [21]. Hence, such data-driven models become more scalable and flexible.…”

Section: Introductionmentioning

confidence: 99%

Development and Analysis of a Dynamic Energy Model of an Office Using a Building Management System (BMS) and Actual Measurement Data

et al. 2021

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Calibration of the energy model of a building is one of the essential tasks required to determine the efficiency of building management systems, and both their own and other systems’ improvement potential. In order to make the building energy model as accurate as possible, it is necessary to collect comprehensive data on its operation and sometimes to assess the missing information. This paper represents the process of developing an energy model for an administrative building and its calibration procedure, using detailed long-term measurement and building management system (BMS) data. Indoor air temperature, CO₂ concentration, and relative humidity were experimentally measured and evaluated separately. Such dual application of data reduces the inaccuracy of the assumptions made and assesses the model’s accuracy. The DesignBuilder software developed the building model. During the development of the model, it was observed that the actual energy consumption needs to be assessed, as the assumptions made during the design about the operation and management of HVAC systems often do not coincide with the actual situation. After integrating BMS information on HVAC management into the building model, the resulting discrepancy between the model results and the actual heat consumption was 6.5%. Such a model can be further used to optimize management decisions and assess energy savings potential.

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“…Some attempts have been made to include two-dimensional modeling in [9] considering both heat and mass transfer. In [10,11], a two-dimensional model has been proposed based on an intelligent co-simulation approach. However, those works assume only simple time-varying boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

An efficient two-dimensional heat transfer model for building envelopes

Berger

Gasparin

Mazuroski

et al. 2020

Numerical Heat Transfer, Part A: Applications

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A two-dimensional model is proposed for energy efficiency assessment through the simulation of heat transfer in building envelopes, considering the influence of the surrounding environment. The model is based on the Du Fort-Frankel approach that provides an explicit scheme with a relaxed stability condition. The model is first validated using an analytical solution and then compared to three other standard schemes. Results show that the proposed model offers a good compromise in terms of high accuracy and reduced computational efforts. Then, a more complex case study is investigated, considering non-uniform shading effects due to the neighboring buildings. In addition, the surface heat transfer coefficient varies with wind velocity and height, which imposes an addition non-uniform boundary condition. After showing the reliability of the model prediction, a comparison over almost 120 cities in France is carried out between the two-and the one-dimensional approaches of the current building simulation programs. Important discrepancies are observed for regions with high magnitudes of solar radiation and wind velocity. Last, a sensitivity analysis is carried out using a derivative-based approach. It enables to assess the variability of the solution according to the modeling of the two-dimensional boundary conditions. Moreover, the proposed model computes efficiently the solution and its sensitivity to the modeling of the urban environment.

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An artificial intelligence-based method to efficiently bring CFD to building simulation

Cited by 15 publications

References 23 publications

A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions

A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions

Development and Analysis of a Dynamic Energy Model of an Office Using a Building Management System (BMS) and Actual Measurement Data

An efficient two-dimensional heat transfer model for building envelopes

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