Improvements of Fast Fluid Dynamics for Simulating Air Flow in Buildings

Jin, Mingang; Chen, Qingyan

doi:10.1080/10407790.2012.724988

Cited by 37 publications

(15 citation statements)

References 25 publications

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“…be found in (Zuo and Chen 2009;Jin et al 2012). One can also refer to the parallelized FFD model by CUDA and OpenCL in these literature (Zuo and Chen 2010;Yang 2013;.…”

Section: Coupled Simulation Between Cfd and Multizone Models Based Onmentioning

confidence: 99%

Coupled Simulation between CFD and Multizone Models Based on Modelica Buildings Library to Study Indoor Environment Control

Tian

Sevilla

Sohn

2017

Linköping Electronic Conference Proceedings

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Multizone models are widely used in building airflow and energy performance simulations because they are often suitable for the analysis needed, and due to their fast computation speed. However, the results provided by the multizone models are sometimes limited due to the underlying well-mixed assumption of the air in a zone (e.g., a room). For zones where this assumption is not suitable, a Computational Fluid Dynamics (CFD) models may be needed. This paper proposes a coupled simulation model between the multizone and CFD model, which in the paper is fast fluid dynamics, a freely available and publicly released program. The model allows the simulation of a dynamic interaction between airflow and Heating, Ventilation and Air-Conditioning (HVAC) systems for buildings with stratified airflow distribution in some of the zones. The approach is implemented using Modelica and its buildings library. In this presentation, we first discuss the design and implementation of a data synchronization strategy between the two models. We then show a possible validation of the implementation by comparing the simulated results with experimental data from previous research. Finally, we perform a case study by linking a Variable Air Volume (VAV) terminal box to space in order to evaluate the capability of the coupled simulation. Finally, further research needs are discussed at the end of the paper.

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“…be found in (Zuo and Chen 2009;Jin et al 2012). One can also refer to the parallelized FFD model by CUDA and OpenCL in these literature (Zuo and Chen 2010;Yang 2013;.…”

Section: Coupled Simulation Between Cfd and Multizone Models Based Onmentioning

confidence: 99%

Coupled Simulation between CFD and Multizone Models Based on Modelica Buildings Library to Study Indoor Environment Control

Tian

Sevilla

Sohn

2017

Linköping Electronic Conference Proceedings

Self Cite

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“…Although more accurate than network and zonal models, FFD still needs further improvements to be used as an engineering tool. Recent works by (Jin et al, 2012) and have shown some promising outcomes.…”

Section: Introductionmentioning

confidence: 99%

“…The major constraint in developing transient models is excessive computation time (Jin et al, 2012); depending on the CFD model used the calculation time might extend from hours to months . Hence, CFD based models are limited in their ability to provide quick evaluation at conceptual design stage, and in conducting risk assessments for situations such as smoke management in case of building fire and the transmission of airborne infectious contaminant spreading in hospital wards.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, these models are not easily adaptable and require special models and zones to be incorporated for every new building configuration. CFD simulations can be coupled with multizone (Wang and Chen, 2007) models to improve accuracy for specific zones of interest, but at the expense of losing the advantage of fast computation time due to the CFD simulation's long computing time (Jin et al, 2012). More recently a fast fluid dynamics (FFD) method has been used to simulate indoor environments in real-time (Zuo and Chen, 2009;).…”

Section: Introductionmentioning

confidence: 99%

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Real-time flow simulation of indoor environments using lattice Boltzmann method

et al. 2015

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A novel lattice Boltzmann method (LBM) -based 3D computational fluid dynamics (CFD) technique has been implemented on the graphics processing unit (GPU) for the purpose of simulating the indoor environment in real-time . We study the time evolution of the turbulent air flow and temperature inside a test chamber and in a simple model of a four-bed hospital room. The predicted results from LBM are compared with traditional CFD-based large eddy simulations (LES). Reasonable agreement between LBM results and LES method are observed with significantly faster computational times.

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“…One of the CFD disadvantages is that it can be time-consuming. Therefore, another numerical method can be considered such as Fast fluid dynamic (FFD) [29]- [32]. FFD is less accurate than CFD but more stable and faster than CFD.…”

Section: List Of Tablesmentioning

confidence: 99%

A virtual thermostat for local temperature control

Alhashme

2016

Energy and Buildings

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This thesis presents design and operation of a newly developed virtual thermostat to control any desired local temperature in an HVAC controlled space. Conventional HVAC thermostats use a single point temperature sensor at one fixed location in a controlled space to control the temperature of the whole space. The single point temperature sensor does not represent the entire controlled domain. In addition, in most applications only a small zone in the controlled space needs to be controlled (for example where the people are located). Heating and cooling of the unnecessary zones lead to extra energy consumption that can be saved if only the required zones are controlled. Such a control system requires knowledge of the temperature distribution in the whole zone at all times. In this work, we have used computational fluid dynamics (CFD) to determine the distributive temperature inside the controlled space at all times and turn the HVAC system ON and OFF based on the temperature of the desired zone in the space. In this study, we have determined the energy savings by comparing the energy consumption of a conventional thermostat controlled system with a locally controlled one. Several cases with different heat losses, and different inlet air velocities and directions are studied. Energy savings of up to 22% is realized for the cases studied here. In addition, the study showed the effect of person's location on the energy saving using the local control. One of the main problems with such a control system is that the CFD calculations may take a long time (10-24 hours depending on the complexity of the iii problem), which is not practical for real-time temperature control. In order to reduce the computational times and simulate various operating conditions quickly, an artificial neural network (ANN) model is used to train the temperature control system. This resulted in reduction of the computational times to few seconds, making this system practical. This thesis, presents various elements of the newly developed virtual thermostat and its operating principals.iv

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Improvements of Fast Fluid Dynamics for Simulating Air Flow in Buildings

Cited by 37 publications

References 25 publications

Coupled Simulation between CFD and Multizone Models Based on Modelica Buildings Library to Study Indoor Environment Control

Coupled Simulation between CFD and Multizone Models Based on Modelica Buildings Library to Study Indoor Environment Control

Real-time flow simulation of indoor environments using lattice Boltzmann method

A virtual thermostat for local temperature control

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