Review of OpenFOAM applications in the computational wind engineering: from wind environment to wind structural engineering

被引:3
作者
Ricci, Alessio [1 ,2 ]
机构
[1] Univ Sch Adv Studies IUSS, Dept Sci Technol & Soc, Pavia, Italy
[2] Eindhoven Univ Technol, Dept Built Environm, Bldg Phys & Serv, Eindhoven, Netherlands
关键词
Review; OpenFOAM; Computational wind engineering; Mesoscale; Built environment; Structural engineering; LARGE-EDDY SIMULATION; BUILDINGS PAST ACHIEVEMENTS; MICROSCALE CFD SIMULATIONS; ATMOSPHERIC BOUNDARY-LAYER; PEDESTRIAN-LEVEL; POLLUTANT DISPERSION; NUMERICAL-SIMULATION; FLUID-DYNAMICS; K-EPSILON; INFLOW CONDITIONS;
D O I
10.1007/s11012-024-01826-x
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The use of computational fluid dynamics (CFD) in the wind engineering (WE) is generally defined as computational wind engineering (CWE). Since its foundation in 2004, the use of OpenFOAM in CWE has been increasing progressively and covers nowadays a wide range of topics, from wind environment to wind structural engineering. This paper was drafted in response to the invitation from the organizers of the 18th OpenFOAM workshop held in Genoa (Italy) on 11-14 July 2023, when a technical session on Civil Engineering and Wind Engineering was organized. In this paper the author briefly reviews the history of WE and surveys the evolution, methods, and future challenges of OpenFOAM in the CWE. Topics are here regrouped into three main research areas and discussed from a physical, engineering and purely computational perspective. The study does not cover the Wind Energy and related topics, since this can be considered nowadays as a stand-alone subfield of the WE. This review confirms that OpenFOAM is a versatile tool widely used for WE applications that often require new models to be developed ad hoc by CFD users. It can be coupled easily with numerical weather prediction models for mesoscale-microscale wind and thermal studies, with building energy simulation models to determine the energy demand, with finite element method for structural engineering design. OpenFOAM represents an extraordinary opportunity for all CFD users worldwide to share codes and case studies, to explore the potential of new functionalities and strengthen the network within the CFD community.
引用
收藏
页码:1695 / 1735
页数:41
相关论文
共 50 条
[21]   Appropriate boundary conditions for computational wind engineering: Still an issue after 25 years [J].
Richards, Peter J. ;
Norris, Stuart E. .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2019, 190 :245-255
[22]   Thunderstorm characteristics of importance to wind engineering [J].
Lombardo, Franklin T. ;
Smith, Douglas A. ;
Schroeder, John L. ;
Mehta, Kishor C. .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2014, 125 :121-132
[23]   Urban wind conditions and small wind turbines in the built environment: A review [J].
Anup, K. C. ;
Whale, Jonathan ;
Urmee, Tania .
RENEWABLE ENERGY, 2019, 131 :268-283
[24]   Wind engineering analysis of parabolic trough collectors to optimise wind loads and heat loss [J].
Paetzold, J. ;
Cochard, S. ;
Fletcher, D. F. ;
Vassallo, A. .
INTERNATIONAL CONFERENCE ON CONCENTRATING SOLAR POWER AND CHEMICAL ENERGY SYSTEMS, SOLARPACES 2014, 2015, 69 :168-177
[25]   Computational method in database-assisted design for wind engineering with varying performance objectives [J].
Merhi, Ali ;
Letchford, Chris W. .
WIND AND STRUCTURES, 2021, 32 (05) :439-452
[26]   A review of computational fluid dynamics (CFD) simulations of the wind flow around buildings for urban wind energy exploitation [J].
Toja-Silva, Francisco ;
Kono, Takaaki ;
Peralta, Carlos ;
Lopez-Garcia, Oscar ;
Chen, Jia .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2018, 180 :66-87
[27]   AN ANALYSIS FOR PARALLEL WIND SIMULATION USING OPENFOAM [J].
Frasheri, Neki ;
Atanassov, Emanouil .
SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2018, 19 (02) :97-105
[28]   Simulations of Wind Formation in Idealised Mountain-Valley Systems Using OpenFOAM [J].
Arias, Santiago ;
Rojas, Jose I. ;
Athota, Rathan B. ;
Montlaur, Adeline .
SUSTAINABILITY, 2023, 15 (02)
[29]   Koopman analysis by the dynamic mode decomposition in wind engineering [J].
Li, Cruz Y. ;
Chen, Zengshun ;
Zhang, Xuelin ;
Tse, Tim K. T. ;
Lin, Chongjia .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2023, 232
[30]   Research Progress of Machine Learning in Bridge Wind Engineering [J].
Laima S.-J. ;
Li W.-J. ;
Feng H. ;
Zhou X.-X. ;
Zhang Z.-Y. ;
Chen W.-L. ;
Li H. .
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 2023, 36 (08) :1-13