TY - JOUR
T1 - Optimal design of an indoor environment using an adjoint RNG k-ε turbulence model
AU - Zhao, Xingwang
AU - Chen, Qingyan
N1 - Funding Information:
This research was partially supported by the National Key R&D Program of the Ministry of Science and Technology,
Funding Information:
This research was partially supported by the National Key R&D Program of the Ministry of Science and Technology, China, on ?Green Buildings and Building Industrialization? through Grant No. 2016YFC0700500 and by the National Natural Science Foundation of China through Grant No. 51478302.
Funding Information:
through Grant No. 2016YFC0700500 and by the National Natural Science Foundation of China through Grant No. 51478302.
Publisher Copyright:
© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0
PY - 2019/8/13
Y1 - 2019/8/13
N2 - The computational fluid dynamics (CFD)-based adjoint method can determine design variables of an indoor environment according to the optimal design objective, such as minimal predicted mean vote (PMV) for thermal comfort. The method calculates the gradient of the objective function over the design variables so that the objective function can be minimized along the fastest direction using an optimization algorithm. Since the RNG k-ε model is the most popular model used in CFD, the corresponding adjoint equations of the turbulence model should be solved during the design process, rather than the “frozen turbulence” assumption used in the existing approach. This investigation developed adjoint equations for the RNG k-ε turbulence model and applied it to a two-dimensional ventilated cavity. Design processes with the adjoint RNG k-ε turbulence model led to a near-zero design function for the cavity case, while that one with the RNG k-ε turbulence model did not.
AB - The computational fluid dynamics (CFD)-based adjoint method can determine design variables of an indoor environment according to the optimal design objective, such as minimal predicted mean vote (PMV) for thermal comfort. The method calculates the gradient of the objective function over the design variables so that the objective function can be minimized along the fastest direction using an optimization algorithm. Since the RNG k-ε model is the most popular model used in CFD, the corresponding adjoint equations of the turbulence model should be solved during the design process, rather than the “frozen turbulence” assumption used in the existing approach. This investigation developed adjoint equations for the RNG k-ε turbulence model and applied it to a two-dimensional ventilated cavity. Design processes with the adjoint RNG k-ε turbulence model led to a near-zero design function for the cavity case, while that one with the RNG k-ε turbulence model did not.
UR - http://www.scopus.com/inward/record.url?scp=85071862522&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/201911104037
DO - 10.1051/e3sconf/201911104037
M3 - Conference article
AN - SCOPUS:85071862522
SN - 2555-0403
VL - 111
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 04037
T2 - 13th REHVA World Congress, CLIMA 2019
Y2 - 26 May 2019 through 29 May 2019
ER -