Yang Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Yang Wang has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
Hong Hao
4 shared publicationsJingde Li
3 shared publications- David E. Harris
Is the Group Head of Sustainable Business, London Stock Exchange Group and FTSE Russell in London, UK
1 shared publication Ernst D von Meerwall
Maurice Morton Institute of Polymer Science, The University of Akron, Akron, OH 44325, USA
1 shared publicationFeng Ren
Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China
1 shared publication- Gecheng Zha
University of Miami
1 shared publication
Latest Publications
- Open Access
- 24 April 2024
- Published by Elsevier in Journal of Loss Prevention in the Process Industries
- Vol. 90
Prediction of BLEVE loading on structures
- 24 April 2024
- Published by Elsevier in Journal of Loss Prevention in the Process Industries
- Vol. 90
Open AccessPrediction of BLEVE loading on structures
- Open Access
- 3 May 2023
- Published by Elsevier in Process Safety and Environmental Protection
- Vol. 175, 1-16
Prediction of BLEVE loading on a rigid structure
- 3 May 2023
- Published by Elsevier in Process Safety and Environmental Protection
- Vol. 175, 1-16
Open AccessPrediction of BLEVE loading on a rigid structure
- Open Access
- 3 February 2023
- Published by Elsevier in Process Safety and Environmental Protection
- Vol. 171, 914-925
Prediction of BLEVE loads on structures using machine learning and CFD
- 3 February 2023
- Published by Elsevier in Process Safety and Environmental Protection
- Vol. 171, 914-925
Open AccessPrediction of BLEVE loads on structures using machine learning and CFD
- 2 December 2022
- Published by Elsevier in Engineering Structures
- Vol. 276
A comparative study on the most effective machine learning model for blast loading prediction: From GBDT to Transformer
- 2 December 2022
- Published by Elsevier in Engineering Structures
- Vol. 276
A comparative study on the most effective machine learning model for blast loading prediction: From GBDT to Transformer
- 2 November 2022
- Published by Elsevier in Journal of Loss Prevention in the Process Industries
- Vol. 80
A state-of-the-art review of experimental and numerical studies on BLEVE overpressure prediction
- 2 November 2022
- Published by Elsevier in Journal of Loss Prevention in the Process Industries
- Vol. 80
A state-of-the-art review of experimental and numerical studies on BLEVE overpressure prediction
- 28 July 2021
- Published by With Intelligence LLC in Practical Applications
- Vol. 9 (2) , 1.10-7
Practical Applications of EU Paris-Aligned and Climate Transition Benchmarks: A Case Study
In EU Paris-Aligned and Climate Transition Benchmarks: A Case Study, from the Summer 2021 issue of The Journal of Impact and ESG Investing, authors Yang Wang, Peter Gunthorp, and David Harris (all of FTSE Russell) address the climate transition benchmarks laid out by the EU’s Commission Delegated Regulation 2020/1818 (the Benchmark Regulation). The authors use a tilt-based target exposure framework to construct portfolios to meet the new benchmarks and demonstrate their performance over a 10-year simulation period. They also use third-party assessments for corporate target-setting requirements and examine how adding those assessments affects portfolio allocations.
- 28 July 2021
- Published by With Intelligence LLC in Practical Applications
- Vol. 9 (2) , 1.10-7
Practical Applications of EU Paris-Aligned and Climate Transition Benchmarks: A Case Study
In EU Paris-Aligned and Climate Transition Benchmarks: A Case Study, from the Summer 2021 issue of The Journal of Impact and ESG Investing, authors Yang Wang, Peter Gunthorp, and David Harris (all of FTSE Russell) address the climate transition benchmarks laid out by the EU’s Commission Delegated Regulation 2020/1818 (the Benchmark Regulation). The authors use a tilt-based target exposure framework to construct portfolios to meet the new benchmarks and demonstrate their performance over a 10-year simulation period. They also use third-party assessments for corporate target-setting requirements and examine how adding those assessments affects portfolio allocations.
- 8 June 2020
- Published by American Institute of Aeronautics and Astronautics (AIAA)
Study of Reynolds Number Effect for 2D Co-Flow Jet Airfoil at Cruise Conditions
This paper numerically studies the Reynolds number effect for a 2D Co-Flow Jet (CFJ) airfoil and a 3D wing at freestream Mach number of 0.46. The Reynolds averaged Navier-Stokes equations solver with Spalart-Allmaras one-equation turbulence model is utilized for the simulation. The Reynolds number is decreased from 4.1x10^6 to 0.18x10^6 to mimic the altitude change from 10000 m to 30000 m. The results show that, at Reynolds number of 4.1x10^6, the best CFJ airfoil corrected aerodynamic efficiency (CL/CDc) of 81.64 occurs at Cmu of 0.03 at AoA of 6deg. When the Reynolds number is reduced to 0.18x10^6, the (CL/CD)c has a 39.5% decrease. It is because of the dramatic increase of the viscous drag by 66.2%. However, the lift coefficient drops only by 5.1%. The second reason for the decrease of the CFJ airfoil corrected aerodynamic efficiency is that the power coefficient Pc is increased significantly by 85% with the decrease of the Reynolds number. It is caused mostly by the increased total pressure ratio of CFJ pumping due to higher loss. The 3D wing with an aspect ratio of 20 based on the same 2D airfoil is also studied for the same Reynolds numbers and freestream Mach number. Similar to the 2D cases, the wing at low Reynolds number suffers significantly increased viscous drag and energy loss of the CFJ.
- 8 June 2020
- Published by American Institute of Aeronautics and Astronautics (AIAA)
Study of Reynolds Number Effect for 2D Co-Flow Jet Airfoil at Cruise Conditions
This paper numerically studies the Reynolds number effect for a 2D Co-Flow Jet (CFJ) airfoil and a 3D wing at freestream Mach number of 0.46. The Reynolds averaged Navier-Stokes equations solver with Spalart-Allmaras one-equation turbulence model is utilized for the simulation. The Reynolds number is decreased from 4.1x10^6 to 0.18x10^6 to mimic the altitude change from 10000 m to 30000 m. The results show that, at Reynolds number of 4.1x10^6, the best CFJ airfoil corrected aerodynamic efficiency (CL/CDc) of 81.64 occurs at Cmu of 0.03 at AoA of 6deg. When the Reynolds number is reduced to 0.18x10^6, the (CL/CD)c has a 39.5% decrease. It is because of the dramatic increase of the viscous drag by 66.2%. However, the lift coefficient drops only by 5.1%. The second reason for the decrease of the CFJ airfoil corrected aerodynamic efficiency is that the power coefficient Pc is increased significantly by 85% with the decrease of the Reynolds number. It is caused mostly by the increased total pressure ratio of CFJ pumping due to higher loss. The 3D wing with an aspect ratio of 20 based on the same 2D airfoil is also studied for the same Reynolds numbers and freestream Mach number. Similar to the 2D cases, the wing at low Reynolds number suffers significantly increased viscous drag and energy loss of the CFJ.
- 1 June 2020
- Published by Elsevier in Renewable Energy
- Vol. 153, 985-997
Evaluation of geothermal development considering proppant embedment in hydraulic fractures
- 1 June 2020
- Published by Elsevier in Renewable Energy
- Vol. 153, 985-997
Evaluation of geothermal development considering proppant embedment in hydraulic fractures
- 1 September 1994
- Published by Elsevier in Journal of Non-Crystalline Solids
- Vol. 172-174, 1047-1052
Study of Couette flow in polymer-based liquids via 1-D NMR imaging
- 1 September 1994
- Published by Elsevier in Journal of Non-Crystalline Solids
- Vol. 172-174, 1047-1052
Study of Couette flow in polymer-based liquids via 1-D NMR imaging