## Ping He

### Title(s):

Assistant Professor, Michael and Denise Mack 2050 Challenge Scholar

### Office

2243 Howe

537 Bissell Rd

Ames, IA 50011-1096

### Information

**Links:**

**Education:**

**Ph.D**. Engineering Thermophysics, Chinese Academy of Sciences, 2012

**B.S. **Thermal Energy and Power Engineering, Sichuan University, 2007

**Teaching:**

AerE 362: Aerospace Systems Integration

AerE 463/563: Introduction to Multidisciplinary Design Optimization

**Research Interests:**

Multidisciplinary Design Optimization (MDO)

Machine Learning and Reduced-order Modeling

Computational Fluid Dynamics (CFD)

Aircraft and Turbomachinery Design

Spacecraft Mission Optimization

**Sponsored Projects:**

Five funded projects from federal agencies and the industry. Total: $1.368M. My share: $515K.

Accelerating Scientific Discovery: A Toolset for Standardizing Data Collection and Machine Learning. The Ames National Lab, Department of Energy (DOE). Total award: $400K. 2023-2025. My role: PI. My share: $100K.

High-fidelity Multidisciplinary Design Optimization of Heat Exchangers for eVTOL Aircraft Thermal Management. National Aeronautics and Space Administration (NASA). Total award: $100K. 2023-2024. My role: Science PI. My share: $100K.

Collaborative Research: Enabling Large-scale Multidisciplinary Design Optimization with Unsteady Simulations: A Hybrid Pseudo-spectral Approach. National Science and Foundation (NSF). Total award: $575K. 2022−2025. My role: PI of the lead institute. My share: $250K.

5G Accelerated Scientific Discovery: Enabling AI at the Edge. The Ames National Lab, Department of Energy (DOE). Total award: $273K. 2021−2023. My role: co-PI. My share: $45K

High-fidelity MDO considering propeller-wing interaction. Hyundai Motor Company subcontracted from the University of Michigan. Total award: $19K. 2021−2022. My role: PI. My share: $20K

### Publications

**Selected Publications (of 55 papers including 25 journal and 30 conference papers. Google H-index: 16)**

Fang, L, **He, P. **“A Duality-Preserving Adjoint Method for Segregated Navier-Stokes Solvers”. *Journal of Computational Physics*, 2024

Fang, L, He, P. “Field inversion machine learning augmented turbulence modeling for time-accurate unsteady flow”. *Physics of Fluids*, 2024.

Harris, G, **He, P**, Abdelkhalik, O. “Control Co-Design Optimization of Spacecraft Trajectory and System for Interplanetary Missions.” *Journal of Spacecraft and Rockets*, 2024.

Wang, J, Hu, H, **He, P**, Hu, H. “A Machine Learning Study to Predict Wind-Driven Water Runback Characteristics”. *Physics of Fluids*, 2023.

Li, Z., **He, P.** “Accelerating Unsteady Aerodynamic Simulations Using Predictive Reduced-order Modeling”. *Aerospace Science and Technology*, 2023.

Koyuncuoglu, H.,** He, P. “**Simultaneous wing shape and actuator parameter optimization using the adjoint method”. *Aerospace Science and Technology*, 2022.

Secco, N., Kenway, G. K. W., **He, P.**, Mader, C. A., Martins, J. R. R. A. “Efficient mesh generation and deformation for aerodynamic shape optimization”. *AIAA Journal*, 2021.

Du, X., **He, P.**, Martins, J.R.R.A. “Rapid airfoil design optimization via neural network-based parameterization and surrogate modeling”. *Aerospace Science and Technology*, 2021.

**He, P.**, Mader, C.A., Martins, J.R.R.A., Maki, K.J. “DAFoam: An open-source adjoint framework for multidisciplinary design optimization with OpenFOAM”. *AIAA Journal*, 58, pp. 1304-1319, 2020.

**He, P.**, Mader, C.A., Martins, J.R.R.A., Maki, K.J. “Aerothermal optimization of a ribbed U bend cooling channel using the adjoint method”. *International Journal of Heat and Mass Transfer*, 140, pp. 152-172, 2019.

Kenway, G.K.W., Mader, C.A.,** He, P.**, Martins, J.R.R.A. “Effective adjoint approaches for computational fluid dynamics”. *Progress in Aerospace Sciences*, 110, p. 100542, 2019.

**He, P.**, Mader, C.A., Martins, J.R.R.A., Maki, K.J. “An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM”. *Computers & Fluids*, 168, pp. 285-303, 2018.