Jack Weatheritt

Computational Mechanics · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 12 citations into it

Whom Jack Weatheritt trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. John R. Koza
2. Cândida Ferreira
3. Richard D. Sandberg
4. Jeremy A. Templeton
5. François G. Schmitt

Who trusts Jack Weatheritt overall

1. Heng Xiao
2. Ricardo Vinuesa
3. Jin-Long Wu
4. Karthik Duraisamy
5. Richard D. Sandberg
6. Paola Cinnella
7. Steven L. Brunton
8. Gianluca Iaccarino
9. R. Tan
10. Eric Paterson

Papers from Jack Weatheritt's perspective

Ordered by how strongly the researchers Jack Weatheritt trusts endorse each paper. Same corpus, a different order for every researcher.

1. Genetic Programming: On the Programming of Computers by Means of Natural Selection
2. Wall-Adapting Local Eddy-Viscosity models for simulations in complex geometries
3. Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
4. A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship (Journal of Computational Physics)
5. Nonreflecting Zonal Characteristic Boundary Condition for Direct Numerical Simulation of Aerodynamic Sound
6. Turbulent Flows
7. Genetic Algorithms in Search
8. Direct numerical simulation of ‘short’ laminar separation bubbles with turbulent reattachment (Journal of Fluid Mechanics)
9. A paradigm for data-driven predictive modeling using field inversion and machine learning
10. Neural network modeling for near wall turbulent flow

Their papers

• A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship (2016) — 309 citations
• Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot (2018) — 46 citations