Machine-learning and digital-twins for rapid evaluation and design of injected vaccine immune-system responses
From MaRDI portal
Publication:2083207
DOI10.1016/J.CMA.2022.115315OpenAlexW4285402675MaRDI QIDQ2083207
Publication date: 10 October 2022
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cma.2022.115315
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Perspectives on biological growth and remodeling
- Simulation of coupled microscale multiphysical-fields in particulate-doped dielectrics with staggered adaptive FDTD
- Computation of strongly coupled multifield interaction in particle-fluid systems
- On consistency, stability and convergence of staggered solution procedures
- Modeling and simulation of a class of coupled thermo-chemo-mechanical processes in multiphase solids.
- Special issue. Genetic and evolutionary computation
- A digital twin framework for machine learning optimization of aerial fire fighting and pilot safety
- A digital-twin and machine-learning framework for precise heat and energy management of data-centers
- A machine-learning framework for rapid adaptive digital-twin based fire-propagation simulation in complex environments
- \textit{The game of drones:} rapid agent-based machine-learning models for multi-UAV path planning
- A digital-twin and machine-learning framework for the design of multiobjective agrophotovoltaic solar farms
- A partitioned solution procedure for geothermal reservoir analysis
- Unconditionally stable staggered solution procedure for soil-pore fluid interaction problems
- An adaptive-recursive staggering strategy for simulating multifield coupled processes in microheterogeneous solids
- A frontal solver tuned for fully coupled non-linear hygro-thermo-mechanical problems
- Review Paper: Continuum biomechanics of soft biological tissues
- A Finite Element Primer for Beginners
This page was built for publication: Machine-learning and digital-twins for rapid evaluation and design of injected vaccine immune-system responses
