Adaptive Reduced Basis Methods For Multiscale Problems And Large Scale Pde Constrained Optimization

Adaptive Reduced Basis Methods for Multiscale Problems and Large-scale PDE-constrained Optimization

Real-time PDE-constrained Optimization

Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs--and the requirement for rapid solution--pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics. Audience: readers who have expertise in simulation and are interested in incorporating optimization into their simulations, who have expertise in numerical optimization and are interested in adapting optimization methods to the class of infinite-dimensional simulation problems, or who have worked in "offline" optimization contexts and are interested in moving to "online" optimization.

Large-Scale Scientific Computations

This book constitutes the refereed proceedings of the 14th International Conference on Large-Scale Scientific Computations, LSSC 2023, held in Sozopol, Bulgaria, during June 5–9, 2023. The 49 full papers included in this book were carefully reviewed and selected from 61 submissions. They were organized in topical sections as follows: preconditioning and multilevel methods; fractures and mixed dimensional modeling: discretizations, solvers, and methodology; machine learning and model order reduction for large scale predictive simulations; fractional differential problems: theoretical aspects, algorithms and applications; variational analysis and optimal control; stochastic optimal control and numerical methods in economics and finance; tensor methods for big data analytics and low-rank approximations of PDEs solutions; applications of metaheuristics to large-scale problems; large-scale models: numerical methods, parallel computations and applications; HPC and HPDA: algorithms and applications.