Optimization-based Design for Manufacturing
This report provides detailed documentation of the algorithms that where developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.
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Jump to search filtersAlgorithms Developed and Implemented in the Plato Software for Optimization-based Design for Manufacturing
This report provides detailed documentation of the algorithms that were developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.
Optimization-based design for additive manufacturing
Abstract not provided.
PLATO: Optimization-Based Design Ecosystem
Abstract not provided.
Optimization-based design for manufacturing
Abstract not provided.
Optimization-based design: A Forward-looking Perspective
Abstract not provided.
PLATO Training Course
Abstract not provided.
Alexa: Fast Shock Hydrodynamics on GPUs
Abstract not provided.
GPU Accelerated Topology Optimization with Plato/Alexa
Abstract not provided.
Accelerating Multidisciplinary Design Optimization with Machine Learning
Abstract not provided.
Additive manufacturing: Toward holistic design
Scripta Materialia
Additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.
SNL ATDM Analysis Components
Abstract not provided.
?PLATO? Environment for Designing with Topology Optimization
Abstract not provided.
PLATO Platinum Topology Optimization
Abstract not provided.
Designing with Topology Optimization
Abstract not provided.
Topology Optimzation for Next-Generation Design
Abstract not provided.
Considering DIC Uncertainties in Material Property Identification Using VFM
Abstract not provided.
Inverse Source and Material Identification in Sierra-SD
Abstract not provided.
Optimality conditions for the numerical solution of optimization problems with PDE constraints: Theoretical framework and applications to parameter identification and optimal control problems
A theoretical framework for the numerical solution of partial differential equation (PDE) constrained optimization problems is presented in this report. This theoretical framework embodies the fundamental infrastructure required to efficiently implement and solve this class of problems. Detail derivations of the optimality conditions required to accurately solve several parameter identification and optimal control problems are also provided in this report. This will allow the reader to further understand how the theoretical abstraction presented in this report translates to the application.
Inverse Structural Acoustic Source and Material Identification in a Massively Parallel Finite Element Framework
Abstract not provided.
Solving massive-scale inverse problems using matrix-fre dequential quadratic programming (SQP) methods
Abstract not provided.
Inverse Structural Acoustic Source and Material Identification in a Massively Parallel Finite Element Framework
Abstract not provided.
Efficient Handling of Inequality Constraints in a Matrix-Free Trust-Region SQP Algorithm
Abstract not provided.
Solving Large-Scale Inverse Problems in Elasticity Using Sequential Quadratic Programming (SQP)
Abstract not provided.
Numerical study of a matrix-free trust-region SQP method for equality constrained optimization
This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' in which we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).
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