PI: Prof. Nicholas Zabaras Participating student: Swagato Acharjee

1. E S D PDF of design Objective Input support space Fail Safe Design variables Engineering component Random Meso-Scale features Robust design and analysis of deformation processes PI: Prof. Nicholas Zabaras Participating student: Swagato Acharjee Materials Process Design and Control Laboratory, Cornell University http://mpdc.mae.cornell.edu Research Objectives: To develop a mathematically and computationally rigorous methodology for virtual materials process design that is based on quantified product quality and accounts for process targets and constraints with explicit consideration of uncertainty in the process. II – Uncertainty modeling in inelastic deformation processes I - Deterministic Design of Deformation Processes III– Ongoing work - Robust design with explicit consideration of uncertainty MOTIVATION - All physical systems have an inherent associated randomness Object oriented, parallel MPI based software for Lagrangian finite element analysis and design of 3D hyperelastic-viscoplastic metal forming processes. Implementation of 3D continuum sensitivity analysis algorithm. Mathematically rigorous computation of gradients - good convergence observed within few optimization iterations Advanced unstructured hexahedral remeshing using the meshing software CUBIT (Sandia). Thermomechanical deformation process design in the presence of ductile damage and dynamic recrystallization Multi-stage deformation process design PROBLEM STATEMENT Compute the predefined random process design parameters which lead to a desired objectives with acceptable (or specified) levels of uncertainty in the final product and satisfying all constraints. SOURCES OF UNCERTAINTIES • Uncertainties in process conditions • Input data • Model formulation • Material heterogeneity • Errors in simulation software UNCERTAINTY DUE TO MATERIAL HETEROGENEITY Uncertainty modeling in a tension test using Generalized Polynomial Chaos Expansions (GPCE). The input uncertainty is assumed in the state variable (deformation resistance) – a random heterogeneous parameter Schematic of the continuum sensitivity method (CSM) Discretize Design differentiate Continuum problem Contact & friction constraints Equilibrium equation Sensitivity weak form Design derivative of equilibrium equation Adaptive discretization of the PDF of the design objective based on Smooth (S) Extreme (E) and Discontinuous (D) regions Incremental sensitivity contact sub-problem Material constitutive laws • Robustness limits on the desired properties in the product – acceptable range of uncertainty. • Design in the presence of uncertainty/ not to reduce uncertainty. • Design variables are stochastic processes or random variables. • Design problem is a multi-objective and multi-constraint optimization problem. Incremental thermal sensitivity sub-problem Time & space discretized weak form Incremental sensitivity constitutive sub-problem Effect of heterogeneities at linear-nonlinear transition Random realizations Conservation of energy Preform Optimization of a Steering LInk NON INTRUSIVE STOCHASTIC GALERKIN (NISG) MODELING OF PROCESS UNCERTAINTY IN UPSETTING Reference problem Large Flash First iteration Underfill SELECTED PUBLICATIONS • S. Acharjee and N. Zabaras "The continuum sensitivity method for the computational design of three-dimensional deformation processes", Computer Methods in Applied Mechanics and Engineering, in press. • S. Acharjee and N. Zabaras, "Uncertainty propagation in finite deformation plasticity -- A spectral stochastic Lagrangian approach", Computer Methods in Applied Mechanics and Engineering, in press. • S. Acharjee and N. Zabaras, "A support-based stochastic Galerkin approach for modeling uncertainty propagation in deformation processes", Computers and Structures, submitted. • S. Acharjee and N. Zabaras, "A gradient optimization method for efficient design of three-dimensional deformation processes", NUMIFORM, Columbus, Ohio, 2004. • N. Zabaras and S. Acharjee, "An efficient sensitivity analysis for optimal 3D deformation process design", 2005 NSF Design, Service and Manufacturing Grantees Conference, Scottsdale, Arizona, 2005. • S. Acharjee and N. Zabaras "Modeling uncertainty propagation in large deformations", 8th US National Congress in Computational Mechanics, Austin, TX, 2005. • S. Acharjee and N. Zabaras, "On the analysis of finite deformations and continuum damage in materials with random properties", 3nd M.I.T. Conference on Computational Fluid and Solid Mechanics, Cambridge, MA, 2005. Final iteration – Flash reduced , no underfill Objective Function Uncertainty in die/workpiece friction and initial shape Financial support from NSF, AFOSR and ARO. Computing facilities provided by Cornell Theory Center