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Tushar Goel

from Short Hills, NJ
Age ~45
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Related to:
Bhawna Goel
Connected to:
Aakriti Goel, 34Aditya Goel, 37Akhilesh K Goel, 62Amrit L Goel, 86Anoop S Goel, 66Anu Goel, 51Anukul Goel, 46Anvita Goel, 45Ashvin Goel, 54Ashwani K Goel, 46

Tushar Goel Phones & Addresses

  • 806 Morris Tpke APT 3B, Short Hills, NJ 07078
  • New York, NY
  • 4380 La Mirage, Pensacola, FL 32504
  • Livermore, CA
  • Gainesville, FL

Publications

Us Patents

Topology Optimization For Designing Engineering Product

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US Patent:
8126684, Feb 28, 2012
Filed:
Apr 10, 2009
Appl. No.:
12/422149
Inventors:
Tushar Goel - Livermore CA, US
Willem J. Roux - Livermore CA, US
Assignee:
Livermore Software Technology Corporation - Livermore CA
International Classification:
G06F 17/50
US Classification:
703 1
Abstract:
Improved topology optimization for engineering product design is disclosed. An engineering product including a design domain to be optimized is defined. Design domain can be a portion or the entire engineering product. Design objective and optional constraint are defined such that optimization goal is achieved. Additionally, initial configuration of the design domain is represented by a finite element analysis (FEA) mesh. Each element or element group is associated with a design variable. A set of discrete material models is created from the baseline material used for the design domain. The set of discrete material models is configured to cover entire range of the design variable and each discrete material model represents a non-overlapping portion. Each element representing the design domain is associated with an appropriate discrete material model according to the design variable. Structure response is obtained via FEA to evaluate design objective and update design variable.

Neighborhood Determination Methods And Systems In Computer Aided Engineering Analysis

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US Patent:
8165856, Apr 24, 2012
Filed:
Jul 6, 2009
Appl. No.:
12/498180
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
Livermore Software Technology Corporation - Livermore CA
International Classification:
G06F 7/60
G06F 17/10
US Classification:
703 2
Abstract:
Improved methods and systems for a neighborhood determination in computer aided engineering analysis are disclosed. According to one aspect, a list of neighbor elements is created for a base element of a grid model representing a structure or an engineering product. The representative node's coordinates of the base element are calculated using corner nodes of the base element. A characteristic length is assigned to the base element. The characteristic length can be determined by users of the computer aided analysis, or be calculated using geometry of the base element. The characteristic length and the representative node collectively define a surface boundary that divides elements in the grid model into two groups. The first group contains potential neighbors, while the second group contains non-neighbors. Only elements in the first group are further processed using traditional procedures to determine whether each of them is indeed a neighbor element according to one of the neighborhood determination criteria.

Multi-Objective Evolutionary Algorithm Based Engineering Design Optimization

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US Patent:
7996344, Aug 9, 2011
Filed:
Mar 8, 2010
Appl. No.:
12/719764
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
Livermore Software Technology Corporation - Livermore CA
International Classification:
G06N 3/12
US Classification:
706 13
Abstract:
Systems and methods of obtaining a set of better converged and diversified Pareto optimal solutions in an engineering design optimization of a product (e. g. , automobile, cellular phone, etc. ) are disclosed. According to one aspect, a plurality of MOEA based engineering optimizations of a product is conducted independently. Each of the independently conducted optimizations differs from others with parameters such as initial generation and/or evolutionary algorithm. For example, populations (design alternatives) of initial generation can be created randomly from different seed of a random or pseudo-random number generator. In another, each optimization employs a particular revolutionary algorithm including, but not limited to, Nondominated Sorting Genetic Algorithm (NSGA-II), strength Pareto evolutionary algorithm (SPEA), etc. Furthermore, each independently conducted optimization's Pareto optimal solutions are combined to create a set of better converged and diversified solutions. Combinations can be performed at one or more predefined checkpoints during evolution process of the optimization.

Systems And Methods Of Constructing Radial Basis Function (Rbf) Based Meta-Models Used In Engineering Design Optimization

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US Patent:
20090248368, Oct 1, 2009
Filed:
Mar 26, 2008
Appl. No.:
12/056155
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
LIVERMORE SOFTWARE TECHNOLOGY CORPORATION - Livermore CA
International Classification:
G06F 17/50
G06F 17/11
US Classification:
703 1
Abstract:
Systems and methods of consuming radial basis function (RBF) based meta-models are described. In one aspect, a product is to be designed and optimized with a set of design variables, objectives and constraints. A number of design of experimentals (DOE) points are identified. Each of the DOE points represents a particular or unique combination of design variables. Computer-aided engineering (CAE) analysis/analyses is/are then performed for each of the DOE points. A RBF based meta-model is created to approximate the CAE analysis results at all of the DOE points. A crowding distance is calculated for each DOE point. The DOE points are sorted accordingly in a predetermined criterion such as descending order, from which a predefined number of the DOE points are chosen as RBF neuron centers. RBF parameters such as function type, width and weight factor are adjusted so that the meta-model can substantially match the CAE analysis results.

Sampling Strategy Using Genetic Algorithms In Engineering Design Optimization

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US Patent:
20090319453, Dec 24, 2009
Filed:
Jun 24, 2008
Appl. No.:
12/145339
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
Livermore Software Technology Corporation - Livermore CA
International Classification:
G06N 3/12
US Classification:
706 13
Abstract:
A sampling strategy using genetic algorithms (GA) in engineering design optimization is disclosed. A product is to design and optimize with a set of design variables, objectives and constraints. A suitable number of design of experiments (DOE) samples is then identified such that each point represents a particular or unique combination of design variables. The sample selection strategy is based on genetic algorithms. Computer-aided engineering (CAE) analysis or analyses (e.g., finite element analysis, finite difference analysis, mesh-free analysis, etc.) is/are performed for each of the samples during the GA based sample selection procedure. A meta-model is created to approximate the CAE analysis results at all of the DOE samples. Once the meta-model is satisfactory (e.g., accuracy within a tolerance), an optimized “best” design can be found by using the meta-model as function evaluator for the optimization method. Finally, a CAE analysis is performed to verify the optimized “best” design.

Methods And Systems For Multi-Objective Evolutionary Algorithm Based Engineering Desgin Optimization

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US Patent:
20110078100, Mar 31, 2011
Filed:
Feb 9, 2010
Appl. No.:
12/702939
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
LIVERMORE SOFTWARE TECHNOLOGY CORPORATION - Livermore CA
International Classification:
G06N 3/12
US Classification:
706 13
Abstract:
The present invention discloses systems and methods of conducting multi-objective evolutionary algorithm (MOEA) based engineering design optimization of a product (e.g., automobile, cellular phone, etc.). Particularly, the present invention discloses an archive configured for monitoring the progress and characterizing the performance of the MOEA based optimization. Further, an optimization performance indicator is created using the archive's update history. The optimization performance indicator is used as a metric of the current state of the optimization. Finally, a stopping or termination criterion for the MOEA based optimization is determined using a measurement derived from the optimization performance indicators. For example, a confirmation of a “knee” formation has developed in the optimization performance indicators. The optimization performance indicators include, but are not limited to, consolidation ratio, improvement ratio, hypervolume.

Identification Of Most Influential Design Variables In Engineering Design Optimization

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US Patent:
20110251711, Oct 13, 2011
Filed:
Apr 13, 2010
Appl. No.:
12/759594
Inventors:
Tushar Goel - Livermore CA, US
Assignee:
LIVERMORE SOFTWARE TECHNOLOGY CORPORATION - Livermore CA
International Classification:
G06F 17/50
G06F 3/048
US Classification:
700104, 715833
Abstract:
A method of identifying most influential design variables in a multi-objective engineering design optimization of a product is disclosed. According to one aspect of the present invention, a product is optimized with a set of design variables and a set of response functions as objectives and constraints. Representative product design alternatives (samples) are chosen from the design space and evaluated for responses. Metamodels are then used for fitting the sample responses to facilitate a global sensitivity analysis of all design variables versus the response functions. A graphical presentation tool is configured for allowing the user to conduct “what-if” scenarios by interactively applying respective weight factors to response functions to facilitate identification of most influential design variables. Engineering design optimization is then conducted in a reduced design space defined by the most influential design variables.
Control profile
Tushar Goel from Short Hills, NJ, age ~45 Get Report