9783843379793 - Optimal Design of Meso-structured Materials under Uncertainty: Reliability Based Topology Optimization (RBTO) based method for design of meso-structures de Patel, J... (7 resultados)

Paperback. Condición: Brand New. 112 pages. 8.66x5.91x0.26 inches. In Stock.

Taschenbuch. Condición: Neu. Optimal Design of Meso-structured Materials under Uncertainty | Reliability Based Topology Optimization (RBTO) based method for design of meso-structures | Jiten Patel | Taschenbuch | 112 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843379793 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The main objective of the topology optimization is to fulfill the objective function with the minimum amount of material. This reduces the overall cost of the structure and at the same time reduces the assembly, manufacturing and maintenance costs because of the reduced number of parts in the final structure. The concept of reliability analysis can be incorporated into the deterministic topology optimization method; this incorporated scheme is referred to as Reliability-based Topology Optimization (RBTO). This book explores a reliability-based synthesis method which estimates all the statistical parameters and finds the optimum while being less computationally intensive. The efficiency of the proposed method is achieved with the combination of topology optimization and stochastic approximation which utilizes a sampling technique such as Latin Hypercube Sampling (LHS) and metamodeling techniques such as Local Regression and Classification using Artificial Neural Networks (ANN). 112 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Patel JitenJiten Patel graduated with a BTech degree in Mechanical Engineering from the Indian Institute of Technology (IIT) Madras in 2007. In 2009 he graduated with a MS degree in Mechanical Engineering from Georgia Institute of .

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The main objective of the topology optimization is to fulfill the objective function with the minimum amount of material. This reduces the overall cost of the structure and at the same time reduces the assembly, manufacturing and maintenance costs because of the reduced number of parts in the final structure. The concept of reliability analysis can be incorporated into the deterministic topology optimization method; this incorporated scheme is referred to as Reliability-based Topology Optimization (RBTO). This book explores a reliability-based synthesis method which estimates all the statistical parameters and finds the optimum while being less computationally intensive. The efficiency of the proposed method is achieved with the combination of topology optimization and stochastic approximation which utilizes a sampling technique such as Latin Hypercube Sampling (LHS) and metamodeling techniques such as Local Regression and Classification using Artificial Neural Networks (ANN).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The main objective of the topology optimization is to fulfill the objective function with the minimum amount of material. This reduces the overall cost of the structure and at the same time reduces the assembly, manufacturing and maintenance costs because of the reduced number of parts in the final structure. The concept of reliability analysis can be incorporated into the deterministic topology optimization method; this incorporated scheme is referred to as Reliability-based Topology Optimization (RBTO). This book explores a reliability-based synthesis method which estimates all the statistical parameters and finds the optimum while being less computationally intensive. The efficiency of the proposed method is achieved with the combination of topology optimization and stochastic approximation which utilizes a sampling technique such as Latin Hypercube Sampling (LHS) and metamodeling techniques such as Local Regression and Classification using Artificial Neural Networks (ANN).