A Simulation-Based and Reliability-Based Design Framework for Floor-Isolation Protective Systems

2013 ◽  
Author(s):  
G. Jia ◽  
A.A. Taflanidis ◽  
I. Gidaris
Keyword(s):  
Design Framework ◽  
Reliability Based Design ◽  
Simulation Based ◽  
Floor Isolation ◽  
Protective Systems

scholarly journals A reliability-based design framework for early stages of design process

2017 ◽  
Vol 39 (6) ◽  
pp. 2105-2120 ◽  
Author(s):  
Murat Mayda ◽  
Seung-Kyum Choi
Keyword(s):  
Design Process ◽  
Design Framework ◽  
Early Stages ◽  
Reliability Based Design

Reliability-Based Analysis and Optimization of the Gravity Balancing Performance of Spring-Articulated Serial Robots with Uncertainties

2021 ◽  
pp. 1-32
Author(s):  
Vu Linh Nguyen ◽  
Chin-Hsing Kuo ◽  
Po Ting Lin
Keyword(s):  
Pso Algorithm ◽  
Reliability Based Design Optimization ◽  
Swarm Optimization ◽  
Reliability Based Design ◽  
Serial Robots ◽  
Simulation Based ◽  
Serial Robot ◽  
Simulation Results ◽  
Uncertainty Level

Abstract This article proposes a method for analyzing the gravity balancing reliability of spring-articulated serial robots with uncertainties. Gravity balancing reliability is defined as the probability that the torque reduction ratio (the ratio of the balanced torque to the unbalanced torque) is less than a specified threshold. The reliability analysis is performed by exploiting a Monte Carlo simulation (MCS) with consideration of the uncertainties in the link dimensions, masses, and compliance parameters. The gravity balancing begins with a simulation-based analysis of the gravitational torques of a typical serial robot. Based on the simulation results, a gravity balancing design for the robot using mechanical springs is realized. A reliability-based design optimization (RBDO) method is also developed to seek a reliable and robust design for maximized balancing performance under a prescribed uncertainty level. The RBDO is formulated with consideration of a probabilistic reliability constraint and solved by using a particle swarm optimization (PSO) algorithm. A numerical example is provided to illustrate the gravity balancing performance and reliability of a robot with uncertainties. A sensitivity analysis of the balancing design is also performed. Lastly, the effectiveness of the RBDO method is demonstrated through a case study in which the balancing performance and reliability of a robot with uncertainties are improved with the proposed method.

Development of a Reliability-Based Design Framework for Transmission Line Structure Foundations

2003 ◽  
Vol 129 (9) ◽  
pp. 798-806 ◽  
Author(s):  
Kok-Kwang Phoon ◽  
Fred H. Kulhawy ◽  
Mircea D. Grigoriu
Keyword(s):  
Transmission Line ◽  
Design Framework ◽  
Line Structure ◽  
Reliability Based Design

New simulation-based frameworks for multi-objective reliability-based design optimization of structures

2018 ◽  
Vol 62 ◽  
pp. 1-20 ◽  
Author(s):  
Naser Safaeian Hamzehkolaei ◽  
Mahmoud Miri ◽  
Mohsen Rashki
Keyword(s):  
Design Optimization ◽  
Reliability Based Design Optimization ◽  
Multi Objective ◽  
Reliability Based Design ◽  
Simulation Based

System RBDO With Correlated Variables Using Probabilistic Re-Analysis and Local Metamodels

2010 ◽  
Author(s):  
Ramon C. Kuczera ◽  
Zissimos P. Mourelatos ◽  
Efstratios Nikolaidis
Keyword(s):  
System Reliability ◽  
Random Variables ◽  
Trust Region ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Sensitivity Derivatives ◽  
Simulation Based ◽  
Gradient Based ◽  
Mc Simulation

A simulation-based, system reliability-based design optimization (RBDO) method is presented that can handle problems with multiple failure regions and correlated random variables. Copulas are used to represent dependence between random variables. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with a sequential trust-region optimization approach and local metamodels covering each trust region. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation per trust region. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing the use of a gradient-based optimizer. The PRRA method is based on importance sampling. One requirement for providing accurate results is that the support of the sampling PDF must contain the support of the joint PDF of the input random variables. The trust-region optimization approach satisfies this requirement. Local metamodels are constructed sequentially for each trust region taking advantage of the potential overlap of the trust regions. The metamodels are used to determine the value of the indicator function in MC simulation. An example with correlated input random variables demonstrates the accuracy and efficiency of the proposed RBDO method.

A Reliability-Based Design Method Using Simulation Techniques and Efficient Optimization Approach

2004 ◽  
Author(s):  
Tong Zou ◽  
Sankaran Mahadevan ◽  
Akhil Sopory
Keyword(s):  
Computational Cost ◽  
Nonlinear Problems ◽  
Side Impact ◽  
System Level ◽  
Optimization Approach ◽  
Sequential Approach ◽  
Model Based ◽  
Reliability Based Design ◽  
Reliability Method ◽  
Simulation Based

A novel reliability-based design optimization (RBDO) method using simulation-based techniques for reliability assessments and efficient optimization approach is presented in this paper. In RBDO, model-based reliability analysis needs to be performed to calculate the probability of not satisfying a reliability constraint and the gradient of this probability with respect to each design variable. Among model-based methods, the most widely used in RBDO is the first-order reliability method (FORM). However, FORM could be inaccurate for nonlinear problems and is not applicable for system reliability problems. This paper develops an efficient optimization methodology to perform RBDO using simulation-based techniques. By combining analytical and simulation-based reliability methods, accurate probability of failure and sensitivity information is obtained. The use of simulation also enables both component and system-level reliabilities to be included in RBDO formulation. Instead of using a traditional RBDO formulation in which optimization and reliability computations are nested, a sequential approach is developed to greatly reduce the computational cost. The efficiency of the proposed RBDO approach is enhanced by using a multi-modal adaptive importance sampling technique for simulation-based reliability assessment; and by treating the inactive reliability constraints properly in optimization. A vehicle side impact problem is used to demonstrate the capabilities of the proposed method.

A Simulation-Based RBDO Method Using Probabilistic Re-Analysis and a Trust Region Approach

2009 ◽  
Author(s):  
Ramon C. Kuczera ◽  
Zissimos P. Mourelatos ◽  
Efstratios Nikolaidis ◽  
Jing Li
Keyword(s):  
System Reliability ◽  
Combustion Engine ◽  
Trust Region ◽  
Optimization Approach ◽  
Reliability Based Design ◽  
Support Set ◽  
Sensitivity Derivatives ◽  
Simulation Based ◽  
Gradient Based ◽  
Mc Simulation

A simulation-based, system reliability-based design optimization (RBDO) method is presented which can handle problems with multiple failure regions. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with a trust-region optimization approach. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. The PRRA method is based on importance sampling. It provides accurate results, if the support (set of all values for which a function is non zero) of the sampling PDF contains the support of the joint PDF of the input random variables and, if the mass of the input joint PDF is not concentrated in a region where the sampling PDF is almost zero. A sequential, trust-region optimization approach satisfies these two requirements. The potential of the proposed method is demonstrated using the design of a vibration absorber, and the system RBDO of an internal combustion engine.

A Concept and Framework for a Shipyard Layout Design Based on Simulation

2009 ◽  
Vol 25 (03) ◽  
pp. 126-135
Author(s):  
Jong Gye Shin ◽  
Young Joo Song ◽  
Dong Kun Lee ◽  
Jong Hun Woo
Keyword(s):  
Computer Simulation ◽  
Design Process ◽  
Systems Engineering ◽  
Layout Design ◽  
Engineering Method ◽  
Design Framework ◽  
Planning Phase ◽  
Engineering Technique ◽  
Simulation Based ◽  
Framework Development

Recently, global shipbuilding companies have been increasing their productivity or expanding their shipyards to accommodate a large amount of orders. However, few studies have been carried out on shipyard layout designs. This research presents a simulation-based shipyard layout design framework to resolve the problems of the shipyard layout design. The shipyard layout design framework was developed on the basis of the systems engineering method. The disciplined systems engineering technique was guided by ISO/IEC 15288 during the planning phase of the shipyard layout design framework development. This framework suggests how to achieve an efficient and effective shipyard layout design that can satisfy the stakeholder of the layout design process. Furthermore, a method is recommended for how the proposed shipyard layout should be verified and validated using a computer simulation. It is expected that the framework will contribute not only to the improvement of the existing shipyard layout design but also to the construction of the new shipyard or ship-yard advancement.

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