scholarly journals Methodology Development for Passive Component Reliability Modeling in a Multi-Physics Simulation Environment

2015 ◽  
Author(s):  
Tunc Aldemir ◽  
Richard Denning ◽  
Umit Catalyurek ◽  
Stephen Unwin
Keyword(s):  
Passive Component ◽  
Simulation Environment ◽  
Reliability Modeling ◽  
Component Reliability ◽  
Methodology Development ◽  
Physics Simulation

Degradation Susceptibility Metrics as the Bases for Bayesian Reliability Models of Aging Passive Components and Long-Term Reactor Risk

2011 ◽  
Author(s):  
Stephen D. Unwin ◽  
Peter P. Lowry ◽  
Michael Y. Toyooka ◽  
Benjamin E. Ford
Keyword(s):  
Passive Component ◽  
Degradation Mechanisms ◽  
Component Reliability ◽  
Passive Components ◽  
Reliability Models ◽  
Age Dependent ◽  
Probabilistic Risk Assessments ◽  
Component Failure Rates ◽  
Service Data

Conventional probabilistic risk assessments (PRAs) are not well-suited to addressing long-term reactor operations. Since passive structures, systems and components are among those for which refurbishment or replacement can be least practical, they might be expected to contribute increasingly to risk in an aging plant. Yet, passives receive limited treatment in PRAs. Furthermore, PRAs produce only snapshots of risk based on the assumption of time-independent component failure rates. This assumption is unlikely to be valid in aging systems. The treatment of aging passive components in PRA does present challenges. First, service data required to quantify component reliability models are sparse, and this problem is exacerbated by the greater data demands of age-dependent reliability models. A compounding factor is that there can be numerous potential degradation mechanisms associated with the materials, design, and operating environment of a given component. This deepens the data problem since the risk-informed management of materials degradation and component aging will demand an understanding of the long-term risk significance of individual degradation mechanisms. In this paper we describe a Bayesian methodology that integrates the metrics of materials degradation susceptibility being developed under the Nuclear Regulatory Commission’s Proactive Materials Degradation Assessment Program with available plant service data to estimate age-dependent passive component reliabilities. Integration of these models into conventional PRA will provide a basis for materials degradation management informed by the predicted long-term operational risk.

scholarly journals Reliability Modeling and Assessment of Component with Multiple Weak Sites under Complex Loading

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Wenxue Qian ◽  
Xiaowei Yin ◽  
Liyang Xie
Keyword(s):  
Static Loading ◽  
Safety Margin ◽  
Complex Loading ◽  
The Other ◽  
Reliability Model ◽  
Reliability Modeling ◽  
Component Reliability ◽  
Reliability Design ◽  
Practical Engineering ◽  
Weak Site

A component with multiple weak sites is widely used in practical engineering and the existence of multiple weak sites can significantly decrease the component reliability. On the other hand, only a few components bear static loading and most components bear dynamic loading. In this paper, a reliability model of isomorphic component with multiple weak sites is built based on an order statistics model and the influences of strength decentrality and loading decentrality on isomorphic component with multiple weak sites are discussed. Furthermore the influence of loading times is studied in detail. The results show that unlike a component with only one weak site, not only does the failure of a component with multiple weak sites have a relationship with the safety margin, but there also exist relationships with the number of weak sites, the loading roughness, and loading times. The work in this paper is of some guiding significance in reliability design and assessment of a component with multiple weak sites under complex loading.

Physics Simulation Environment for Swarms of Self-Assembly Autonomous Robots

2004 ◽  
Vol 37 (14) ◽  
pp. 79-84
Author(s):  
Giovanni Cosimo Pettinaro ◽  
Ivo Widjaja Kwee ◽  
Luca Maria Gambardella
Keyword(s):  
Self Assembly ◽  
Autonomous Robots ◽  
Simulation Environment ◽  
Physics Simulation

scholarly journals An In-Memory Physics Environment as a World Model for Robot Motion Planning

2020 ◽  
Author(s):  
Navin K Ipe
Keyword(s):  
Motion Planning ◽  
Computational Intelligence ◽  
Fitness Landscape ◽  
Mental Simulation ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Simulation Environment ◽  
World Model ◽  
Simulated Environment ◽  
Physics Simulation

This paper investigates the possibility of utilizing a physics simulation environment as the imagination of a robot, where it creates a replica of the detected terrain in a physics simulation environment in its memory, and “imagines” a simulated version of itself in that memory, performing actions and navigation on the terrain. The physics of the environment simulates the movement of robot parts and its interaction with the objects in the environment and the terrain, thus avoiding the need for explicitly programming many calculations. The robot chooses the best possible action from multiple simulations of movement, and executes it in the real world. Moreover, as the complexity of motion increases with each degree of freedom of the robot’s joints, this paper also explores the utility of uniform pseudo-randomness to explore the fitness landscape of robot motility, and compares it with Computational Intelligence algorithms. Such techniques could potentially simplify the algorithmic complexity of programming multi-jointed robots, and also be capable of dynamically adjusting the “mental” simulation of the robot when it encounters environments with different gravity, viscosity or traction, merely by adjusting parameters of the simulated environment.

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