scholarly journals Knowledge-Based Approach for System Level Electromagnetic Safety Analysis

2021 ◽  
Author(s):  
Lokesh Devaraj ◽  
Alastair R. Ruddle ◽  
Qazi Mashaal Khan ◽  
Alistair P. Duffy
Keyword(s):  
Safety Analysis ◽  
System Level ◽  
Knowledge Based

Introducing Knowledge-Based Engineering Into an Interconnected Product Development Process

1999 ◽  
Author(s):  
Daniel E. Whitney ◽  
Qi Dong ◽  
Jared Judson ◽  
Gregory Mascoli
Keyword(s):  
Development Process ◽  
Product Development Process ◽  
System Level ◽  
Knowledge Based ◽  
Design Structure ◽  
Engine Component ◽  
Level Information ◽  
Tightly Coupled ◽  
Knowledge Based Engineering ◽  
Knowledge Content

Abstract Recently, a large automobile company implemented a Knowledge-based Engineering (KBE) application to help design an engine component. While the KBE developers aimed to facilitate a single engineer’s ability to design this component using only the KBE application, it can be shown that in fact this component’s design is tightly coupled to that of several others. Can KBE handle situations like this? How common are they? To address these and other questions, Design Structure Matrix (DSM) models were made of this component at three levels: system interactions, assembly of the component, and individual parts. The size, row names, and internal entries of these matrices were compared to matrices constructed from several conventional written design guides and a flowchart of the KBE application. In each case, the DSM contained more rows or more matrix entries per row, especially at the system interaction level. Since the DSMs were constructed by interviewing experienced engineers, one implication is that while low-aggregation information may be documented, system level information at this company mostly resides in people’s heads. An informal measure of “knowledge content” based on the number of matrix entries per row was shown to be consistent with similar measurements made on DSMs obtained by several other researchers. These results indicate some of the scope and complexity challenges that KBE faces.

Component and System Life Distribution Prediction with Reliability Demonstration Implications for a Diesel Fuel Injector

2004 ◽  
Vol 47 (2) ◽  
pp. 15-24
Author(s):  
Dustin Aldridge
Keyword(s):  
Distribution System ◽  
Failure Criteria ◽  
System Level ◽  
Fuel Injector ◽  
Life Distribution ◽  
Knowledge Based ◽  
System Requirements ◽  
System Life ◽  
Manufacturing Variation

A vehicle case study is used to illustrate a methodology of analysis and testing to predict component and system reliability and durability. The methodology integrates customer usage data, component failure distribution, system failure criteria, manufacturing variation, and customer severity variation. Extending this methodology to the vehicle system level enables correlation between component and system requirements. Further, this analysis provides the basis to establish a knowledge-based test option for a successful test validation program to demonstrate reliability.

scholarly journals NFP: An R Package for Characterizing and Comparing of Annotated Biological Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-5
Author(s):  
Yang Cao ◽  
Wenjian Xu ◽  
Chao Niu ◽  
Xiaochen Bo ◽  
Fei Li
Keyword(s):  
Biological Networks ◽  
Biological Network ◽  
R Package ◽  
System Level ◽  
Application Development ◽  
Mathematical Concepts ◽  
Computational Framework ◽  
Knowledge Based ◽  
Different Types ◽  
Gene Regulatory

Large amounts of various biological networks exist for representing different types of interaction data, such as genetic, metabolic, gene regulatory, and protein-protein relationships. Recent approaches on biological network study are based on different mathematical concepts. It is necessary to construct a uniform framework to judge the functionality of biological networks. We recently introduced a knowledge-based computational framework that reliably characterized biological networks in system level. The method worked by making systematic comparisons to a set of well-studied “basic networks,” measuring both the functional and topological similarities. A biological network could be characterized as a spectrum-like vector consisting of similarities to basic networks. Here, to facilitate the application, development, and adoption of this framework, we present an R package called NFP. This package extends our previous pipeline, offering a powerful set of functions for Network Fingerprint analysis. The software shows great potential in biological network study. The open source NFP R package is freely available under the GNU General Public License v2.0 at CRAN along with the vignette.

Knowledge Based Qualification Methodology to Evaluate Shock Induced Risks in BGA Components

2017 ◽  
Author(s):  
Min Pei ◽  
Guru Arakere ◽  
Milena Vujosevic
Keyword(s):  
User Behavior ◽  
System Level ◽  
Special Focus ◽  
Detailed Knowledge ◽  
End User ◽  
Physics Of Failure ◽  
Knowledge Based ◽  
Test Board ◽  
Deformation Modes

This paper provides details of Knowledge Based Qualification (KBQ) methodology to calculate BGA component shock qualification requirements. The methodology is based on experimental, theoretical and computational approach used to generate a detailed knowledge of the use conditions and failure physics. Discussed are the steps taken to understand the end-user behavior and system design impact on dynamic load experienced by the component in the field. A special focus is placed on the understanding of the board deformation modes, their impact on BGA failures, and the physics-of-failure (PoF) metric that is not only accurate enough but also practical for everyday applications. Theoretical and computational modeling was used to perform the necessary “translations” from use condition to test conditions and from system level drop to test board component shock. These “translations” enabled by the PoF metric, directly lead to the determination of BGA shock qualification requirements.

Sensitivity and Uncertainty Information Incorporated Loss of Flow Accident Analyses for Research Reactors

2020 ◽  
Author(s):  
Tao Liu ◽  
Zeyun Wu
Keyword(s):  
Research Reactor ◽  
Safety Analysis ◽  
Primary Objective ◽  
Analysis Procedure ◽  
System Level ◽  
Normal Operation ◽  
Reactor Model ◽  
Research Reactors ◽  
Design Basis ◽  
Uncertainty Information

Abstract This paper outlines a system level safety analysis procedure for research reactors incorporating sensitivity and uncertainty components. The protected loss of flow (LOF) accident was selected as an exemplified design basis accident to demonstrate the analysis procedure. The conceptual NIST (National Institute of Standards and Technology) horizontally split-core based research reactor was adopted as a research reactor model in the study. Two system level dynamics codes, RELAP5-3D and PARET, were employed in this work in a comparison study manner. The primary objective of the present work is to demonstrate the analysis capability of integrating sensitivity and uncertainty information in addition to traditional predictions of the system code models for the study of the thermal-hydraulics (T/H) safety characteristics of research reactors under accidental transient scenarios. The canonical transient predictions on the LOF accident yielded from the two system codes mentioned above have demonstrated some noticeable yet acceptable discrepancies. To better understand the discrepancies observed in the simulations, sensitivity and uncertainty analyses were performed by coupling the RELAP5-3D model and the data analytic engines provided by the RAVEN framework developed by INL. The sensitivity information reveals the significances of key figure of merits such as the peak cladding temperature varies with different boundary and initial parameters in both normal operation and design basis transients. The uncertainty analysis informs the deviations of the responses contributed by the errors of various input components. Both the sensitivity and uncertainty information will be incorporated into a safety analysis framework as part of the safety characteristic predictions delivered by the framework.

scholarly journals Safety Analysis of AADL Models for Grid Cyber-Physical Systems via Model Checking of Stochastic Games

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 212 ◽  
Author(s):  
Xiaomin Wei ◽  
Yunwei Dong ◽  
Pengpeng Sun ◽  
Mingrui Xiao
Keyword(s):  
Model Checking ◽  
Stochastic Games ◽  
Safety Analysis ◽  
Cyber Physical Systems ◽  
System Level ◽  
Probabilistic Model Checking ◽  
Critical Systems ◽  
System Safety ◽  
Physical Systems ◽  
Analysis And Design

As safety-critical systems, grid cyber-physical systems (GCPSs) are required to ensure the safety of power-related systems. However, in many cases, GCPSs may be subject to uncertain and nondeterministic environmental hazards, as well as the variable quality of devices. They can cause failures and hazards in the whole system and may jeopardize system safety. Thus, it necessitates safety analysis for system safety assurance. This paper proposes an architecture-level safety analysis approach for GCPSs applying the probabilistic model-checking of stochastic games. GCPSs are modeled using Architecture Analysis and Design Language (AADL). Random errors and failures of a GCPS and nondeterministic environment behaviors are explicitly described with AADL annexes. A GCPS AADL model including the environment can be regarded as a game. To transform AADL models to stochastic multi-player games (SMGs) models, model transformation rules are proposed and the completeness and consistency of rules are proved. Property formulae are formulated for formal verification of GCPS SMG models, so that occurrence probabilities of failed states and hazards can be obtained for system-level safety analysis. Finally, a modified IEEE 9-bus system with grid elements that are power management systems is modeled and analyzed using the proposed approach.

scholarly journals System Level Design and Conception of a System-on-a-Chip (SoC) for Cognitive Robotics

2021 ◽  
Author(s):  
Diego Stéfano Fonseca Ferreira ◽  
Augusto Loureiro da Costa ◽  
Wagner Luiz Alves De Oliveira ◽  
Alejandro Rafael Garcia Ramirez
Keyword(s):  
Cognitive Model ◽  
Cognitive Robotics ◽  
System Level ◽  
System Level Design ◽  
Cognitive Level ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
System On A Chip ◽  
Level Design ◽  
Complex Knowledge

In this work, a system level design and conception of a System-on-a-Chip (SoC) for the execution of cognitive agents in robotics will be presented. The cognitive model of the Concurrent Autonomous Agent (CAA), which was already successfully applied in several robotics applications, is used as a reference for the development of the hardware architecture. This cognitive model comprises three levels that run concurrently, namely the reactive level (perception-action cycle that executes predefined behaviours), the instinctive level (receives goals from cognitive level and uses a knowledge based system for selecting behaviours in the reactive level) and the cognitive level (planning). For the development of such system level hardware model, the C++ library SystemC with Transaction Level Modelling (TLM) 2.0 will be used. A system model of a module that executes a knowledge based system is presented, followed by a system level description of a processor dedicated to the execution of the Graphplan planning algorithm. The buses interconnecting these modules are modelled by the TLM generic payload. Results from simulated experiments with complex knowledge bases for solving planning problems in different robotics contexts demonstrate the correctness of the proposed architecture. Finally, a discussion on performance gains takes place in the end.

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