A Generative Human-in-the-Loop Approach for Conceptual Design Exploration Using Flow Failure Frequency in Functional Models1

2019 ◽  
Vol 19 (3) ◽  
Author(s):  
Ryan M. Arlitt ◽  
Douglas L. Van Bossuyt
Keyword(s):  
Risk Assessment ◽  
Conceptual Design ◽  
Electrical Power ◽  
Functional Model ◽  
Flow Distribution ◽  
Heat Extraction ◽  
System Failure ◽  
Electrical Power System ◽  
Human In The Loop ◽  
Functional Models

A challenge systems engineers and designers face when applying system failure risk assessment methods such as probabilistic risk assessment (PRA) during conceptual design is their reliance on historical data and behavioral models. This paper presents a framework for exploring a space of functional models using graph rewriting rules and a qualitative failure simulation framework that presents information in an intuitive manner for human-in-the-loop decision-making and human-guided design. An example is presented wherein a functional model of an electrical power system testbed is iteratively perturbed to generate alternatives. The alternative functional models suggest different approaches to mitigating an emergent system failure vulnerability in the electrical power system's heat extraction capability. A preferred functional model configuration that has a desirable failure flow distribution can then be identified. The method presented here helps systems designers to better understand where failures propagate through systems and guides modification of systems functional models to adjust the way in which systems fail to have more desirable characteristics.

Toward a Generative Human-in-the-Loop Approach for Conceptual Design Exploration Using Flow Failure Frequency in Functional Models

2018 ◽  
Author(s):  
Ryan M. Arlitt ◽  
Douglas L. Van Bossuyt
Keyword(s):  
Risk Assessment ◽  
Conceptual Design ◽  
Electrical Power ◽  
Functional Model ◽  
Flow Distribution ◽  
Heat Extraction ◽  
System Failure ◽  
Electrical Power System ◽  
Human In The Loop ◽  
Functional Models

A challenge systems engineers and designers face when applying system failure risk assessment methods such as Probabilistic Risk Assessment (PRA) during conceptual design is their reliance on historical data and behavioral models. This paper presents a framework for exploring a space of functional models using graph rewriting rules and a qualitative failure simulation framework that presents information in an intuitive manner for human-in-the-loop decision-making and human-guided design. An example is presented wherein a functional model of an electrical power system is iteratively perturbed to generate alternatives. The alternative functional models suggest different approaches to mitigating an emergent system failure vulnerability in the electrical power system’s the heat extraction capability. A preferred functional model configuration that has a desirable failure flow distribution can then be identified. The method presented here helps systems designers to better understand where failures propagate through systems and guides modification of systems functional models to adjust the way in which systems fail to have more desirable characteristics.

Safety-Informed Design: Using Cluster Analysis to Elicit Hazardous Emergent Failure Behavior in Complex Systems

2015 ◽  
Author(s):  
Matthew G. McIntire ◽  
Christopher Hoyle ◽  
Irem Y. Tumer ◽  
David C. Jensen
Keyword(s):  
Complex System ◽  
Hazard Analysis ◽  
Electrical Power ◽  
Functional Model ◽  
Hazard Identification ◽  
Emergent Behavior ◽  
Failure Behavior ◽  
Large Set ◽  
Electrical Power System ◽  
Engineered Systems

Identifying failure paths and potentially hazardous scenarios resulting from component faults and interactions is a challenge in the early design process. The inherent complexity present in large engineered systems leads to non-obvious emergent behavior, which may result in unforeseen hazards. Current hazard analysis techniques either focus on small slices of failure scenarios (fault trees and event trees), or lists of known hazards in the domain (hazard identification). Early in the design of a complex system, engineers may represent their system as a functional model. A function failure reasoning tool can then exhaustively simulate qualitative failure scenarios. Some scenarios will be identified as hazardous by hazard rules specified by the engineer, but the goal is to identify scenarios representing unknown hazards. A clustering method is applied repetitively to the large set of failure propagation results. Then, an algorithm identifies the scenario most likely to be hazardous, and presents it to the engineer. After viewing the scenario and judging its safety, the engineer may have insight to produce additional rules. The collaborative process of computer rating and human judgment will identify previously unknown hazards. The feasibility of this methodology is being tested on a relatively simple functional model of an electrical power system. Related work applying function failure reasoning to a team of robotic rovers will provide data from a more complex system.

A Theory for the Development of Conceptual Functional Models for Automation of Manual Processes

2007 ◽  
Author(s):  
Robert L. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Conceptual Design ◽  
Functional Model ◽  
Process Models ◽  
Functional Modeling ◽  
Functional Basis ◽  
Functional Models ◽  
Electromechanical Products ◽  
The Creation

Conceptual design is a vital stage in the development of any product, and its importance only increases with the complexity of a design. Functional modeling with the Functional Basis provides a framework for the conceptual design of electromechanical products. This framework is just as applicable to the conceptual design of automated solutions where an engineered product with components spanning multiple engineering domains is designed to replace or aid a human and his or her tools in a human-centric process. This paper presents research toward the simplification of the generation of conceptual functional models for automation solutions. The presented methodology involves the creation of functional and process models to fully explore existing human operated tasks for potential automation. Generated functional and process models are strategically combined to create a new conceptual functional model for an automation solution to potentially automate the human-centric task. The presented methodology is applied to the generation of a functional model for a conceptual automation solution. Then conceptual automation solutions generated through the presented methodology are compared to existing automation solutions to demonstrate the effectiveness of the presented methodology.

scholarly journals Safety-informed design: Using subgraph analysis to elicit hazardous emergent failure behavior in complex systems

2016 ◽  
Vol 30 (4) ◽  
pp. 466-473 ◽  
Author(s):  
Matthew G. McIntire ◽  
Christopher Hoyle ◽  
Irem Y. Tumer ◽  
David C. Jensen
Keyword(s):  
Complex System ◽  
Hazard Analysis ◽  
Electrical Power ◽  
Functional Model ◽  
Hazard Identification ◽  
Emergent Behavior ◽  
Failure Behavior ◽  
Electrical Power System ◽  
Graph Representations ◽  
Engineered Systems

AbstractIdentifying failure paths and potentially hazardous scenarios resulting from component faults and interactions is a challenge in the early design process. The inherent complexity present in large engineered systems leads to nonobvious emergent behavior, which may result in unforeseen hazards. Current hazard analysis techniques focus on single hazards (fault trees), single faults (event trees), or lists of known hazards in the domain (hazard identification). Early in the design of a complex system, engineers may represent their system as a functional model. A function failure reasoning tool can then exhaustively simulate qualitative failure scenarios. Some scenarios can be identified as hazardous by hazard rules specified by the engineer, but the goal is to identify scenarios representing unknown hazards. The incidences of specific subgraphs in graph representations of known hazardous scenarios are used to train a classifier to distinguish hazard from nonhazard. The algorithm identifies the scenario most likely to be hazardous, and presents it to the engineer. After viewing the scenario and judging its safety, the engineer may have insight to produce additional hazard rules. The collaborative process of strategic presentation of scenarios by the computer and human judgment will identify previously unknown hazards. The feasibility of this methodology has been tested on a relatively simple functional model of an electrical power system with positive results. Related work applying function failure reasoning to a team of robotic rovers will provide data from a more complex system.

Towards Rules for Functional Composition

2008 ◽  
Author(s):  
Benjamin W. Caldwell ◽  
Gregory M. Mocko
Keyword(s):  
Conceptual Design ◽  
Functional Model ◽  
Functional Composition ◽  
Functional Decomposition ◽  
Functional Basis ◽  
Functional Models ◽  
Hierarchical Levels ◽  
Unknown Solution

Functional decomposition is used in conceptual design to divide an overall problem with an unknown solution into smaller problems with known solutions. The procedure for functional decomposition, however, has not been formalized. In a larger effort to understand and develop rules for functional decomposition, this paper develops rules for composition of reverse-engineered functional models. First, the functional basis hierarchy is used in an attempt to compose the functional model of a hair dryer, which does not produce the desired results. Second, a set of rules for composition is presented and applied to the hair dryer functional model. This composed functional model is more similar to the desired decomposition result than the functional model developed by changing hierarchical levels. Ten additional functional models are also composed and the results shown. The findings demonstrate that composition rules can be developed empirically through analysis of functional models.

scholarly journals THE ALGORITHM FOR CORRECTING A MODE OF THE POWER SUPPLY SYSTEM THAT TAKES THE TRANSFORMATIONS AND HETEROGENEITY OF THE NETWORK INTO ACCOUNT

2017 ◽  
Vol 60 (6) ◽  
pp. 523-535
Author(s):  
O. I. Alexandrov
Keyword(s):  
Power Supply ◽  
Power Supply System ◽  
Equations Of State ◽  
Electrical Power ◽  
Flow Distribution ◽  
Supply System ◽  
Electrical Network ◽  
Electrical Power System ◽  
Method Of Calculation ◽  
Generalized Parameters

The problem of expeditious correction has great practical value for operation of the power supply system and is one of the most important and complex challenges of an automated control system of an electrical power system. Its complexity is due to the dynamics and nonlinearity of equations of state of an electrical network, recorded as related to node voltages, and also due to multiply connected network elements. Attempts to solve the problem by using the theory of sensitivity lead to the appearance – in addition to the matrices of the generalized parameters of the network – of several sensitivity matrices, for the formation of which sufficiently effective algorithms for fast recalculation of the matrices when switching schemes are not yet developed. It results in a need to calculate matrix data anew at each switching, or to recognizing some mode as a basic one considering other modes virtually unchanged at relatively small deviations of the parameters, which, in its turn, leads to additional errors. The new method of calculation of the power flows distribution in the network is proposed that based is not on physical modeling of the structure of the investigated circuit, but on the mathematical modeling of the structure of the equations describing the flow distribution, thereby removing the limitations imposed by heterogeneity and the presence of transformations.

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