Constraint Reasoning in Concurrent Design

1990 ◽  
Author(s):  
James R. Rinderle ◽  
V. Krishnan
Keyword(s):  
Life Cycle ◽  
Constraint Satisfaction ◽  
Design Space ◽  
Design Solution ◽  
Concurrent Design ◽  
Design Consideration ◽  
Simultaneous Treatment ◽  
Critical Design ◽  
Constraint Reasoning ◽  
Fan Blade

Abstract One paradigm of concurrent design is based on the simultaneous consideration of a broad range of life-cycle constraints including those arising from function, manufacturing and maintenance. This simultaneous treatment of life-cycle issues results in a multitude of constraints, which not only increase the complexity of finding a design solution, but also make it difficult to understand the trends and interactions underlying the design. It is our goal to enhance the designer’s ability to identify and discriminate those constraints that critically impact the design from those that are irrelevant. We propose an interval analysis based approach, which is augmented with monotonicity and dominance principles. The approach helps in identifying regions of the design space where constraints possess certain desirable properties. It also enables reasoning with constraints in these regions. The regional inferences can then be reassembled to obtain global results. These ideas have been applied in the concurrent design of a fan blade, to identify the dominant, active and redundant constraints, enabling the designer to more clearly perceive and base his decisions on the critical design consideration. Furthermore, the identification of dominant constraints permits the easy evaluation of the significance of newly asserted constraints and frequently facilitates the automatic formulation of noniterative constraint satisfaction methods which guarantee a globally optimal design.

Quiescence in Internal Propagation

1991 ◽  
Author(s):  
Sanjay E. Sarma ◽  
James R. Rinderle
Keyword(s):  
Mathematical Optimization ◽  
Constraint Propagation ◽  
Design Solution ◽  
Design Parameters ◽  
Concurrent Design ◽  
Quiescent State ◽  
Slow Process ◽  
Trade Offs ◽  
Constraint Reasoning ◽  
Speed And Accuracy

Abstract Concurrent design often involves a large number of variables related through a complex network of constraints. This not only makes it difficult to find a design solution, but also to understand the design parameter trade-offs, trends and interactions. Precise estimates of all the design parameters which would facilitate the exploration of tradeoffs and interactions are generally not available, however, the allowable ranges or intervals of some design parameters are often known. Narrower, or more refined intervals, facilitate the inference of stronger conclusions and the more robust application of mathematical optimization and constraint reasoning tools. Refinement of intervals can be carried out conveniently by constraint propagation, however, direct constraint propagation is often a computationally slow process. In this paper we study constraint propagation at a fundamental level and identify certain properties of the process. We then propose an alternative method in which these properties are utilized to increase considerably the speed and accuracy with which the final quiescent state of constraint propagation can be computed.

Searching Feasible Design Space by Solving Quantified Constraint Satisfaction Problems

2013 ◽  
Vol 136 (3) ◽  
Author(s):  
Jie Hu ◽  
Masoumeh Aminzadeh ◽  
Yan Wang
Keyword(s):  
Monte Carlo ◽  
Constraint Satisfaction ◽  
Design Space ◽  
Constraint Satisfaction Problem ◽  
Constraint Satisfaction Problems ◽  
Design Solution ◽  
New Approach ◽  
Solution Sets ◽  
Branch And Prune Algorithm ◽  
Branch And Prune

In complex systems design, multidisciplinary constraints are imposed by stakeholders. Engineers need to search feasible design space for a given problem before searching for the optimum design solution. Searching feasible design space can be modeled as a constraint satisfaction problem (CSP). By introducing logical quantifiers, CSP is extended to quantified constraint satisfaction problem (QCSP) so that more semantics and design intent can be captured. This paper presents a new approach to formulate searching design problems as QCSPs in a continuous design space based on generalized interval, and to numerically solve them for feasible solution sets, where the lower and upper bounds of design variables are specified. The approach includes two major components. One is a semantic analysis which evaluates the logic relationship of variables in generalized interval constraints based on Kaucher arithmetic, and the other is a branch-and-prune algorithm that takes advantage of the logic interpretation. The new approach is generic and can be applied to the case when variables occur multiple times, which is not available in other QCSP solving methods. A hybrid stratified Monte Carlo method that combines interval arithmetic with Monte Carlo sampling is also developed to verify the correctness of the QCSP solution sets obtained by the branch-and-prune algorithm.

scholarly journals A rapid design space exploration approach for multi-objective optimization of DSP filter designs

2021 ◽  
Author(s):  
Aakriti Tarun Sharma
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Systems Design ◽  
Design Solution ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Time Period ◽  
And Performance ◽  
High Level

The process of converting a behavioral specification of an application to its equivalent system architecture is referred to as High Level-Synthesis (HLS). A crucial stage in embedded systems design involves finding the trade off between resource utilization and performance. An exhaustive search would yield the required results, but would take a huge amount of time to arrive at the solution even for smaller designs. This would result in a high time complexity. We employ the use of Design Space Exploration (DSE) in order to reduce the complexity of the design space and to reach the desired results in less time. In reality, there are multiple constraints defined by the user that need to be satisfied simultaneously. Thus, the nature of the task at hand is referred to as Multi-Objective Optimization. In this thesis, the design process of DSP benchmarks was analyzed based on user defined constraints such as power and execution time. The analyzed outcome was compared with the existing approaches in DSE and an optimal design solution was derived in a shorter time period.

Qualitative Evaluation of Engineering Designs Using Fuzzy Logic

1996 ◽  
Author(s):  
Rajkumar Roy ◽  
Ian C. Parmee ◽  
Graham Purchase
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Engineering Design ◽  
Evaluation System ◽  
Design Space ◽  
Qualitative Evaluation ◽  
Fuzzy Rules ◽  
Design Solution ◽  
Fuzzy Expert System ◽  
Adaptive Search

Abstract The paper describes a Qualitative Evaluation System developed using a fuzzy expert system. The evaluation system gives a qualitative rating to design solutions by considering manufacturability aspects, choice of materials and some special preferences. The information is used in decision support for engineering design. The system is an integrated part of a decision support tool for engineering design called the ‘Adaptive Search Manager’ (ASM). ASM uses an adaptive search technique to identify multiple design solutions for a 12 dimensional Turbine Blade Cooling System design problem. Thus the task has been to develop a fuzzy expert system that can qualitatively evaluate any design solution from a design space using a realistically small number of fuzzy rules. The developed system utilises a knowledge separation and then a knowledge integration technique. The design knowledge is first separated into three categories: inter variable knowledge, intra variable knowledge and heuristics. Inter variable knowledge and intra variable knowledge are integrated using a concept of “compromise”. The qualitative evaluation system can evaluate any design solution within the 12 dimensional design space, but uses only 44 fuzzy rules and one function that implements the inter variable knowledge.

Web-Based Distributed System and Database Modeling for Concurrent Design

2001 ◽  
Author(s):  
D. Xue ◽  
Y. Xu
Keyword(s):  
Life Cycle ◽  
Concurrent Design ◽  
Product Modeling ◽  
Web Based ◽  
Database Modeling ◽  
New Class ◽  
Local Site ◽  
Development Life Cycle ◽  
Modeling Systems ◽  
Design Activities

Abstract This research introduces a new approach for web-based collaborative concurrent design. In this approach, systems, product libraries, and product databases for modeling different product development life-cycle aspects are distributed at different locations that are linked through the web. Product modeling libraries and databases are described by class features and instance features. Product modeling systems are used for manipulating design activities. A class feature at a remote location can be used for defining a new class feature at the local site. A system at one location can be implemented using the systems at other locations as the components. Distributed life-cycle databases are associated by their relations.

scholarly journals An Automated Procedure for Assessing Local Reliability Index and Life-Cycle Cost of Alternative Girder Bridge Design Solutions

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Ilaria Venanzi ◽  
Riccardo Castellani ◽  
Laura Ierimonti ◽  
Filippo Ubertini
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Design Solution ◽  
Bridge Design ◽  
Limit States ◽  
Technical Standards ◽  
Local Character ◽  
Repair Costs ◽  
Design Solutions ◽  
Girder Bridge

Stakeholders of civil infrastructures have to usually choose among several design alternatives in order to select a final design representing the best trade-off between safety and economy, in a life-cycle perspective. In this framework, the paper proposes an automated procedure for the estimation of life-cycle repair costs of different bridge design solutions. The procedure provides the levels of safety locally guaranteed by the selected design solution and the related total life-cycle cost. The method is based on the finite element modeling of the bridge and uses design traffic models as suggested by international technical standards. Both the global behavior and the transversal cross section of the bridge are analyzed in order to provide local reliability indexes. Several parameters involved in the design, such as geometry and loads and materials’ characteristics, are considered as uncertain. Degradation models are adopted for steel carpentry and rebars. The application of the procedure to a road bridge case study shows its potential in providing local safety levels for different limit states over the entire lifetime of the bridge and the life-cycle cost of the infrastructure, highlighting the importance of the local character of the life-cycle cost analysis.

A System Framework With Online Monitoring and Evaluation for Design Evolution of Engineering Systems

2010 ◽  
Vol 10 (3) ◽  
Author(s):  
L. B. Gamage ◽  
C. W. de Silva
Keyword(s):  
Genetic Programming ◽  
Domain Knowledge ◽  
Design Space ◽  
Graph Model ◽  
Bond Graph ◽  
Design Solution ◽  
Engineering Systems ◽  
Design Evolution ◽  
Bond Graph Modeling ◽  
Machine Health Monitoring

This paper presents a methodology for the design evolution of engineering systems, with a mechatronic emphasis. The developed approach specifically integrates machine health monitoring and an expert system and carries out the design evolution of a multidomain dynamic system using bond graph modeling and genetic programming. The evolution of a bond graph model of a mechatronic system through genetic programming enables the exploration of the design space, thereby generating a global optimum design solution in an automated manner. Domain knowledge and expertise are used to control the design exploration and to restrict it only to a meaningful design space. As an illustrative example, the developed methodology is applied to redesign the electrohydraulic manipulator of an existing industrial fish processing machine.

Building design-space exploration through quasi-optimization of life cycle impacts and costs

2018 ◽  
Vol 144 ◽  
pp. 34-44 ◽  
Author(s):  
Joshua Hester ◽  
Jeremy Gregory ◽  
Franz-Josef Ulm ◽  
Randolph Kirchain
Keyword(s):  
Life Cycle ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Building Design

scholarly journals Considerations of sample size and power calculations given a range of analytical scenarios

2021 ◽  
Author(s):  
Alice Carter ◽  
Kate Tilling ◽  
Marcus Robert Munafo
Keyword(s):  
Sample Size ◽  
Statistical Power ◽  
Poor Quality ◽  
Research Quality ◽  
Design Stage ◽  
Design Consideration ◽  
Power Calculations ◽  
Critical Design ◽  
Study Planning ◽  
Research Questions

The sample size of a study is a key design and planning consideration. However, sample size and power calculations are often either poorly reported or not reported at all, which suggests they may not form a routine part of study planning. Inadequate understanding of sample size and statistical power can result in poor quality studies. Journals increasingly require a justification of sample size, for example through the use of reporting checklists. However, for meaningful improvements in research quality to be made, researchers need to consider sample size and power at the design stage of a study, rather than at the publication stage. Here we briefly illustrate sample size and statistical power in the context of different research questions and how they should be viewed as a critical design consideration.

scholarly journals A rapid design space exploration approach for multi-objective optimization of DSP filter designs

2021 ◽  
Author(s):  
Aakriti Tarun Sharma
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Systems Design ◽  
Design Solution ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Time Period ◽  
And Performance ◽  
High Level

The process of converting a behavioral specification of an application to its equivalent system architecture is referred to as High Level-Synthesis (HLS). A crucial stage in embedded systems design involves finding the trade off between resource utilization and performance. An exhaustive search would yield the required results, but would take a huge amount of time to arrive at the solution even for smaller designs. This would result in a high time complexity. We employ the use of Design Space Exploration (DSE) in order to reduce the complexity of the design space and to reach the desired results in less time. In reality, there are multiple constraints defined by the user that need to be satisfied simultaneously. Thus, the nature of the task at hand is referred to as Multi-Objective Optimization. In this thesis, the design process of DSP benchmarks was analyzed based on user defined constraints such as power and execution time. The analyzed outcome was compared with the existing approaches in DSE and an optimal design solution was derived in a shorter time period.

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