Similarity of Engineering Design Problems to Enable Reuse in Design Research Experiments

2016 ◽  
Author(s):  
Varun Kumar ◽  
Gregory Mocko
Keyword(s):  
Latent Semantic Analysis ◽  
Design Problem ◽  
Design Research ◽  
Semantic Analysis ◽  
Functional Requirements ◽  
Design Problems ◽  
Creativity Research ◽  
Engineering Design Problems ◽  
Five Elements ◽  
Protocol Study

The objective of this research is to evaluate the similarity of design problems used in research experiments based on their representation. Design problems form an essential component of experiments in creativity research. However, the formulation of a design problem for an experiment is still a challenging task. An opportunity for the design community is leverage existing design problems to reduce a source of difference between experiments and increase the validity of new method and tools. To answer this question, fifty-five design problems, published over the past fifteen years, were collected and analyzed using two approaches. First, the information content of the design problems was assessed based on five structural elements. A protocol study was developed with four independent evaluators, who were asked to identify the five elements in a set of design problems. A high correlation was observed for the characteristics: goal of a problem, functional requirements, non-functional requirement and reference to an existing product. A low correlation was observed for the characteristics information about end user. The results suggest that this approach could serve as a useful tool in comparing and selecting problems with a desired number of elements. In the second approach, latent semantic analysis was used to compare the design problems. Latent semantic analysis enables design problem similarity to be computed prior to solving the problem. However, this method cannot identify the nuances in problem representations, which could potentially affect solution development. The paper concludes with an appeal to research community of using similar or benchmarked design problems, and postulate other means to enable comparison or development of problems in creativity research.

In Search of Effective Design Problems for Design Research

2015 ◽  
Author(s):  
Fabien Durand ◽  
Michael E. Helms ◽  
Joanna Tsenn ◽  
Daniel A. McAdams ◽  
Julie S. Linsey
Keyword(s):  
Design Problem ◽  
Design Theory ◽  
Design Research ◽  
Design Thinking ◽  
Design Method ◽  
Evaluation Metrics ◽  
Or Education ◽  
Design Problems ◽  
Early Results ◽  
Thinking Tools

Much design theory research seeks to create, evaluate, improve or optimize design methods. Whether that research focuses on design thinking, tools, methods, or education, short design problems are often provided to participants in order to evaluate the effects of the variables being tested. When designing and creating such problems, certain characteristics may influence design outcomes: experience and exposure to the design problems vary between participants, and each problem may be more or less favorable to the controlled variable. In this paper we conjecture a small set of design problem characteristics that may influence experimental outcomes, and we discuss two experiments targeted at uncovering this influence. In our first experiment we examine differences in evaluation metrics between two design problems. In a follow up experiment we correlate the hypothesized characteristics to the variances in experiment outcome. These early results assist to further compare and contrast the empirical differences in common evaluation metrics, as well as show how familiarity and extent of the subjects’ knowledge of a design problem influence these metrics. We also expose the potential for interaction between the design method and the design problem.

scholarly journals Coda: Creativity in psychological research versus in linguistics – Same but different?

2020 ◽  
Author(s):  
Selina Weiss ◽  
Oliver Wilhelm
Keyword(s):  
Individual Differences ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Psychological Research ◽  
General Process ◽  
Interdisciplinary Work ◽  
Verbal Creativity ◽  
Societal Relevance ◽  
Creativity Research ◽  
Similarities And Differences

Understanding the very nature of creativity is a hot topic in research across various disciplines and has profound societal relevance. In this contribution, we discuss verbal creativity by highlighting its definition, psy-chometric measurement, and relations with other personality dispositions. We relate psychological research with findings from linguistics presented in this issue and depict similarities and differences between both approaches. More specifically, we relate the linguistic terminology of F-creativity to flu-ency and flexibility, whereas we identify E-creativity as akin to originality. We propose latent semantic analysis as a possible approach for evaluating originality and compare this approach with more commonly applied human ratings. Based on contributions in this issue, we discuss creativity as a domain-general process that is (e.g., in applied arts) often driven by the recombination of mental elements. Lastly, we propose several intelligence and personality dispositions as determinants of individual differences in creativity. We conclude that creativity research in linguistic and psycholo-gy has many communalities and interdisciplinary work bears strong prom-ises for the future.

scholarly journals Optimal Solution of Structural Engineering Design Problems using Crow Search Algorithm

2019 ◽  
Vol 4 (4) ◽  
pp. 968-981
Author(s):  
Madhur Agarwal
Keyword(s):  
Engineering Design ◽  
Design Problem ◽  
Structural Engineering ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Worst Case ◽  
Design Problems ◽  
Beam Design ◽  
Engineering Design Problems ◽  
Better Than

In real world, the structural engineering design problems are large scale non-linear constrained problems. In the present study, crow search algorithm (CSA) is applied to find the optimal solution of structural engineering design problems such as pressure vessel design problem, welded beam design problem and tension/ compression string design problem. The numerical results are compared with the existing results reported in the literature including metaheuristic algorithms and it is found that the results obtained by the crow search algorithm are better than other existing algorithms. Further, the effectiveness of the algorithm is verified to be better than the existing algorithms by statistical analysis using mean, median, best case, and worst case scenarios. The present study confirms that the crow search algorithm may be easily and effectively applied to various structural design problems.

A New Artificial Immune Algorithm for Solving Gear Design Problem

2015 ◽  
Vol 766-767 ◽  
pp. 1003-1008
Author(s):  
S. Padmanabhan ◽  
S. Sivasaravanan ◽  
Karun Devasundaram
Keyword(s):  
Immune System ◽  
Design Problem ◽  
Artificial Immune System ◽  
Population Based ◽  
Design Solution ◽  
Artificial Immune ◽  
Design Problems ◽  
Gear Design ◽  
Mechanical Field ◽  
Engineering Design Problems

The design of gears is critical for smooth running of any mechanism, automobile and machinery. Gear drive design starts with the need of optimizing the gear thickness, module, number of teeth etc., this creates huge challenges to a designer. Optimization algorithms are more flexible and gaining importance in engineering design problems, because of the accessibility and affordability of today’s mechanical field. A population based heuristic algorithm offers well-organized ways of creating and comparing a novel design solution in order to complete an optimal design. In this paper, a new artificial immune system based algorithm proposed as Modified Artificial Immune System (MAIS) algorithm is used to optimize a gear design problem. The results are compared with an existing design.

Multi-Objective Optimal Design of Automotive Engine Using Genetic Algorithm

1998 ◽  
Author(s):  
Kikuo Fujita ◽  
Noriyasu Hirokawa ◽  
Shinsuke Akagi ◽  
Shinji Kitamura ◽  
Hideaki Yokohata
Keyword(s):  
Genetic Algorithm ◽  
Engineering Design ◽  
Design Problem ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Total Power ◽  
Design Problems ◽  
Automotive Engine ◽  
Multi Objective ◽  
Engineering Design Problems

Abstract A genetic algorithm based optimization method is proposed for a multi-objective design problem of an automotive engine, that includes several difficulties in practical engineering optimization problems. While various optimization techniques have been applied to engineering design problems, a class of realistic engineering design problems face on a mixture of different optimization difficulties, such as the rugged nature of system response, the numbers of design variables and objectives, etc. In order to overcome such a situation, this paper proposes a genetic algorithm based multi-objective optimization method, that introduces Pareto-optimality based fitness function, similarity based selection and direct real number crossover. This optimization method is also applied to the design problem of an automotive engine with the design criteria on a total power train. The computational examples show the ability of the proposed method for finding a relevant set of Pareto optima.

Parametric Deformations and Model Optimality in Concurrent Design

1993 ◽  
Author(s):  
J. R. Jagannatha Rao ◽  
Bala Chidambaram
Keyword(s):  
Engineering Design ◽  
Design Research ◽  
Stackelberg Game ◽  
Stackelberg Games ◽  
Concurrent Design ◽  
Design Problems ◽  
Pareto Model ◽  
Engineering Design Problems ◽  
Analysis And Synthesis ◽  
Potential Benefits

Abstract Concurrent modeling, as an emerging theme in engineering design research, also offers interesting new challenges in applied optimization. However, it is not always clear how best to construct mathematical models that represent such concurrent decision-making. In this paper, a class of engineering design problems, comprising analysis and synthesis tasks, is shown to be a two-player Stackelberg game with synthesis as the leader and analysis as the follower. Situations arising from a reversal of roles of the two tasks are studied and a Pareto model of a Design versus Analysis game is also investigated. Stackelberg games are then viewed in the larger context of concurrent design with design and manufacturing as two players. The potential benefits of such an approach are illustrated in the concurrent design of a stiffened plate structure.

scholarly journals ASSESSMENT OF EVIDENCE FOR THE EFFECTIVENESS OF DIFFERENT IDEATION PRACTICES

2012 ◽  
Author(s):  
Antony J Hodgson ◽  
HF Machiel Van Der Loos
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Design Problem ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Assessment Of Evidence ◽  
Engineering Schools

While most engineering schools substantially agree on the general form of the design process that should be used to address engineering design problems, surprisingly little is known about the actual practical effectiveness of many recommended techniques. In this paper and presentation, we review some of the recent evidence concerning the effectiveness of several well- known practices related to ideation - i.e., generating alternative potential solutions to a design problem.

Optimal Designs by Means of Genetic Algorithms

2021 ◽  
pp. 344-354
Author(s):  
Lata Nautiyal ◽  
Preeti Shivach ◽  
Mangey Ram
Keyword(s):  
Genetic Algorithms ◽  
Modeling And Simulation ◽  
Engineering Design ◽  
Design Problem ◽  
High Performance ◽  
Mechanical Engineering ◽  
Design Parameters ◽  
Design Problems ◽  
Simulation Tools ◽  
Engineering Design Problems

With the advancement in contemporary computational and modeling skills, engineering design completely depends upon on variety of computer modeling and simulation tools to hasten the design cycles and decrease the overall budget. The most difficult design problem will include various design parameters along with the tables. Finding out the design space and ultimate solutions to those problems are still biggest challenges for the area of complex systems. This chapter is all about suggesting the use of Genetic Algorithms to enhance maximum engineering design problems. The chapter recommended that Genetic Algorithms are highly useful to increase the High-Performance Areas for Engineering Design. This chapter is established to use Genetic Algorithms to large number of design areas and delivered a comprehensive conversation on the use, scope and its applications in mechanical engineering.

Optimal Designs by Means of Genetic Algorithms

2018 ◽  
pp. 151-161
Author(s):  
Lata Nautiyal ◽  
Preeti Shivach ◽  
Mangey Ram
Keyword(s):  
Genetic Algorithms ◽  
Modeling And Simulation ◽  
Engineering Design ◽  
Design Problem ◽  
High Performance ◽  
Mechanical Engineering ◽  
Design Parameters ◽  
Design Problems ◽  
Simulation Tools ◽  
Engineering Design Problems

With the advancement in contemporary computational and modeling skills, engineering design completely depends upon on variety of computer modeling and simulation tools to hasten the design cycles and decrease the overall budget. The most difficult design problem will include various design parameters along with the tables. Finding out the design space and ultimate solutions to those problems are still biggest challenges for the area of complex systems. This chapter is all about suggesting the use of Genetic Algorithms to enhance maximum engineering design problems. The chapter recommended that Genetic Algorithms are highly useful to increase the High-Performance Areas for Engineering Design. This chapter is established to use Genetic Algorithms to large number of design areas and delivered a comprehensive conversation on the use, scope and its applications in mechanical engineering.

scholarly journals Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design

2021 ◽  
pp. 1-21
Author(s):  
Ayush Raina ◽  
Lucas Puentes ◽  
Jonathan Cagan ◽  
Christopher McComb
Keyword(s):  
Design Problem ◽  
Domain Knowledge ◽  
Search Space ◽  
Design Strategies ◽  
Design Problems ◽  
Engineering Design Problems ◽  
One Step ◽  
Convolutional Encoder ◽  
Action Spaces ◽  
Relevant Domain

Abstract Engineering design problems often involve large state and action spaces along with highly sparse rewards. Since an exhaustive search of those spaces is not feasible, humans utilize relevant domain knowledge to condense the search space. Deep learning agents (DLAgents) were previously introduced to use visual imitation learning to model design domain knowledge. This note builds on DLAgents and integrates them with one-step lookahead search to develop goal-directed agents capable of enhancing learned strategies for sequentially generating designs. Goal-directed DLAgents can employ human strategies learned from data along with optimizing an objective function. The visual imitation network from DLAgents is composed of a convolutional encoder-decoder network, acting as a rough planning step that is agnostic to feedback. Meanwhile, the lookahead search identifies the fine-tuned design action guided by an objective. These design agents are trained on an unconstrained truss design problem modeled as a sequential, action-based configuration design problem. The agents are then evaluated on two versions of the problem: the original version used for training and an unseen constrained version with an obstructed construction space. The goal-directed agents outperform the human designers used to train the network as well as the previous feedback-agnostic versions of the agent in both scenarios. This illustrates a design agent framework that can efficiently use feedback to not only enhance learned design strategies but also adapt to unseen design problems.

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