A Method for Visualizing the Relations Between Grammar Rules, Performance Objectives and Search Space Exploration in Grammar-Based Computational Design Synthesis

2015 ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Computational Design ◽  
Search Space ◽  
Synthesis Process ◽  
Design Synthesis ◽  
Novel Approach ◽  
Grammar Rules ◽  
Computational Design Synthesis

Design grammars have been successfully applied in numerous engineering disciplines, e.g. in electrical engineering, architecture and mechanical engineering. A successful application of design grammars in Computational Design Synthesis (CDS) requires a) a meaningful representation of designs and the design task at hand, b) a careful formulation of grammar rules to synthesize new designs, c) problem specific design evaluations, and d) the selection of an appropriate algorithm to guide the synthesis process. Managing these different aspects of CDS requires not only a detailed understanding of each individual part, but also of the interdependencies between them. In this paper, a new method is presented to analyze the exploration of design spaces in CDS. The method analyzes the designs generated during the synthesis process and visualizes how the design space is explored with respect to a) design characteristics, and b) objectives. The selected algorithm as well as the grammar rules can be analyzed with this approach to support the human designer in successfully understanding and applying a CDS method. The case study demonstrates how the method is used to analyze the synthesis of bicycle frames. Two algorithms are compared for this task. Results demonstrate how the method increases the understanding of the different components in CDS. The presented research can be useful for both novices to CDS to help them gain a deeper understanding of the interplay between grammar rules and guidance of the synthesis process, as well as for experts aiming to further improve their CDS application by improving parameter settings of their search algorithms, or by further refining their design grammar. Additionally, the presented method constitutes a novel approach to interactively visualize design space exploration considering not only designs objectives, but also the characteristics and interdependencies of different designs.

Visualizing Relations Between Grammar Rules, Objectives, and Search Space Exploration in Grammar-Based Computational Design Synthesis1

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Method Development ◽  
Search Algorithm ◽  
Computational Design ◽  
Search Space ◽  
Synthesis Process ◽  
Design Synthesis ◽  
Grammar Rules ◽  
Computational Design Synthesis ◽  
Design Characteristics ◽  
Selection Of

Design grammars have been successfully applied in numerous engineering disciplines, e.g., in electrical engineering, architecture, and mechanical engineering. A successful application of design grammars in computational design synthesis (CDS) requires (a) meaningful representation of designs and the design task at hand, (b) careful formulation of grammar rules to synthesize new designs, (c) problem-specific design evaluation, and (d) selection of an appropriate algorithm to guide the synthesis process. Determining these different components of a CDS method requires not only a detailed understanding of each individual part but also of the interdependencies between them. In this paper, a new method is presented to support both CDS method development and application. The method analyzes the designs generated during the synthesis process and visualizes how the design space is explored with respect to design characteristics and objectives. The search algorithm as well as the grammar rules are analyzed with this approach. Two case studies, the synthesis of gearboxes and of bicycle frames, demonstrate how the method can be used to analyze the different components of CDS methods. The presented research can analyze the interplay between grammar rules and the search process during method development.

Toward an automated approach to the design of sheet metal components

2003 ◽  
Vol 17 (3) ◽  
pp. 187-204 ◽  
Author(s):  
ADITYA SOMAN ◽  
SWAPNIL PADHYE ◽  
MATTHEW I. CAMPBELL
Keyword(s):  
Sheet Metal ◽  
User Interaction ◽  
Computational Design ◽  
Design Synthesis ◽  
Manufacturing Operations ◽  
Grammar Rules ◽  
Computational Design Synthesis ◽  
Representation Scheme ◽  
Sheet Metal Component ◽  
Synthesis Approach

The design of sheet metal components is perhaps one of the more challenging concurrent activities for design and manufacturing engineers. To aid this design process, a method is developed to encapsulate the constraints of sheet metal that make designing such components a tedious and iterative procedure. This project involves the implementation and testing of a geometric representation scheme for building feasible sheet metal components through the use of 17 grammar rules that capture manufacturing operations like cutting and bending. The implemented system has benefits both as a user interaction tool and as the basis for a computational design synthesis approach for designing sheet metal components. An example of a constructed sheet metal component is shown along with the method for invoking the sheet metal grammar to create this component.

PaDGAN: Learning to Generate High-Quality Novel Designs

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Wei Chen ◽  
Faez Ahmed
Keyword(s):  
Loss Function ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Generative Models ◽  
Training Data ◽  
High Quality ◽  
Generative Adversarial Network ◽  
Design Synthesis ◽  
Adversarial Network

Abstract Deep generative models are proven to be a useful tool for automatic design synthesis and design space exploration. When applied in engineering design, existing generative models face three challenges: (1) generated designs lack diversity and do not cover all areas of the design space, (2) it is difficult to explicitly improve the overall performance or quality of generated designs, and (3) existing models generally do not generate novel designs, outside the domain of the training data. In this article, we simultaneously address these challenges by proposing a new determinantal point process-based loss function for probabilistic modeling of diversity and quality. With this new loss function, we develop a variant of the generative adversarial network, named “performance augmented diverse generative adversarial network” (PaDGAN), which can generate novel high-quality designs with good coverage of the design space. By using three synthetic examples and one real-world airfoil design example, we demonstrate that PaDGAN can generate diverse and high-quality designs. In comparison to a vanilla generative adversarial network, on average, it generates samples with a 28% higher mean quality score with larger diversity and without the mode collapse issue. Unlike typical generative models that usually generate new designs by interpolating within the boundary of training data, we show that PaDGAN expands the design space boundary outside the training data towards high-quality regions. The proposed method is broadly applicable to many tasks including design space exploration, design optimization, and creative solution recommendation.

A Spatial Grammar Method for the Computational Design Synthesis of Virtual Soft Locomotion Robots

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Merel van Diepen ◽  
Kristina Shea
Keyword(s):  
Degrees Of Freedom ◽  
Computational Design ◽  
Simulation Method ◽  
Search Space ◽  
Search Process ◽  
Design Synthesis ◽  
Spatial Grammar ◽  
Three Stages ◽  
Computational Design Synthesis ◽  
Simulation Feedback

Soft locomotion robots are intrinsically compliant and have a large number of degrees of freedom. They lack rigid components that provide them with higher flexibility, and they have no joints that need protection from liquids or dirt. However, the hand-design of soft robots is often a lengthy trail-and-error process. This work presents the computational design of virtual, soft locomotion robots using an approach that integrates simulation feedback. The computational approach consists of three stages: (1) generation, (2) evaluation through simulation, and (3) optimization. Here, designs are generated using a spatial grammar to explicitly guide the type of solutions generated and exclude infeasible designs. The soft material simulation method developed and integrated is stable and sufficiently fast for use in a highly iterative simulated annealing search process. The resulting virtual designs exhibit a large variety of expected and unexpected gaits, thus demonstrating the method capabilities. Finally, the optimization results and the spatial grammar are analyzed to understand and map the challenges of the problem and the search space.

Automatically Transforming Object-Oriented Graph-Based Representations Into Boolean Satisfiability Problems for Computational Design Synthesis

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
Clemens Münzer ◽  
Bergen Helms ◽  
Kristina Shea
Keyword(s):  
Space Exploration ◽  
Solution Space ◽  
Object Oriented ◽  
Computational Design ◽  
Building Blocks ◽  
Boolean Satisfiability ◽  
Design Synthesis ◽  
Alcohol Production ◽  
Systematic Solution ◽  
Computational Design Synthesis

Ever since computers have been used to support human designers, a variety of representations have been used to encapsulate engineering knowledge. Computational design synthesis (CDS) approaches utilize this knowledge to generate design candidates for a specified task. However, new approaches are required to enable systematic solution space exploration. This paper presents an approach that combines a graph-based object-oriented knowledge representation with first-order logic and Boolean satisfiability. This combination is used as the foundation for a generic automated approach for requirement-driven computational design synthesis. Available design building blocks and a design task defined through a set of requirements are modeled in a graph-based environment and then automatically transferred into a Boolean satisfiability problem and solved, considering a given solution size. The Boolean solution is automatically transferred back to the graph-based domain. The method is validated through two case studies: synthesis of automotive powertrains and chemical process synthesis for ethyl alcohol production. The contribution of the paper is a new method that is able to determine if an engineering task is solvable for a given set of synthesis building blocks and enables systematic solution space exploration.

scholarly journals Systematic rule analysis of generative design grammars

2014 ◽  
Vol 28 (3) ◽  
pp. 227-238 ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Computational Design ◽  
Research Area ◽  
Synthesis Process ◽  
Analysis Method ◽  
Grammar Rule ◽  
Generative Design ◽  
Design Synthesis ◽  
Grammar Rules ◽  
Rule Analysis

AbstractThe use of generative design grammars for computational design synthesis has been shown to be successful in many application areas. The development of advanced search and optimization strategies to guide the computational synthesis process is an active research area with great improvements in the last decades. The development of the grammar rules, however, often resembles an art rather than a science. Poor grammars drive the need for problem specific and sophisticated search and optimization algorithms that guide the synthesis process toward valid and optimized designs in a reasonable amount of time. Instead of tuning search algorithms for inferior grammars, this research focuses on designing better grammars to not unnecessarily burden the search process. It presents a grammar rule analysis method to provide a more systematic development process for grammar rules. The goal of the grammar rule analysis method is to improve the quality of the rules and in turn have a major impact on the quality of the designs generated. Four different grammars for automated gearbox synthesis are used as a case study to validate the developed method and show its potential.

Whither design space?

2006 ◽  
Vol 20 (2) ◽  
pp. 63-82 ◽  
Author(s):  
ROBERT F. WOODBURY ◽  
ANDREW L. BURROW
Keyword(s):  
Network Structure ◽  
Design Space Exploration ◽  
Design Research ◽  
Design Space ◽  
Space Exploration ◽  
Computational Design ◽  
Exploration Process ◽  
Computational Structures

Design space exploration is a long-standing focus in computational design research. Its three main threads are accounts of designer action, development of strategies for amplification of designer action in exploration, and discovery of computational structures to support exploration. Chief among such structures is the design space, which is the network structure of related designs that are visited in an exploration process. There is relatively little research on design spaces to date. This paper sketches a partial account of the structure of both design spaces and research to develop them. It focuses largely on the implications of designers acting as explorers.

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