Heuristic-Guided Solution Search Through a Two-Tiered Design Grammar

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Lucas Puentes ◽  
Jonathan Cagan ◽  
Christopher McComb
Keyword(s):  
Design Space ◽  
Effective Means ◽  
Computational Design ◽  
Research Area ◽  
Domain Specific ◽  
Lower Tier ◽  
Design Changes ◽  
Incremental Design ◽  
Gradual Process ◽  
Design Generation

Abstract Grammar-based design is typically a gradual process; incremental design changes are performed until a problem statement has been satisfied. While they offer an effective means for searching a design space, standard grammars risk being computationally costly because of the iteration required, and the larger a given grammar the broader the search required. This paper proposes a two-tiered design grammar that enhances the computational design generation with generalized heuristics to provide a way to more efficiently search a design space. Specifically, this two-tiered grammar captures a combination of heuristic-based strategic actions (often observed in human designers) and smaller-scale modifications (common in traditional grammars). Rules in the higher tier are abstract and applicable across multiple design domains. Through associated guiding heuristics, these macrorules are translated down into a sequence of domain-specific, lower-tier microrules. This grammar is evaluated through an implementation within an agent-based simulated annealing team algorithm in which agents iteratively select actions from either the higher tier or the lower tier. This algorithm is used in two applications: truss generation, which is commonly used for testing engineering design methods, and wave energy converter design generation, which is currently a relevant research area in sustainable energy production. Comparisons are made between designs generated using only lower-tier rules and those generated using only higher-tier rules. Further tests demonstrate the efficacy of applying a combination of both lower-tier and higher-tier rules.

Computational Design Generation and Evaluation of Beam-Based Tetragonal Bravais Lattice Structures for Tissue Engineering

2020 ◽  
Author(s):  
Amit M. E. Arefin ◽  
Paul F. Egan
Keyword(s):  
Medical Devices ◽  
Design Space ◽  
Specific Growth ◽  
Computational Design ◽  
Tissue Growth ◽  
Biological Behavior ◽  
Mapping Technique ◽  
Bravais Lattice ◽  
Unit Cells ◽  
Design Generation

Abstract The study and application of computational design is gaining importance in biomedical engineering as medical devices are becoming more complex, especially with the emergence of 3D printed scaffold structures. Scaffolds are medical devices that act as temporary mechanical support and facilitate biological interactions to regenerate damaged tissues. Past computational design studies have investigated the influence of geometric design in lattice structured scaffolds to investigate mechanical and biological behavior. However, these studies often focus on symmetric cubic structures leaving an opportunity for investigating a larger portion of the design space to find favorable scaffold configurations beyond these constraints. Here, tissue growth behavior is investigated for tetragonal Bravais lattice structured scaffolds by implementing a computational approach that combines a voxel-based design generation method, curvature-based tissue growth modeling, and a design mapping technique for selecting scaffold designs. Results show that tetragonal unit cells achieve higher specific tissue growth than cubic unit cells when investigated for a constant beam width, thus demonstrating the merits in investigating a larger portion of the design space. It is seen that cubic structures achieve around 50% specific growth, while tetragonal structures achieve more than 60% specific growth for the design space investigated. These findings demonstrate the need for continued adaption and use of computational design methodologies for biomedical applications, where the discovery of favorable solutions may significantly improve medical outcomes.

Parallel Computing for Tire Simulations

2011 ◽  
Vol 39 (3) ◽  
pp. 193-209 ◽  
Author(s):  
H. Surendranath ◽  
M. Dunbar
Keyword(s):  
High Performance ◽  
Effective Means ◽  
Cost Effective ◽  
Turnaround Time ◽  
Careful Consideration ◽  
Rolling Contact ◽  
Element Analysis ◽  
Parallel Solvers ◽  
Design Changes ◽  
Highly Nonlinear

Abstract Over the last few decades, finite element analysis has become an integral part of the overall tire design process. Engineers need to perform a number of different simulations to evaluate new designs and study the effect of proposed design changes. However, tires pose formidable simulation challenges due to the presence of highly nonlinear rubber compounds, embedded reinforcements, complex tread geometries, rolling contact, and large deformations. Accurate simulation requires careful consideration of these factors, resulting in the extensive turnaround time, often times prolonging the design cycle. Therefore, it is extremely critical to explore means to reduce the turnaround time while producing reliable results. Compute clusters have recently become a cost effective means to perform high performance computing (HPC). Distributed memory parallel solvers designed to take advantage of compute clusters have become increasingly popular. In this paper, we examine the use of HPC for various tire simulations and demonstrate how it can significantly reduce simulation turnaround time. Abaqus/Standard is used for routine tire simulations like footprint and steady state rolling. Abaqus/Explicit is used for transient rolling and hydroplaning simulations. The run times and scaling data corresponding to models of various sizes and complexity are presented.

scholarly journals Computational Design of Modular Robots Based on Genetic Algorithm and Reinforcement Learning

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 471
Author(s):  
Jai Hoon Park ◽  
Kang Hoon Lee
Keyword(s):  
Genetic Algorithm ◽  
Reinforcement Learning ◽  
Design Space ◽  
Learning Algorithm ◽  
Computational Design ◽  
Computational Method ◽  
Learning Ability ◽  
Modular Robots ◽  
Control Mechanisms ◽  
Candidate Structure

Designing novel robots that can cope with a specific task is a challenging problem because of the enormous design space that involves both morphological structures and control mechanisms. To this end, we present a computational method for automating the design of modular robots. Our method employs a genetic algorithm to evolve robotic structures as an outer optimization, and it applies a reinforcement learning algorithm to each candidate structure to train its behavior and evaluate its potential learning ability as an inner optimization. The size of the design space is reduced significantly by evolving only the robotic structure and by performing behavioral optimization using a separate training algorithm compared to that when both the structure and behavior are evolved simultaneously. Mutual dependence between evolution and learning is achieved by regarding the mean cumulative rewards of a candidate structure in the reinforcement learning as its fitness in the genetic algorithm. Therefore, our method searches for prospective robotic structures that can potentially lead to near-optimal behaviors if trained sufficiently. We demonstrate the usefulness of our method through several effective design results that were automatically generated in the process of experimenting with actual modular robotics kit.

Scaled Prediction Variances of Equiradial Design under Changing Design Sizes, Axial Distances and Center Runs

2021 ◽  
pp. 1-13
Author(s):  
Bartholomew, Desmond Chekwube ◽  
Obite, Chukwudi Paul ◽  
Ismaila-Cosmos Joan
Keyword(s):  
Model Comparison ◽  
Design Space ◽  
Optimality Criterion ◽  
Information Matrix ◽  
Axial Distance ◽  
Design Changes ◽  
Design Choice ◽  
Prediction Variance ◽  
Design Type ◽  
Scaled Prediction Variance

The aim of every design choice is to minimize the prediction error, especially at every location of the design space, thus, it is important to measure the error at all locations in the design space ranging from the design center (origin) to the perimeter (distance from the origin). The measure of the errors varies from one design type to another and considerably the distance from the design center. Since this measure is affected by design sizes, it is ideal to scale the variance for the purpose of model comparison. Therefore, we have employed the Scaled Prediction Variance and D – optimality criterion to check the behavior of equiradial designs and compare them under varying axial distances, design sizes and center points. The following similarities were observed: (i) increasing the design radius (axial distance) of an equiradial design changes the maximum determinant of the information matrix by five percent of the new axial distance (5% of 1.414 = 0.07) see Table 3. (ii) increasing the nc center runs  pushes the maximum  SPV(x) to the furthest distance from the design center (0  0) (iii) changing the design radius changes the location in the design region with maximum SPV(x) by a multiple of the change and (iv) changing the design radius also does not change the maximum  SPV(x) at different radial points and center runs . Based on the findings of this research, we therefore recommend consideration of equiradial designs with only two center runs in order to maximize the determinant of the information matrix and minimize the scaled prediction variances.

Negotiating human engagement and the fixity of computational design: Toward a performative design space for the differently-abled bodymind

2020 ◽  
Vol 18 (2) ◽  
pp. 174-193
Author(s):  
Sean Ahlquist
Keyword(s):  
Environmental Factors ◽  
Structural Optimization ◽  
Design Process ◽  
Design Space ◽  
Computational Design ◽  
Social Nature ◽  
And Performance ◽  
The Moment ◽  
Cultural Entity

Computational design affords agency: the ability to orchestrate the material, spatial, and technical architectural system. In this specific case, it occurs through enhanced, authored means to facilitate making and performance—typically driven by concerns of structural optimization, material use, and responsivity to environmental factors—of an atmospheric rather than social nature. At issue is the positioning of this particular manner of agency solely with the architect auteur. This abruptly halts—at the moment in which fabrication commences—the ability to amend, redefine, or newly introduce fundamentally transformational constituents and their interrelationships and, most importantly, to explore the possibility for extraordinary outcomes. When the architecture becomes a functional, social, and cultural entity, in the hands of the idealized abled-bodied user, agency—especially for one of an otherly body or mind—is long gone. Even an empathetic auteur may not be able to access the motivations of the differently-abled body and neuro-divergent mind, effectively locking the constraints of the design process, which creates an exclusionary system to those beyond the purview of said auteur. It can therefore be deduced that the mechanisms or authors of a conventional computational design process cannot eradicate the exclusionary reality of an architectural system. Agency is critical, yet a more expansive terminology for agent and agency is needed. The burden to conceive of capacities that will always be highly temporal, social, unpredictable, and purposefully unknown must be shifted far from the scope of the traditional directors of the architectural system. Agency, and who it is conferred upon, must function in a manner that dissolves the distinctions between the design, the action of designing, the author of design, and those subjected to it.

scholarly journals Nature-based solutions for hydro-meteorological risk reduction: a state-of-the-art review of the research area

2020 ◽  
Vol 20 (1) ◽  
pp. 243-270 ◽  
Author(s):  
Laddaporn Ruangpan ◽  
Zoran Vojinovic ◽  
Silvana Di Sabatino ◽  
Laura Sandra Leo ◽  
Vittoria Capobianco ◽  
...  
Keyword(s):  
Risk Reduction ◽  
Current Knowledge ◽  
Effective Means ◽  
Storm Surges ◽  
Cost Effective ◽  
Research Area ◽  
Significant Rise ◽  
Future Research ◽  
Scientific Publications ◽  
Projected Changes

Abstract. Hydro-meteorological risks due to natural hazards such as severe floods, storm surges, landslides and droughts are causing impacts on different sectors of society. Such risks are expected to become worse given projected changes in climate, degradation of ecosystems, population growth and urbanisation. In this respect, nature-based solutions (NBSs) have emerged as effective means to respond to such challenges. A NBS is a term used for innovative solutions that are based on natural processes and ecosystems to solve different types of societal and environmental challenges. The present paper provides a critical review of the literature concerning NBSs for hydro-meteorological risk reduction and identifies current knowledge gaps and future research prospects. There has been a considerable growth of scientific publications on this topic, with a more significant rise taking place from 2007 onwards. Hence, the review process presented in this paper starts by sourcing 1608 articles from Scopus and 1431 articles from the Web of Science. The full analysis was performed on 146 articles. The analysis confirmed that numerous advancements in the area of NBSs have been achieved to date. These solutions have already proven to be valuable in providing sustainable, cost-effective, multi-purpose and flexible means for hydro-meteorological risk reduction. However, there are still many areas where further research and demonstration are needed in order to promote their upscaling and replication and to make them become mainstream solutions.

scholarly journals Assessing secondary students’ scientific literacy: A comparative study of suburban schools in England and Malaysia

2021 ◽  
Vol 32 (4) ◽  
pp. 343-352
Author(s):  
Mohd Syafiq Aiman Mat Noor ◽  
Keyword(s):  
Secondary Students ◽  
Scientific Literacy ◽  
Research Area ◽  
Suburban Schools ◽  
Assessment Instrument ◽  
Literacy Assessment ◽  
Domain Specific ◽  
Data Collection And Analysis ◽  
Malaysian Students ◽  
English Students

This study sought to assess the level of secondary students’ scientific literacy in suburban schools in Malaysia and England, a research area which to date has not been fully explored in the literature. The study analysed the data using the OECD’s three domain-specific competencies of scientific literacy, namely: i) explain phenomena scientifically, ii) evaluate and design scientific enquiry, and iii) interpret data and evidence scientifically. To assess the level of secondary students’ scientific literacy in these contexts, the study applied the scientific literacy assessment instrument called the ‘Nature of Scientific Literacy Test’ (NOSLiT), first developed by Wenning (2006). The results indicated that the level of scientific literacy of English students was higher than that of Malaysian students across all three domain-specific competencies. Despite the fact that NOSLiT is a systematic and reliable instrument for assessing the level of students’ scientific literacy, the study found that OECD’s three domain-specific competencies of scientific literacy provided better insights into the level of secondary students’ scientific literacy in Malaysian and English suburban schools. It is suggested that future studies should use a qualitative approach to both data collection and analysis to understand the level of students’ scientific literacy in more detail.

Domain Specific Custom Search for Quicker Information Retrieval

2013 ◽  
Vol 3 (3) ◽  
pp. 26-39
Author(s):  
Tushar Kanti Saha ◽  
A. B. M. Shawkat Ali
Keyword(s):  
Research Area ◽  
Google Scholar ◽  
Research Articles ◽  
Search Technique ◽  
Relevant Research ◽  
Domain Specific ◽  
First Time ◽  
Specific Search ◽  
Specific Country ◽  
Quick Search

Recently researchers are using Google scholar widely to find out the research articles and the relevant experts in their domain. But it is unable to find out all experts in a relevant research area from a specific country by a quick search. Basically the custom search technique is not available in the current Google scholar’s setup. The authors have combined custom search with domain-specific search and named as domain specific custom search in this research. First time this research introduces a domain specific custom search technique using new search methodology called n-paged-m-items partial crawling algorithm. This algorithm is a real-time faster crawling algorithm due to the partial crawling technique. It does not store anything in the database, which can be shown later on to the user. The proposed algorithm is implemented on a new domain scholar.google.com to find out the scholars or experts quickly. Finally the authors observe the better performance of the proposed algorithm comparing with Google scholar.

scholarly journals Bayesian Network Classifiers for Set-Based Collaborative Design

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
David W. Shahan ◽  
Carolyn Conner Seepersad
Keyword(s):  
Bayesian Network ◽  
Collaborative Design ◽  
Design Problem ◽  
Design Space ◽  
Expert Knowledge ◽  
Optimization Techniques ◽  
Domain Specific ◽  
Bayesian Network Classifiers ◽  
New Information ◽  
Engineering Design Problems

Complex engineering design problems are often decomposed into a set of interdependent, distributed subproblems that are solved by domain-specific experts. These experts must resolve couplings between the subproblems and negotiate satisfactory, system-wide solutions. Set-based approaches help resolve these couplings by systematically mapping satisfactory regions of the design space for each subproblem and then intersecting those maps to identify mutually satisfactory system-wide solutions. In this paper, Bayesian network classifiers are introduced for mapping sets of promising designs, thereby classifying the design space into satisfactory and unsatisfactory regions. The approach is applied to two example problems—a spring design problem and a simplified, multilevel design problem for an unmanned aerial vehicle (UAV). The method is demonstrated to offer several advantages over competing techniques, including the ability to represent arbitrarily shaped and potentially disconnected regions of the design space and the ability to be updated straightforwardly as new information about the satisfactory design space is discovered. Although not demonstrated in this paper, it is also possible to interface the classifier with automated search and optimization techniques and to combine expert knowledge with the results of quantitative simulations when constructing the classifiers.

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