Combined Feed
https://feeds.library.caltech.edu/people/Antonsson-E-K/combined.rss
A Caltech Library Repository Feedhttp://www.rssboard.org/rss-specificationpython-feedgenenTue, 16 Apr 2024 14:54:25 +0000Representing Imprecision in Engineering Design - Comparing Fuzzy and Probability Calculus
https://resolver.caltech.edu/CaltechAUTHORS:20120830-154129133
Authors: {'items': [{'id': 'Wood-K-L', 'name': {'family': 'Wood', 'given': 'Kristin L.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Beck-J-L', 'name': {'family': 'Beck', 'given': 'James L.'}}]}
Year: 1990
DOI: 10.1007/BF01581211
A technique to perform design calculations on imprecise representations of parameters using the calculus of fuzzy sets has been previously developed [25]. An analogous approach to representing and manipulatinguncertainty in choosing among alternatives (design imprecision) using probability calculus is presented and compared with the fuzzy calculus technique. Examples using both approaches are presented, where the examples represent a progression from simple operations to more complex design equations. Results of the fuzzy sets and probability methods for the examples are shown graphically. We find that the fuzzy calculus is well suited to representing and manipulating the imprecision aspect of uncertainty in design, and that probability is best used to represent stochastic uncertainty.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/yxnpg-jv869Integrated modeling, finite-element analysis, and engineering design for thin-shell structures using subdivision
https://resolver.caltech.edu/CaltechAUTHORS:20171208-164357957
Authors: {'items': [{'id': 'Cirak-F', 'name': {'family': 'Cirak', 'given': 'Fehmi'}}, {'id': 'Scott-M-J', 'name': {'family': 'Scott', 'given': 'Michael J.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Ortiz-M', 'name': {'family': 'Ortiz', 'given': 'Michael'}, 'orcid': '0000-0001-5877-4824'}, {'id': 'SchrÃ¶der-P', 'name': {'family': 'SchrÃ¶der', 'given': 'Peter'}, 'orcid': '0000-0002-0323-7674'}]}
Year: 2002
DOI: 10.1016/S0010-4485(01)00061-6
Many engineering design applications require geometric modeling and mechanical simulation of thin flexible structures, such as those found in the automotive and aerospace industries. Traditionally, geometric modeling, mechanical simulation, and engineering design are treated as separate modules requiring different methods and representations. Due to the incompatibility of the involved representations the transition from geometric modeling to mechanical simulation, as well as in the opposite direction, requires substantial effort. However, for engineering design purposes efficient transition between geometric modeling and mechanical simulation is essential. We propose the use of subdivision surfaces as a common foundation for modeling, simulation, and design in a unified framework. Subdivision surfaces provide a flexible and efficient tool for arbitrary topology free-form surface modeling, avoiding many of the problems inherent in traditional spline patch based approaches. The underlying basis functions are also ideally suited for a finite-element treatment of the so-called thin-shell equations, which describe the mechanical behavior of the modeled structures. The resulting solvers are highly scalable, providing an efficient computational foundation for design exploration and optimization. We demonstrate our claims with several design examples, showing the versatility and high accuracy of the proposed method.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/drcyt-3y668Hierarchical modularity: Decomposition of function structures with the minimal description length principle
https://resolver.caltech.edu/CaltechAUTHORS:20110816-090033673
Authors: {'items': [{'id': 'Wang-Bingwen', 'name': {'family': 'Wang', 'given': 'Bingwen'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2005
DOI: 10.1115/DETC2005-85173
In engineering design and analysis, complex systems often need to be decomposed into a hierarchical combination of different simple subsystems. It's necessary to provide formal, computable methods to hierarchically decompose complex structures. Since graph structures are commonly used as modeling methods in engineering practice, this paper presents a method to hierarchically decompose graph structures. The Minimal Description Length (MDL) principle is introduced as a measure to compare different decompositions. The best hierarchical decomposition is searched by, evolutionary computation methods with newly defined crossover and mutation operators of tree structures. The results on abstract graph without attributes and a real function structure show that the technique is promising.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/73afq-yky13Compensation and Weights for Trade-offs in Engineering Design: Beyond the Weighted Sum
https://resolver.caltech.edu/CaltechAUTHORS:SCOjmd05
Authors: {'items': [{'id': 'Scott-M-J', 'name': {'family': 'Scott', 'given': 'Michael J.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2005
DOI: 10.1115/1.1909204
Multicriteria decision support methods are common in engineering design. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. It has long been known that a weighted sum, when used for multicriteria optimization, may fail to locate all points on a nonconvex Pareto frontier. More recent results from the optimization literature relate the curvature of an objective function to its ability to capture Pareto points, but do not consider the significance of the objective function parameters in choosing one Pareto point over another. A parametrized family of aggregations appropriate for engineering design is shown to model decisions capturing all possible trade-offs, and therefore can direct the solution to any Pareto optimum. This paper gives a mathematical and theoretical interpretation of the parameters of this family of aggregations as defining a degree of compensation among criteria as well as a measure of their relative importance. The inability to reach all Pareto optima is shown to be surmounted by this consideration of degree of compensation as an additional parameter of the decision. Additionally, the direct specification of importance weights is common to many decision methods. The choice of a single point from a Pareto frontier by specifying importance weights alone is shown to depend on the degree of compensation implicit in the aggregation. Thus both the degree of compensation and weights must be considered to capture all potentially acceptable decisions. A simple truss design example is used here to illustrate the concepts.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/vdxv5-99p85Evolving neural controllers for collective robotic inspection
https://resolver.caltech.edu/CaltechAUTHORS:20110425-074717159
Authors: {'items': [{'id': 'Zhang-Yizhen', 'name': {'family': 'Zhang', 'given': 'Yizhen'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Martinoli-A', 'name': {'family': 'Martinoli', 'given': 'Alcherio'}}]}
Year: 2006
DOI: 10.1007/3-540-31662-0_55
In this paper, an automatic synthesis methodology based on evolutionary computation is applied to evolve neural controllers for a homogeneous team of miniature autonomous mobile robots. Both feed-forward and recurrent neural networks can be evolved with fixed or variable network topologies. The efficacy of the evolutionary methodology is demonstrated in the framework of a realistic case study on collective robotic inspection of regular structures, where the robots are only equipped with limited local on-board sensing and actuating capabilities. The neural controller solutions generated during evolutions are evaluated in a sensorbased embodied simulation environment with realistic noise. It is shown that the evolutionary algorithms are able to successfully synthesize a variety of novel neural controllers that could achieve performances comparable to a carefully hand-tuned, rule-based controller in terms of both average performance and robustness to noise.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/k572z-rbq98Growth and development of continuous structures
https://resolver.caltech.edu/CaltechAUTHORS:20100504-112315815
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2007
DOI: 10.1145/1276958.1277169
Nature has demonstrated the capability to evolve high performance systems. In natural evolution, genetic information is used to control the growth and development of individuals, whose performance in the environment determines whether their genetic information is passed on to subsequent generations. In this paper an artificial biological model has been created. The model uses artificial genetic information to control the growth and development of continuous inhomogeneous structures, where sets of rules control the growth and development of the individual. Using this method a relatively simple artificial genome can give rise to highly complex structures without defining explicitly the final configuration and form convenient model for evolution.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/s0m4h-kf475Modularity and symmetry in computational embryogeny
https://resolver.caltech.edu/CaltechAUTHORS:20170109-154237488
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2008
DOI: 10.1145/1389095.1389323
Modularity and symmetry are two properties observed in almost every engineering and biological structure. The origin of these properties in nature is still unknown. Yet, as engineers we tend to generate designs which share these properties. In this paper we will report on the origin of these properties in three dimensional evolved structures (phenotypes). The phenotypes were evolved in an evolutionarydevelopmental model of biological structures. The phenotypes were grown under a high volatility stochastic environment. The phenotypes have evolved to function within the environment using the very basic requirements. Even though neither modularity nor symmetry have been directly imposed as part of the requirements, the phenotypes were able to generate these properties after only a few hundred generations. These results may suggest that modularity and symmetry are both very fundamental properties that develop during the early stages of evolution. This result may give insight to the origin of both modularity and symmetry in biological organisms.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/c3sbj-6zr11Growth control and disease mechanisms in computational embryogeny
https://resolver.caltech.edu/CaltechAUTHORS:20170109-153829857
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2008
DOI: 10.1145/1389095.1389265
This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/qytgp-1sd28Evolutionary engineering design synthesis of on-board traffic monitoring sensors
https://resolver.caltech.edu/CaltechAUTHORS:20090813-100446801
Authors: {'items': [{'id': 'Zhang-Yizhen', 'name': {'family': 'Zhang', 'given': 'Yizhen'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Martinoli-A', 'name': {'family': 'Martinoli', 'given': 'Alcherio'}}]}
Year: 2008
DOI: 10.1007/s00163-008-0047-0
In this paper, a formal engineering design synthesis methodology based on evolutionary computation is presented, with special emphasis on the design and optimization of distributed independent systems. A case study concerned with design of a sensory system for traffic monitoring purposes is presented, along with simulations of traffic scenarios at several levels of abstraction. It is shown how the methodology introduced is able to deal with the engineering design challenges present in the case study, and effectively synthesize novel design solutions of good quality. Moreover, when the fitness function is formulated as an aggregation of design preferences with different weights and trade-off strategies, the complete Pareto optimal frontier can be determined by the evolutionary synthesis methodology. The results of this study suggest that the approach can be useful for designers to solve challenging engineering design synthesis problems.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/vkj63-qhd81Genetic programming of an artificial neural network for robust control of a 2-D path following robot
https://resolver.caltech.edu/CaltechAUTHORS:20100618-141102014
Authors: {'items': [{'id': 'Roy-A-M', 'name': {'family': 'Roy', 'given': 'Anthony M.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}]}
Year: 2009
DOI: 10.1115/DETC2008-50137
Genetic Programs that have phenotypes created by the application of genotypes comprising rules are robust and highly scalable. Such encodings are useful for complex applications such as controller design. This paper outlines an evolutionary algorithm capable of creating a controller for 2 DOF, path following robot. The controllers are embodied by Artificial Neural Networks capable of full functionality despite multiple failures.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/33w6p-2a737Engineering by fundamental elements of evolution
https://resolver.caltech.edu/CaltechAUTHORS:20100621-090548397
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2009
DOI: 10.1115/DETC2008-50102
The method presented in this note mimics two fundamental mechanisms from nature, growth, and development, for the synthesis of new three-dimensional structures. The structures were synthesized to support a load generated by a wind. Every structure grows from a single artificial cell following a set of genes, encoded in an artificial genome shared by all cells. Genes are a set of commands that control the growth process. Genes are regulated by interaction with the environment. The environment is both external and internal to the structure. The performance each structure is measured by its ability to hold the load and other additional engineering criteria. A population of structures is evolved using a genetic algorithm, which alters the genome of two mating individuals. We will present evolved phenotypes with high degrees of modularity and symmetry which evolved according to engineering criteria. Neither one of these two characteristics has been directly imposed as the fitness evaluation, but rather spontaneously emerge as a consequence of natural selection. We will argue that the types of rules we are using in this model are not biased toward any of these characteristics, but rather basic rules for growth and development.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/mrtch-mss24A novel evolutionary method for synthesis of 3D continuous structures
https://resolver.caltech.edu/CaltechAUTHORS:20100618-111644515
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2009
DOI: 10.1115/ESDA2008-59036
The design of complex structures which benefit the usage of inhomogeneous properties is a very difficult task. In this paper we present a novel approach in which we synthesize the design of structures by mimicking two fundamental processes from biology - Evolution and Development. We will show that by using these two processes in a computational model, we are able to evolve high performance structures. These structures contain a high degree of complexity from a topological aspect and from a materials distribution aspect. This degree of complexity is difficult or even impossible to achieve by ordinary design methods.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/x9xv4-k7h50An investigation into the structure of genomes within an evolution that uses embryogenesis
https://resolver.caltech.edu/CaltechAUTHORS:20161213-163636461
Authors: {'items': [{'id': 'Roy-A-M', 'name': {'family': 'Roy', 'given': 'Anthony M.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}]}
Year: 2009
DOI: 10.1145/1570256.1570290
Evolutionary algorithms that use embryogenesis in the creation of individuals have several desirable qualities. Such algorithms are able to create complex, modular designs which can scale well to large problems. However, the inner workings of developmental algorithms have not been investigated as thoroughly as their direct-encoding counterparts. More precisely, it would be beneficial to look at how the rules used during embryogenesis evolve alongside the phenotypes they produced. This paper reports on such an investigation into the evolution of a rule set for the growth of an artificial neural network, and identifies several aspects that are desirable for the genomes of a developmental evolutionary algorithm.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/1jh4w-qjq91Computational Evolutionary Embryogeny
https://resolver.caltech.edu/CaltechAUTHORS:20100513-154348375
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2010
DOI: 10.1109/TEVC.2009.2030438
Evolutionary and developmental processes are used to evolve the configurations of 3-D structures in silico to achieve desired performances. Natural systems utilize the combination of both evolution and development processes to produce remarkable performance and diversity. However, this approach has not yet been applied extensively to the design of continuous 3-D load-supporting structures. Beginning with a single artificial cell containing information analogous to a DNA sequence, a structure is grown according to the rules encoded in the sequence. Each artificial cell in the structure contains the same sequence of growth and development rules, and each artificial cell is an element in a finite element mesh representing the structure of the mature individual. Rule sequences are evolved over many generations through selection and survival of individuals in a population. Modularity and symmetry are visible in nearly every natural and engineered structure. An understanding of the evolution and expression of symmetry and modularity is emerging from recent biological research. Initial evidence of these attributes is present in the phenotypes that are developed from the artificial evolution, although neither characteristic is imposed nor selected-for directly. The computational evolutionary development approach presented here shows promise for synthesizing novel configurations of high-performance systems. The approach may advance the system design to a new paradigm, where current design strategies have difficulty producing useful solutions.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/2pxnx-mhn39A novel energy-based approach for merging finite elements
https://resolver.caltech.edu/CaltechAUTHORS:20110222-133743373
Authors: {'items': [{'id': 'Yogev-O', 'name': {'family': 'Yogev', 'given': 'Or'}}, {'id': 'Shapiro-A-A', 'name': {'family': 'Shapiro', 'given': 'Andrew A.'}}, {'id': 'Antonsson-E-K', 'name': {'family': 'Antonsson', 'given': 'Erik K.'}}]}
Year: 2011
DOI: 10.1002/nme.2963
A novel approach for merging two intersecting finite elements is presented and demonstrated. The solution mimics concepts from biology and uses principles rooted in continuum mechanics.
The problem of attaching (or merging) two coincident finite elements is common when using the plastering technique as part of the advancing front method. This problem is particularly challenging for 3-D meshes of non-convex shapes. Some automatic meshing methods require portions of the partially formed mesh to coincide and merge. This problem is generally solved with heuristic rules, which lack generality, and may have difficulties with unforeseen situations.
The problem of merging two overlapping polyhedra may also appear in other applications such as computer graphics and CAD software.
A new approach to address the problem of merging is presented here. This solution does not utilize heuristic rules, but rather uses an approach based on minimization of strain energy. A fully automatic merging routine has been created that can address, in an optimum way, any situation of two nearby or overlapping elements that are to be merged. This approach, with minor adjustments, is suitable for most types of 3-D elements.https://authors.library.caltech.eduhttps://authors.library.caltech.edu/records/8qj51-n1k34