Article records
https://feeds.library.caltech.edu/people/Antonsson-E-K/article.rss
A Caltech Library Repository Feedhttp://www.rssboard.org/rss-specificationpython-feedgenenTue, 16 Apr 2024 13:17:18 +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.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.edu/records/drcyt-3y668Compensation 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.edu/records/vdxv5-99p85Growth 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.edu/records/s0m4h-kf475Evolutionary 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.edu/records/vkj63-qhd81Computational 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.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.edu/records/8qj51-n1k34