The Experts below are selected from a list of 24546 Experts worldwide ranked by ideXlab platform

S. K. Curtis - One of the best experts on this subject based on the ideXlab platform.

  • Usage scenarios for design space exploration with a dynamic multiobjective Optimization Formulation
    Research in Engineering Design, 2013
    Co-Authors: S. K. Curtis, B. J. Hancock, Christopher A. Mattson
    Abstract:

    In a recent publication, we presented a new strategy for engineering design and Optimization, which we termed Formulation space exploration. The Formulation space for an Optimization problem is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into this new space, the solution to any Optimization problem is no longer predefined by the Optimization problem Formulation. This method allows a designer to both diverge the design space during conceptual design and converge onto a solution as more information about the design objectives and constraints becomes available. Additionally, we introduced a new way to formulate multiobjective Optimization problems, allowing the designer to change and update design objectives, constraints, and variables in a simple, fluid manner that promotes exploration. In this paper, we investigate three usage scenarios where Formulation space exploration can be utilized in the early stages of design when it is possible to make the greatest contributions to development projects. Specifically, we look at Formulation space boundary exploration, Pareto frontier generation for multiple concepts in the Formulation space, and a new way to perform targeted boundary expansion. The benefits of these methods are illustrated with the conceptual design of an impact driver.

  • Divergent exploration in design with a dynamic multiobjective Optimization Formulation
    Structural and Multidisciplinary Optimization, 2013
    Co-Authors: S. K. Curtis, B. J. Hancock, Christopher A. Mattson, P. K. Lewis
    Abstract:

    Formulation space exploration is a new strategy for multiobjective Optimization that facilitates both divergent exploration and convergent Optimization during the early stages of design. The Formulation space is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into the Formulation space, the solution to an Optimization problem is no longer predefined by any single problem Formulation, as it is with traditional Optimization methods. Instead, a designer is free to change, modify, and update design objectives, variables, and constraints and explore design alternatives without requiring a concrete understanding of the design problem a priori. To facilitate this process, we introduce a new vector/matrix-based definition for multiobjective Optimization problems, which is dynamic in nature and easily modified. Additionally, we provide a set of exploration metrics to help guide designers while exploring the Formulation space. Finally, we provide an example to illustrate the use of this new, dynamic approach to multiobjective Optimization.

  • A Method for Exploring Optimization Formulation Space in Conceptual Design
    2012
    Co-Authors: S. K. Curtis
    Abstract:

    A Method for Exploring Optimization Formulation Space in Conceptual Design Shane K. Curtis Department of Mechanical Engineering, BYU Master of Science Formulation space exploration is a new strategy for multiobjective Optimization that facilitates both divergent searching and convergent Optimization during the early stages of design. The Formulation space is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into the Formulation space, the solution to an Optimization problem is no longer predefined by any single problem Formulation, as it is with traditional Optimization methods. Instead, a designer is free to change, modify, and update design objectives, variables, and constraints and explore design alternatives without requiring a concrete understanding of the design problem a priori. To facilitate this process, a new vector/matrix-based definition for multiobjective Optimization problems is introduced, which is dynamic in nature and easily modified. Additionally, a set of exploration metrics is developed to help guide designers while exploring the Formulation space. Finally, several examples are presented to illustrate the use of this new, dynamic approach to multiobjective Optimization.

Mourad Nachaoui - One of the best experts on this subject based on the ideXlab platform.

P. K. Lewis - One of the best experts on this subject based on the ideXlab platform.

  • Divergent exploration in design with a dynamic multiobjective Optimization Formulation
    Structural and Multidisciplinary Optimization, 2013
    Co-Authors: S. K. Curtis, B. J. Hancock, Christopher A. Mattson, P. K. Lewis
    Abstract:

    Formulation space exploration is a new strategy for multiobjective Optimization that facilitates both divergent exploration and convergent Optimization during the early stages of design. The Formulation space is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into the Formulation space, the solution to an Optimization problem is no longer predefined by any single problem Formulation, as it is with traditional Optimization methods. Instead, a designer is free to change, modify, and update design objectives, variables, and constraints and explore design alternatives without requiring a concrete understanding of the design problem a priori. To facilitate this process, we introduce a new vector/matrix-based definition for multiobjective Optimization problems, which is dynamic in nature and easily modified. Additionally, we provide a set of exploration metrics to help guide designers while exploring the Formulation space. Finally, we provide an example to illustrate the use of this new, dynamic approach to multiobjective Optimization.

Mahmoud M. El-halwagi - One of the best experts on this subject based on the ideXlab platform.

  • Involving Environmental Assessment in the Optimal Design of Domestic Cogeneration Systems
    Process Integration and Optimization for Sustainability, 2017
    Co-Authors: Victoria Morales-durán, Mahmoud M. El-halwagi, Luis Fabián Fuentes-cortes, Margarita González-brambila, José María Ponce-ortega
    Abstract:

    This paper presents a multi-objective Optimization Formulation for designing domestic cogeneration systems to satisfy thermal and electric energy demands. The proposed model is formulated as a multi-objective mixed-integer nonlinear programming model, which incorporates as economic objective function the minimization of the total annual cost, which includes the capital costs for the new units and the thermal storage system as well as the operating and maintenance costs. The model also incorporates an environmental objective function, which accounts for the life cycle assessment through the Eco-indicator 99 method to account for the damages to the resources, human health, and ecosystem quality. The proposed model allows considering the interaction with the external users and the external electric grid. The Optimization Formulation is solved to generate design alternatives to establish tradeoffs among the considered objectives.

  • Optimal design of domestic water-heating solar systems
    Clean Technologies and Environmental Policy, 2015
    Co-Authors: Aurora De Fátima Sánchez-bautista, José Ezequiel Santibañez-aguilar, Fabricio Nápoles-rivera, Medardo Serna-gonzález, José María Ponce-ortega, Mahmoud M. El-halwagi
    Abstract:

    This paper presents a multi-criteria Optimization Formulation for the optimal design of a water-heating system for homes. The proposed model accounts for the available solar radiation in the specific place where the solar collector is installed and the hot water demands. The goal is to target economic and environmental objectives by optimizing the design and operating conditions including the optimal hot water storage and distribution. The proposed model is applied to several scenarios for homes with different inhabitants and in various cities in Mexico. The results show that the location has significant effects on the optimal design and operation of the water-heating solar system.

Christopher A. Mattson - One of the best experts on this subject based on the ideXlab platform.

  • Usage scenarios for design space exploration with a dynamic multiobjective Optimization Formulation
    Research in Engineering Design, 2013
    Co-Authors: S. K. Curtis, B. J. Hancock, Christopher A. Mattson
    Abstract:

    In a recent publication, we presented a new strategy for engineering design and Optimization, which we termed Formulation space exploration. The Formulation space for an Optimization problem is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into this new space, the solution to any Optimization problem is no longer predefined by the Optimization problem Formulation. This method allows a designer to both diverge the design space during conceptual design and converge onto a solution as more information about the design objectives and constraints becomes available. Additionally, we introduced a new way to formulate multiobjective Optimization problems, allowing the designer to change and update design objectives, constraints, and variables in a simple, fluid manner that promotes exploration. In this paper, we investigate three usage scenarios where Formulation space exploration can be utilized in the early stages of design when it is possible to make the greatest contributions to development projects. Specifically, we look at Formulation space boundary exploration, Pareto frontier generation for multiple concepts in the Formulation space, and a new way to perform targeted boundary expansion. The benefits of these methods are illustrated with the conceptual design of an impact driver.

  • Divergent exploration in design with a dynamic multiobjective Optimization Formulation
    Structural and Multidisciplinary Optimization, 2013
    Co-Authors: S. K. Curtis, B. J. Hancock, Christopher A. Mattson, P. K. Lewis
    Abstract:

    Formulation space exploration is a new strategy for multiobjective Optimization that facilitates both divergent exploration and convergent Optimization during the early stages of design. The Formulation space is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem Formulations. By extending a computational search into the Formulation space, the solution to an Optimization problem is no longer predefined by any single problem Formulation, as it is with traditional Optimization methods. Instead, a designer is free to change, modify, and update design objectives, variables, and constraints and explore design alternatives without requiring a concrete understanding of the design problem a priori. To facilitate this process, we introduce a new vector/matrix-based definition for multiobjective Optimization problems, which is dynamic in nature and easily modified. Additionally, we provide a set of exploration metrics to help guide designers while exploring the Formulation space. Finally, we provide an example to illustrate the use of this new, dynamic approach to multiobjective Optimization.