摘要 :
Multi-disciplinary analysis and optimization (MDAO) has been a long-standing goal in the aerospace community. In order to employ MDAO effectively, one needs to be able to compute the sensitivity of the objective function with resp...
展开
Multi-disciplinary analysis and optimization (MDAO) has been a long-standing goal in the aerospace community. In order to employ MDAO effectively, one needs to be able to compute the sensitivity of the objective function with respect to the driving parameters in a robust and efficient manner. Over the past decade there have been considerable efforts towards the generation of "adjoint" versions of flow solvers in order to help in this process. Unfortunately, the corresponding efforts have not been expended in the geometry and grid generation processes, especially when the geometries are generated parametrically with a modern computer-aided design (CAD) or CAD-like system. Contained herein is a pair of complementary techniques for computing configuration sensitivities directly on parametric, CAD-based geometries. One technique computes the configuration sensitivity analytically by differentiating the geometry-generating process; the other employs a new finite-difference technique that overcomes the difficulties previously encountered. Modifications to the Engineering Sketch Pad (ESP) (which is built on top of OpenCSM, EGADS, and OpenCASCADE) are described. Then the use of these configuration sensitivities in the computation of the sensitivity of grid-points is discussed. The results of these new techniques are shown on several configurations.
收起
摘要 :
Multi-disciplinary analysis and optimization (MDAO) has been a long-standing goal in the aerospace community. In order to employ MDAO effectively, one needs to be able to compute the sensitivity of the objective function with resp...
展开
Multi-disciplinary analysis and optimization (MDAO) has been a long-standing goal in the aerospace community. In order to employ MDAO effectively, one needs to be able to compute the sensitivity of the objective function with respect to the driving parameters in a robust and efficient manner. Over the past decade there have been considerable efforts towards the generation of "adjoint" versions of flow solvers in order to help in this process. Unfortunately, the corresponding efforts have not been expended in the geometry and grid generation processes, especially when the geometries are generated parametrically with a modern computer-aided design (CAD) or CAD-like system. Contained herein is a pair of complementary techniques for computing configuration sensitivities directly on parametric, CAD-based geometries. One technique computes the configuration sensitivity analytically by differentiating the geometry-generating process; the other employs a new finite-difference technique that overcomes the difficulties previously encountered. Modifications to the Engineering Sketch Pad (ESP) (which is built on top of OpenCSM, EGADS, and OpenCASCADE) are described. Then the use of these configuration sensitivities in the computation of the sensitivity of grid-points is discussed. The results of these new techniques are shown on several configurations.
收起
摘要 :
Geometric models are central to the analysis and design of complex configurations, such as aerospace vehicles. As models expand to include more of the vehicle components, and to include more than one discipline, they become very c...
展开
Geometric models are central to the analysis and design of complex configurations, such as aerospace vehicles. As models expand to include more of the vehicle components, and to include more than one discipline, they become very complex and hard to manage. This makes understanding the linkages between components for a single discipline, or understanding the linkages between the various discipline analysis for a single component, very difficult. This problem is compounded further when one realizes that the design process involves a series of sub-models (for any component and/or discipline) that evolve over time, in which the design is changed or fidelity is enhanced; these various versions must also be managed. Described herein is a new management scheme that directly attacks this problem. It centers around a set of user-defined component files which define the geometric models of the components that are needed by various analyses required for design. After describing the basic ideas of the new management scheme, it is demonstrated on a transport configuration. Then tools that a user can employ to understand a model are described. All this is brought together in an exercise that converts a legacy (dusty-deck) model into the new management scheme.
收起
摘要 :
Aerospace vehicle design can be described as an evolutionary process of gathering information to make informed decisions. Meticulous application of this process involves numerous simulations covering many disciplines and fidelity ...
展开
Aerospace vehicle design can be described as an evolutionary process of gathering information to make informed decisions. Meticulous application of this process involves numerous simulations covering many disciplines and fidelity levels. A design team needs to be able to easily increase or decrease fidelity as they gather more information about a particular design. To this end a geometry system that can support multi-disciplinary, multi-fidelity analysis from a single source is required. The Computational Aircraft Prototype Syntheses (CAPS), which is a part of the Engineering Sketch Pad (ESP), satisfies the above by combining proven computational geometry, meshing, and analyses model generation techniques into a complete browser-based, client-server environment that is accessible to the entire design team of an aerospace vehicle. CAPS links analysis and meshing disciplines to any ESP geometry model via dynamically-loadable Analysis Interface Module (AIM) plugins. CAPS is accessed from either a browser-based user interface and or Multi-Disciplinary Analysis and Optimization (MDAO) framework through a programing interface. In this paper we describe the fundamental building blocks of CAPS and ESP. The paradigm shift of creating geometry for multi-fidelity design is described in detail and represented in ESP scripts. We then demonstrate the use of this multi-fidelity geometry to support multi-fidelity, multi-physics analysis including discipline coupling.
收起
摘要 :
Aerospace vehicle design can be described as an evolutionary process of gathering information to make informed decisions. Meticulous application of this process involves numerous simulations covering many disciplines and fidelity ...
展开
Aerospace vehicle design can be described as an evolutionary process of gathering information to make informed decisions. Meticulous application of this process involves numerous simulations covering many disciplines and fidelity levels. A design team needs to be able to easily increase or decrease fidelity as they gather more information about a particular design. To this end a geometry system that can support multi-disciplinary, multi-fidelity analysis from a single source is required. The Computational Aircraft Prototype Syntheses (CAPS), which is a part of the Engineering Sketch Pad (ESP), satisfies the above by combining proven computational geometry, meshing, and analyses model generation techniques into a complete browser-based, client-server environment that is accessible to the entire design team of an aerospace vehicle. CAPS links analysis and meshing disciplines to any ESP geometry model via dynamically-loadable Analysis Interface Module (AIM) plugins. CAPS is accessed from either a browser-based user interface and or Multi-Disciplinary Analysis and Optimization (MDAO) framework through a programing interface. In this paper we describe the fundamental building blocks of CAPS and ESP. The paradigm shift of creating geometry for multi-fidelity design is described in detail and represented in ESP scripts. We then demonstrate the use of this multi-fidelity geometry to support multi-fidelity, multi-physics analysis including discipline coupling.
收起
摘要 :
There has been a tendency in the last decade to transition from single-discipline to multi-disciplinary analysis and design; this trend has been hastened by the increased availability of analysis and optimization frameworks that m...
展开
There has been a tendency in the last decade to transition from single-discipline to multi-disciplinary analysis and design; this trend has been hastened by the increased availability of analysis and optimization frameworks that manage the workflow. But one of the enabling technologies that is needed has not received much attention: that is, the need to transfer information from the surface of one representation to another, with particular emphasis on transferring the data conservatively. Described herein is a new method for performing such transfers. It is based upon two key technologies: a universal view of solver discretizations and a new optimization-enabled conservative fitting technique. The scheme is fully described and demonstrated in one dimension; then the extension to two dimensions is discussed along with results.
收起
摘要 :
There has been a tendency in the last decade to transition from single-discipline to multi-disciplinary analysis and design; this trend has been hastened by the increased availability of analysis and optimization frameworks that m...
展开
There has been a tendency in the last decade to transition from single-discipline to multi-disciplinary analysis and design; this trend has been hastened by the increased availability of analysis and optimization frameworks that manage the workflow. But one of the enabling technologies that is needed has not received much attention: that is, the need to transfer information from the surface of one representation to another, with particular emphasis on transferring the data conservatively. Described herein is a new method for performing such transfers. It is based upon two key technologies: a universal view of solver discretizations and a new optimization-enabled conservative fitting technique. The scheme is fully described and demonstrated in one dimension; then the extension to two dimensions is discussed along with results.
收起
摘要 :
Within the multi-disciplinary analysis and optimization community, there is a strong need for browser-based tools that provide users with the ability to visualize and interact with complex three-dimensional configurations. This ne...
展开
Within the multi-disciplinary analysis and optimization community, there is a strong need for browser-based tools that provide users with the ability to visualize and interact with complex three-dimensional configurations. This need is particularly acute when the designs involve shape- and/or feature-based optimizations. Described herein is a family of open-sources software products that provides such a capability. At the top is a browser-based system, called the Engineering Sketch Pad (ESP), which provides the user the ability to interact with a configuration by building and/or modifying the design parameters and feature tree that define the configuration. ESP is built both upon the Web Viewer (which is a WebGL-based visualizer for three-dimensional configurations and data) and upon OpenCSM (which is a constructive solid modeler; it in turn is built upon the EGADS and OpenCASCADE systems). Each of these open-source software components are described as well as the interactions amongst them.
收起
摘要 :
Within the multi-disciplinary analysis and optimization community, there is a strong need for browser-based tools that provide users with the ability to visualize and interact with complex three-dimensional configurations. This ne...
展开
Within the multi-disciplinary analysis and optimization community, there is a strong need for browser-based tools that provide users with the ability to visualize and interact with complex three-dimensional configurations. This need is particularly acute when the designs involve shape- and/or feature-based optimizations. Described herein is a family of open-sources software products that provides such a capability. At the top is a browser-based system, called the Engineering Sketch Pad (ESP), which provides the user the ability to interact with a configuration by building and/or modifying the design parameters and feature tree that define the configuration. ESP is built both upon the Web Viewer (which is a WebGL-based visualizer for three-dimensional configurations and data) and upon OpenCSM (which is a constructive solid modeler; it in turn is built upon the EGADS and OpenCASCADE systems). Each of these open-source software components are described as well as the interactions amongst them.
收起
摘要 :
Efficient multi-disciplinary analysis and optimization (MDAO) of aerospace vehicles is enabled by the generation of parametric, feature-based models. Many systems for generating these vehicles have been developed over the past dec...
展开
Efficient multi-disciplinary analysis and optimization (MDAO) of aerospace vehicles is enabled by the generation of parametric, feature-based models. Many systems for generating these vehicles have been developed over the past decades, but most of these systems focus on the development of models that are well suited to the manufacturing process. Recently, the Engineering Sketch Pad (ESP) was introduced whose expressed purpose is the generation of models for aerospace design and analysis. Three of the key features of ESP are its ability to develop multiple, linked models for use throughout the design process, to utilize user-defined features that are central to aerospace vehicles (such as airfoils, flaps, and spoilers), and to compute analytic sensitivities for optimization and uncertainty quantification. Contained herein is a description of ESP, including those components that directly support the above. In particular, the use of ESP to generate models within a single discipline that are used in the conceptual, preliminary, and final design stages is reviewed. Similarly, multiple linked models in cooperating disciplines are also discussed. These concepts are demonstrated on a sample transport configuration.
收起
原文获取