In this study, we design a lightweight antenna-supporting structure for a vehicle-mounted radar system using a multiphase design exploration method. In the first phase of the approach, structural topology within a given design domain is optimized in order to reduce the weight and increase the structural integrity applying various design scenarios, which provides several preliminary structural layouts. Inspecting the commonalities and differences of the preliminary layouts, key shape (i.e., geometry) parameters in an initial layout to be further explored are chosen. In the second phase, design variables, the chosen shape parameters and properties of its material are concurrently explored to satisfy the given system requirements. For the concurrent design exploration of the materials and structures, the inductive design exploration method is employed for obtaining feasible ranged sets of design variables, instead of a single optimum solution. In this way, a designer may simply make a robust choice among the feasible sets under various sources of uncertainties and multiple performance requirements.
The design of complex engineering systems requires that the problem is decomposed into subproblems of manageable size. From the perspective of decision-based design (DBD), typically this results in a set of hierarchical decisions. It is critically important for computational frameworks for engineering system design to be able to capture and document this hierarchical decision-making knowledge for reuse. Ontology is a formal knowledge modeling scheme that provides a means to structure engineering knowledge in a retrievable, computer-interpretable, and reusable manner. In our earlier work, we have created ontologies to represent individual design decisions (selection and compromise). Here, we extend the selection and compromise decision ontologies to an ontology for hierarchical decisions. This can be used to represent workflows with multiple decisions coupling together. The core of the proposed ontology includes the coupled decision support problem (DSP) construct, and two key classes, namely, Process that represents the basic hierarchy building blocks wherein the DSPs are embedded, and Interface to represent the DSP information flows that link different Processes to a hierarchy. The efficacy of the ontology is demonstrated using a portal frame design example. Advantages of this ontology are that it is decomposable and flexible enough to accommodate the dynamic evolution of a process along the design timeline.
The Decision Support Problem (DSP) construct is anchored in the notion that design is fundamentally a decision making process. Key is the concept of two types of decisions (namely, selection and compromise) and that any complex design can be represented through modelling a network of compromise and selection decisions. In a computational environment the DSPs are modeled as decision templates. In this paper, modular, executable, reusable decision templates are proposed as a means to effect design and to archive design-related knowledge on a computer. In the context of the compromise Decision Support Problem (cDSP) we address two questions: 1. What are the salient features for facilitating the reuse of design decision templates? 2. What are the salient features that facilitate maintaining model consistency when reusing design decision templates? Here, the first question is answered by the identification of reuse patterns in which specific modifications of the existing cDSP templates are made to adapt to new design requirements, and the second question is answered by developing an ontology-based cDSP template representation method in which a rule-based reasoning mechanism is used for consistency checking. Effectiveness of the ontology-based cDSP representation and reuse is demonstrated for the redesign of a pressure vessel.
It is efficacious to capture and represent the knowledge for decision support in engineering design. Ontology is a promising knowledge modeling scheme in the engineering domain. In this paper, an ontology is proposed for capturing, representing and documenting the knowledge related to hierarchical decisions in the design of complex engineered systems. The ontology is developed based on the coupled Decision Support Problem (DSP) construct, taking into consideration the requirements for a computational model that represents a decision hierarchy. Key to the ontology is the concept of two classes, namely, Process which represents the basic hierarchy building blocks where the DSPs are embedded, and Interface which represents the DSP information flows that link different Processes to a hierarchy. The efficacy of the ontology is demonstrated using a portal frame design example.
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