A knowledge-based geometry repair system for robust parametric CAD models

In modern multi-objective design optimization (MDO) an effective geometry engine is becoming an essential tool and its performance has a significant impact on the entire MDO process. Building a parametric geometry requires difficult compromises between the conflicting goals of robustness and flexibility. This article presents a method of improving the robustness of parametric geometry models by capturing and modeling engineering knowledge with a support vector regression surrogate, and deploying it automatically for the search of a more robust design alternative while trying to maintain the original design intent. Design engineers are given the opportunity to choose from a range of optimized designs that balance the ‘health’ of the repaired geometry and the original design intent. The prototype system is tested on a 2D intake design repair example and shows the potential to reduce the reliance on human design experts in the conceptual design phase and improve the stability of the optimization cycle. It also helps speed up the design process by reducing the time and computational power that could be wasted on flawed geometries or frequent human intervention

Second-order cone programming formulations for a class of problems in structural optimization

This paper provides efficient and easy to implement formulations for two problems in structural optimization as second-order cone programming (SOCP) problems based on the minimum compliance method and derived using the principle of complementary energy. In truss optimization both single and multiple loads (where we optimize the worst-case compliance) are considered. By using a heuristic which is based on the SOCP duality we can consider a simple ground structure and add only the members which improve the compliance of the structure. It is also shown that thickness optimization is a problem similar to truss optimization. Examples are given to illustrate the method developed in this pape

Totems

In modern multi-objective design optimization (MDO) an effective geometry engine is becoming an essential tool and its performance has a significant impact on the entire MDO process. Building a parametric geometry requires difficult compromises between the conflicting goals of robustness and flexibility. This article presents a method of improving the robustness of parametric geometry models by capturing and modeling engineering knowledge with a support vector regression surrogate, and deploying it automatically for the search of a more robust design alternative while trying to maintain the original design intent. Design engineers are given the opportunity to choose from a range of optimized designs that balance the ‘health’ of the repaired geometry and the original design intent. The prototype system is tested on a 2D intake design repair example and shows the potential to reduce the reliance on human design experts in the conceptual design phase and improve the stability of the optimization cycle. It also helps speed up the design process by reducing the time and computational power that could be wasted on flawed geometries or frequent human intervention

Weld sequence optimization: the use of surrogate models for solving sequential combinatorial problems

The solution of combinatorial optimization problems usually involves the consideration of many possible design configurations. This often makes such approaches computationally expensive, especially when dealing with complex finite element models. Here a surrogate model is proposed that can be used to reduce substantially the computational expense of sequential combinatorial finite element problems. The model is illustrated by application to a weld path planning problem

Ages of the Pliocene-Pleistocene Alexandra and Ngatutura Volcanics, western North Island, New Zealand, and some geological implications

The Alexandra and Ngatutura Volcanics are the two southernmost of the Pliocene-Quaternary volcanic fields of western and northern North Island, New Zealand, northwest of Taupo Volcanic Zone TVZ. The Ngatutura Basalts are an alkalic basaltic field comprising monogenetic volcanoes. The Alexandra Volcanics consist of three basaltic magma series: an alkalic (Okete Volcanics), calcalkalic (Karioi, Pirongia, Kakepuku, and Te Kawa Volcanics), and a minor potassic series. Twenty new K-Arages are presented for the Alexandra Volcanics and 9 new ages for the Ngatutura Basalts. Ages of the Alexandra Volcanics range from 2.74 to 1 .60 Ma, and the ages of all three magma series overlap. Ages of the Ngatutura Basalts range from 1 .83 to 1.54 Ma. Each basaltic field has a restricted time range and there is a progressive younging in age of the basaltic fields of western North Island from the Alexandra Volcanics in the south, to Ngatutura, to South Auckland, and then to the Auckland field in the north. Neither of the Alexandra nor Ngatutura Volcanics shows any younging direction of their volcanic centres or any age pattern within their fields, and there is no systematic variation in age with rock composition. Any correlation of age with degree of erosion of volcanic cones is invalid for these basaltic fields; instead, the degree of erosion may be controlled by the lithology of the cones and possibly by the extent of preservation offered by the thick cover deposits of the Kauroa, Hamilton, and younger tephra beds. Stratigraphic relations have enabled the earliest member of the Kauroa Ash Formation to be dated at 2.3 Ma. This formation represents a series of widespread rhyolitic plinian and ignimbrite eruptions probably derived from TVZ and initiated during the Late Pliocene

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB

A formulation of thickness optimization for plane stress

Thickness optimization can be considered as a case of sizing optimization for plane structures. It canalso be used as an intermediate step for topology problems, i.e. we can eliminate the parts where thethickness tends to be zero. This paper is concerned with the case of plane stress structures coupled withthe finite element method. The aim is to present a formulation of this problem as a case of second-ordercone programming which is a standard form of mathematical programming. The advantage is that,on the one hand, all that the engineer has to do is to compute elemental data, and on the other, largediscretized structures can be optimized accurately due to the efficiency of the proposed formulation.Different types of elements regarding the thickness field are considered

Preliminary fan-blade design using intermediate response approximations

A midrange approximation method for design optimization is formulated. This utilizes intermediate response variables, amenable to simple polynomial representation, to provide a reasonable approximation over a trust region. It has applications to computationally expensive, nonlinear optimization problems where a designer’s knowledge may be exploited to select appropriate intermediate variables. Application to the preliminary structural design of a fan blade is illustrated in two case studies; results for a global optimization strategy and a direct search have been included for comparison. Significant improvement in the number of function calls necessary to identify a local optimum is demonstrated in the case studies considered

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB