Number Of Design Cycles Research Articles

Efficient stress‐constrained topology optimization using inexact design sensitivities

AbstractAn efficient computational approach to stress‐constrained topology optimization is presented. Using a multigrid‐preconditioned Krylov solver for the state and adjoint problems, the number of Krylov iterations is reduced significantly by enforcing early termination of the iterative solves. The criterion for early termination is based on the convergence of the design sensitivities with respect to Krylov iterations. Consequently, the progress of optimization is not affected by the inexact resolution of the state and adjoint problems. The proposed approach is demonstrated on several design problems that possess different characteristics of the maximum stress. Optimization results obtained with early termination show very good agreement with those obtained with an accurate direct solver—in terms of objective value, constrained maximum stress and overall number of design cycles. Savings of 80% in the number of Krylov iterations are achieved, compared to the number of iterations required to satisfy the force residual convergence criterion to a common tolerance. The approach is directly applicable to high‐resolution problems that are solved on parallel computational environments. A MATLAB code for reproducing the results is freely available at https://github.com/odedamir/topopt‐stress‐inexact‐sensitivities

RS-Satellites Propulsion Subsystem Performance Sizing Via Design Plane Technique, a Generic Method

Remote sensing satellites propulsion subsystem preliminary design based on performance sizing is discussed. The process is a fairly complicated one considering a variety of operational as well as performance requirements. This research aims to reduce the number of iterations required by the current practice to reach a compromise. It is based on a rapid-sizing method that helps lessen lengthy iteration cycles. The proposed technique, similar to such class of preliminary design processes, leads to an acceptable approximation that must be properly conveyed to other disciplines involved for further elaborations. With proper selection of design and performance parameters together with fundamental relations, design boundaries are established; while the role of boundaries is to limit the design space, and to minimize the number of design cycles as a result. With the help of a suitable case-study, we demonstrate the effectiveness of the approach. Further investigations might be necessary for the cases where a greater number of uncertainties are involved.

Topology optimization of planar truss structures with continuous element intersection and node stability constraints

This article presents a general nonlinear formulation for the topology optimization of planar truss structures. The novelty of this article is that element intersection is described in terms of a continuous intersection factor. The Heaviside function is used to map the element cross-sectional area to intersection properties. Therefore, the intersection feature is described by a continuous and differentiable function. The topology optimization model is hence set as a ground-structure method by simultaneously including constraints on element intersection and cinematic stability of nodes. The latter is also described by a continuous function. Three test cases are presented to demonstrate the validity of the proposed approach. Unlike mixed integer programming, the number of design cycles does not change much as the number of design variables increases.

Partial data reuse for nested loop computations: design space exploration for FPGA implementations

Automated compiler analyses and transformation techniques aim at improving design productivity of the mapping process of applications expressed in high-level programming languages to FPGAs. These transformations allow a compiler tool to reduce the number of design cycles and eliminate tedious and error-prone low-level transformations required in this mapping process, while still leading to good designs. Scalar replacement, also known as register promotion, is a very important data-oriented transformation that leads to designs that reduce the number of external memory accesses, and thus reduce execution time, at the expense of storage resource's. In this article we present a combination of loop transformation techniques, namely loop unrolling, loop splitting, and loop interchange with scalar replacement to enable partial data reuse on computations expressed by tightly nested loops pervasive in image processing algorithms. We describe a performance modelling in the presence of partial data reuse. Our experimental results reveal that our model accurately captures the non-trivial execution effects of pipelined implementations in the presence of partial data reuse due to the need to fill-up data buffers. The model thus allows a compiler to explore a large design space with high accuracy, ultimately allowing quickly it to find better designs than designs with limited manual search or brute-force approaches.

FLO/STRESS: an integrated software module to predict stress in electronic products

Software technology that predicts stress in electronic systems and packages, developed as part of TCS Programme, is described. The software is closely integrated within a thermal design tool providing the ability to simulate the coupled effects of airflow, temperature and stress on product performance. This integrated approach to analysis will help decrease the number of design cycles.

Genetic algorithm for the design of molecules with desired properties.

The design of molecules with desired properties is still a challenge because of the largely unpredictable end results. Computational methods can be used to assist and speed up this process. In particular, genetic algorithms have proved to be powerful tools with a wide range of applications, e.g. in the field of drug development. Here, we propose a new genetic algorithm that has been tailored to meet the demands of de novo drug design, i.e. efficient optimization based on small training sets that are analyzed in only a small number of design cycles. The efficiency of the design algorithm was demonstrated in the context of several different applications. First, RNA molecules were optimized with respect to folding energy. Second, a spinglass was optimized as a model system for the optimization of multiletter alphabet biopolymers such as peptides. Finally, the feasibility of the computer-assisted molecular design approach was demonstrated for the de novo construction of peptidic thrombin inhibitors using an iterative process of 4 design cycles of computer-guided optimization. Synthesis and experimental fitness determination of only 600 different compounds from a virtual library of more than 10(17) molecules was necessary to achieve this goal.