Structural modelling and optimisation of large scale systems

: Modeling large scale systems with natural and artificial components requires storage of voluminous amounts of knowledge/information as well as computing speed for simulations to provide reliable answers in reasonable time. Computing technology is becoming powerful enough to support such high performance modeling and simulation. This report proposes a high performance simulation based optimization environment to support the design and modeling of large scale systems with high levels of resolution, and represents the results of contract F3O602-95-C-O25O, Methodology for Simulation Model Abstraction.

In this paper, a new decomposition–coordination framework is presented for two-level optimal control of large-scale nonlinear systems. In the proposed approach, decomposition is performed by defining an interaction vector, while coordination is based on a new interaction prediction approach. In the first level, sub-problems are solved for nonlinear dynamics using a gradient method, while in the second level, the coordination is done using the gradient of coordination errors. This is in contrast to the conventional gradient-type coordination schemes, where they use the gradient of Lagrangian function. It is shown that the proposed decomposition–coordination framework considerably reduces the number of iterations. Moreover, compared to the substitution-type coordination approaches which are well known for their fast convergence rates and limited convergence regions, the proposed approach is robust with respect to parameters’ variation in addition to its good convergence rate. The robustness and the convergence rate of the proposed approach in compare to the costate prediction method are shown through simulations of a benchmark problem. The results are also compared to the ones obtained using centralized approach.

Small turbojet engines represent a special class of turbine driven engines. They are suitable for scientific purposes and research of certain thermodynamic processes ongoing in turbojet engines. Moreover such engines can be used for research in the area of alternative fuels and new methods of digital control and measurement. Our research, which is also presented in this article, is headed toward these aims. We evaluate and propose a system of digital measurement of a particular small turbojet engine - MPM 20. Such engine can be considered as highly non-linear large scale system. According to obtained data and experiments we propose different model models of the engine and design of situational control algorithms for the engine with use of certain methods of artificial intelligence as new methods of control and modeling of large scale systems.

Hierarchical analyses of water resources systems: modeling and optimization of large-scale systems: Yacov Y. Habnes McGraw-Hill, New York, 1977, £23.25

A two-level structural model for large scale systems

Most large scale systems manifest significant cross-coupling effects and operate over a wide region. Besides, mathematical models of such large scale systems often exhibit substantial deviation from the real-time model, which renders the static stimuli based emotional learning-based controller unreliable for practical purposes. In this correspondence, an adaptation based multi-variable stimuli design is pro-pounded which manifests the model uncertainties and the coupling effects associated with large scale systems. The proposed strategy is validated on a Quadruple Tank System in the non-minimum phase operating mode. The effectiveness of the proposed approach is established by comparing its performance with that of a static stimulus-based design for various levels of plant uncertainty.

Decentralized optimization of a chemical process by a feasible method

Commercial software Patran/Nastran and the developed Engineering System for Structural Optimization Software ESSOSII were used to demonstrate a structural modeling, analysis and optimization procedure for a practical spacecraft design. The designed spacecraft is a geosynchronous three axis stabilized communication satellite. With pre-processor Patran, the structural components were mainly simulated as laminated honeycomb panels which possess efficient stiffness. The static and dynamic analyses were conducted with Nastran to find the maximum stress and displacement as well as the basic frequencies and corresponding modes of the structural model. Some analysis results such as frequencies of initial structure were used as limitation values of constraints in the structural optimization procedure. The facesheet thickness and sandwich heights of the honeycomb panels were chosen as design variables to minimize the objective function corresponding to the whole structural satellite weight. The Sensitivity Analysis and the Two-level Multipoint Optimization method helped to reach several weight minimum designs of the spacecraft structure under different conditions. It can be seen the initial design is improved from the final results. The present work also shows the design procedure is reasonable for practical engineering problem.

We propose a reduced-space interior-point approach to nonlinear optimization problems with general inequality constraints. It is an extension of the quasi-sequential approach to dynamic optimization of large-scale systems. Inequality constraints are formed by adding slack variables to an equality constrained barrier (interior-point) problem which is solved by a range space step and a null space step in every iteration. Mathematical derivations and computation schemes are presented. We take a highly nonlinear parameter estimation problem as an example to demonstrate the effectiveness of this approach. The result is compared with the full space approach in terms of overall CPU time and number of iterations.

This report covers the research progress made during the calendar year 1992. The new results obtained during this period are described, keyed to the references listed on the last two pages of this report.

Achieving ultra-large-scale software systems will necessarily require new and special development processes. This position paper suggests overall structure of a process model to develop and maintain system of systems similar to Ultra Large Scale (ULS) systems. The proposed process model will be introduced in details and finally, we will evaluate it considering CMMI-ACQ which has been presented by SEI for acquirer organizations.

An interoperability model for ultra large scale systems

With the rapid development of computers and technology in the 20th century, the topological optimisation (TO) method has spread worldwide in various fields.This novel structural optimisation approach has been applied in many disciplines, including architectural form-finding.Especially Bi-directional Evolutionary Structural Optimisation (BESO), which was proposed in the 1990s, is widely used by thousands of engineers and architects worldwide to design innovative and iconic buildings.To integrate topological optimisation with artificial intelligence (AI) algorithms and to leverage its power to improve the diversity and efficiency of the BESO topological optimisation method, this research explores a non-iterative approach to accelerate the topology optimisation process of structures in architectural form-finding via conditional generative adversarial networks (GANs), which is named as OptiGAN.Trained with topological optimisation results generated through Ameba software, OptiGAN is able to predict a wide range of optimised architectural and structural designs under defined conditions.

A scheme for model reduction of large scale systems based on the singular value decomposition incorporating model upgrading technique for a rank 1 addition to the aggregation matrix is provided.

PurposeThis paper aims to summarize design rules based on the process characteristics of selective laser melting (SLM) and structural optimization and apply the design rules in the lightweight design of an aluminum alloy antenna bracket. The design goal is to reduce 30 per cent of the weight while maintaining the stress levels in the original part.Design/methodology/approachTo reduce weight as much as possible, the titanium alloy with higher specific strength was selected during the process of optimization. The material distribution of the bracket was improved by the topology optimization design. The redesign for SLM was used to obtain an optimization model, which was more suitable for SLM. The component performance was improved by shape optimization. The modal analysis data of the structural optimization model were compared with those of the stochastic lightweight model to verify the structural optimization model. The scanning data were compared with those of the original model to verify whether the model was suitable for SLM.FindingsStructural optimization design for antenna bracket realized the mass decrease of 30.43 per cent and the fundamental frequency increase of 50.18 per cent. The modal analysis data of the stochastic lightweight model and the structural optimization model indicated that the optimization performance of structural optimization method was better than that of the stochastic lightweight method. The comparison results between the scanning data of the forming part and the original data confirmed that the structural optimization design for SLM lightweight component could achieve the desired forming accuracy.Originality/valueThis paper summarizes geometric constraints in SLM and derives design rules of structural optimization based on the process characteristics of SLM. SLM design rules make structural optimization design more reasonable. The combination of structural optimization design and SLM can improve the performance of lightweight antenna bracket significantly.