Combined Optimization Strategy Research Articles

Thermal-Mechanical Optimization of Folded Core Sandwich Panels for Thermal Protection Systems of Space Vehicles

The integrated thermal protection system (ITPS) is a complicated system that addresses both mechanical and thermal considerations. An M-pattern folded core sandwich panel packed with low-density insulation material provides inherently low mass for a potential ITPS panel. Herein, we identify the most influential geometric parameters and establish a viable, computationally efficient optimization procedure. Variables considered for optimization are geometric dimensions of the ITPS, while temperature and deflection are taken as constraints. A one-dimensional (1D) thermal model based on a modified form of the rule of mixtures was established, while a three-dimensional (3D) model was adopted for linear static analyses. Parametric models were generated to facilitate a design of experiment (DOE) study, and approximate models using radial basis functions were obtained to carry out the optimization process. Sensitivity studies were first conducted to investigate the effect of geometric parameters on the ITPS responses. Then optimizations were performed for both thermal and thermal-mechanical constraints. The results show that the simplified 1D thermal model is able to predict temperature through the ITPS thickness satisfactorily. The combined optimization strategy evidently improves the computational efficiency of the design process showing it can be used for initial design of folded core ITPS.

The multiple objective optimization of high-speed rotor supported by magnetic bearing in BLDCM

In order to find an algorithm to get a better optimization result of high-speed rotor supported by magnetic bearing in BLDCM, we presented a multiple objective optimization results which included three algorithms' in this paper. They are the local Sequential Quadratic Program (SQP) algorithm, the global Genetic Algorithm (GA) and the combined optimization strategy algorithm which combines GA and SQP. The parametric optimization model of a 100 kW BLDCM supported by magnetic bearings was constituted with software ANSYS and an effective connection between software ANSYS and iSIGHT was used to execute the whole optimization process. To insure the best performance, mass and strength were chosen as the optimization goals, meanwhile, the static strength, dynamic modal, shape and magnetic force of the rotor subassembly were used as the main constrains. Six main dimensions of the subassembly were optimized. The optimization results indicated that the GA can get a higher optimization precision than the other two algorithms and the SQP was not effective in the optimization of magnetic suspended motor rotor subassembly. The GA's optimization result made the mass decrease 7.62 percent with the safe factor is 3.15. The 100 kW BLDCM supported by magnetic bearings was designed and fabricated; the multiple objective optimization results were verified by the prototype.

Automated Guide Vehicles Dynamic Scheduling Based on Annealing Genetic Algorithm

Dispatching automated guided vehicles (AGVs) is the common approach for AGVs scheduling in practice, the information about load arrivals in advance was not used to optimize the performance of the automated guided vehicles system (AGVsS). According to the characteristics of the AGVsS, the mathematical model of AGVs scheduling was established. A heuristic algorithm called Annealing Genetic Algorithm (AGA) was presented to deal with the AGVs scheduling problem,and applied the algorithm dynamically by using it repeatedly under a combined rolling optimization strategy. the performance of the proposed approach for AGVs scheduling was compared with the dispatching rules by simulation. Results showed that the approach performs significantly better than the dispatching rules and proved that it is really effective for AGVsS. DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.2481

What Shape Are Dolphins? Building 3D Morphable Models from 2D Images

3D morphable models are low-dimensional parameterizations of 3D object classes which provide a powerful means of associating 3D geometry to 2D images. However, morphable models are currently generated from 3D scans, so for general object classes such as animals they are economically and practically infeasible. We show that, given a small amount of user interaction (little more than that required to build a conventional morphable model), there is enough information in a collection of 2D pictures of certain object classes to generate a full 3D morphable model, even in the absence of surface texture. The key restriction is that the object class should not be strongly articulated, and that a very rough rigid model should be provided as an initial estimate of the “mean shape.” The model representation is a linear combination of subdivision surfaces, which we fit to image silhouettes and any identifiable key points using a novel combined continuous-discrete optimization strategy. Results are demonstrated on several natural object classes, and show that models of rather high quality can be obtained from this limited information.

Combined use of genetic algorithms and gradient descent optmization methods for accurate inverse permittivity measurement

A novel inverse transmission-line method for the complex permittivity determination of arbitrary shaped materials is presented. Complex permittivity is inferred by using an inverse calculation procedure, which is based on a combined optimization strategy of both genetic algorithms and the gradient descent method. The optimization procedure matches the measured and simulated complex scattering parameters' frequency behavior of materials within a WR340 waveguide. High accuracy and practical suitability are validated through experimental tests. The dielectric properties of PTFE and epoxy resin mixed with iron-oxide-doped fiberglass have been measured for different shapes and positions. Dielectric multilayer structures have been used to demonstrate that this technique is able to measure the individual permittivity of each element of the structure. Both two- and three-dimensional approaches have been carried out and their advantages and drawbacks discussed.

A Novel End-to-End Architecture for H.264 Video Streaming over the Internet

In this paper we propose a novel end-to-end architecture for H.264 unicast video streaming over the Internet. The proposed video streaming architecture is based primarily on a new transport layer protocol, the stream control transmission protocol (SCTP). We show that the network-friendly specification of H.264, and the novel technical characteristics of SCTP, when coupled together are able to provide a highly adaptive and flexible system for unicast video streaming. More specifically, we develop algorithms that handle at the transport layer the following functions concerning video packet transmission: retransmission policy, packet prioritization, implicit receiver feedback. We combine the above algorithms with an R-D optimization strategy at the encoder, that provides more options when adapting to bandwidth variations. This combined optimization strategy leads to more options concerning the streaming parameters. Finally, with simulation results we prove that our system is capable of maintaining good perceptual quality and TCP-friendliness under various loss conditions.

A Combined Control and Optimization System Used in Solvents Recovering Device

The solvents recovering process in lubrication oil production needs a lot of energy, and has large stagnancy, strong coupling, time delay and interference etc. To measure the quality of solvents on-line is difficult. How to assure the quality and save energy is discussed. A non-linear predictive control is proposed frrstly. Because the mathematical model used for energy optimization can't meet actual need, a combined modeling and optimization strategy is then proposed. Intelligent database, adaptive modeling, combined control and optimization, expert control and intelligent alarming etc. are used to improve the function of the device clearly. Actual production results prove that the system is a great success.

A combined strategy for optimization in nonlinear magnetic problems using simulated annealing and search techniques

A combined strategy for optimization of electromagnetic devices based on a two-stage scheme is described. Two different ways of implementing a simulated annealing algorithm, one for discrete and one for continuous variables, have been implemented and tested. The second one proved to be more reliable and problem-independent than the other. This technique was used in a combined optimization strategy in combination with a pattern search method. The combined strategy was tested versus analytical and numerical objective functions and showed good behavior, saving, in the best case, up to 70% of the iterations needed for a complete simulated annealing run. The combined strategy was also tested in magnet design problems, with both analytical objective functions and objective functions evaluated by means of finite element codes. The results obtained were encouraging in terms of the objective function values obtained and in the computer time needed. >

Optimized formulation of magnetic chitosan microspheres containing the anticancer agent, oxantrazole.

A combined emulsion/polymer cross-linking/solvent evaporation technique was used to prepare magnetic chitosan microspheres (MCM) containing the anticancer drug, oxantrazole. A central composite experimental design was used to simultaneously evaluate a variety of formulation factors on a number of response variables, such as the percentage of oxantrazole entrapped in the MCM. In association with the study design, statistical optimization procedures indicated the factors that significantly influence MCM preparation and what levels of the factors are needed to produce optimum MCM. Entrapment of anticancer agents into biodegradable microspheres is difficult because of low aqueous drug solubility and porosity of the particles. The latter effect was circumvented by a chitosan cross-linking step that resulted in approximately 3% (w/w) oxantrazole entrapment in the MCM via the optimization procedures. The combined formulation and statistical optimization strategy provide a basis to develop other microparticulate systems and led to a dosage form that can be used for future in vivo investigations.