Shape optimization on mufflers within a limited space volume is essential for industry, where the equipment layout is occasionally tight and the available space for a muffler is limited for maintenance and operation p...
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Shape optimization on mufflers within a limited space volume is essential for industry, where the equipment layout is occasionally tight and the available space for a muffler is limited for maintenance and operation purposes. To proficiently enhance the acoustical performance within a constrained space, the selection of an appropriate acoustical mechanism and optimizer becomes crucial. A multi-chamber side muffler hybridized with reverse-flow ducts which can visibly increase the acoustical performance is rarely addressed;therefore, the main purpose of this paper is to numerically analyze and maximize the acoustical performance of this muffler within a limited space. In this paper, the four-pole system matrix for evaluating the acoustic performance sound transmission loss (STL) is derived by using a decoupled numerical method. Moreover, a simulated annealing (SA) algorithm, a robust scheme in searching for the global optimum by imitating the softening process of metal, has been used during the optimization process. Before dealing with a broadband noise, the STL's maximization with respect to a one-tone noise is introduced for the reliability check on the SA method. Moreover, the accuracy check of the mathematical models with respect to various acoustical elements is performed. The optimal result in eliminating broadband noise reveals that the multi-chamber muffler with reverse-flow perforated ducts is excellent for noise reduction. Consequently, the approach used for the optimal design of the noise elimination proposed in this study is easy and effective.
This paper presents an approach by combining the genetic algorithm (GA) with simulated annealing (SA) algorithm for enhancing finite element (FE) model updating. The proposed algorithm has been applied to two typical ...
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This paper presents an approach by combining the genetic algorithm (GA) with simulated annealing (SA) algorithm for enhancing finite element (FE) model updating. The proposed algorithm has been applied to two typical rotor shafts to test the superiority of the technique. It also gives a detailed comparison of the natural frequencies and frequency response functions (FRFs) obtained from experimental modal testing, the initial FE model and FE models updated by GA, SA, and combination of GA and SA (GA-SA). The results concluded that the GA, SA, and GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, but the appropriate choice of the updating parameters and objective function is of great importance in the iterative process. Generally, the natural frequencies and FRFs obtained from FE model updated by GA-SA show the best agreement with experiments than those obtained from the initial FE model and FE models updated by GA and SA independently.
Dynamic facility layout problem (DFLP) considers flow over multiple time periods in an environment where material flow between departments changes over time. These changes render the current facility layout inefficien...
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Dynamic facility layout problem (DFLP) considers flow over multiple time periods in an environment where material flow between departments changes over time. These changes render the current facility layout inefficient and could increase material handling costs, which results in a need for dynamic layout models. But a key factor ignored for simplicity in the DFLP literature, is considering the effects of non-cooperating internal and external competitions on the mentioned changes in facility layout over time that sometimes results in main conflict of objectives/goals for these distinct decision makers. To the best our knowledge, the existing special literature did not cover this important assumption. Ignoring this main assumption resulted in the existing monopolistic models for DFLP that cannot satisfy the new needs in the nowadays competitive environments. Therefore, in this paper, a duopoly Bertrand non-cooperative game model is presented to consider the impacts of all conflicting factors on a DFLP for each period and three meta-heuristic algorithms are proposed to obtain Nash equilibrium for this model. The results obtained from solving some numerical examples with these algorithms show that the proposed simulated annealing algorithm is more effective than the others for the competitive dynamic facility layout problem.
Purpose - During any design phase, the associated process variations and uncertainties can cause the design to deviate from its expected performance. The purpose of this paper is to propose a robust design optimizatio...
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Purpose - During any design phase, the associated process variations and uncertainties can cause the design to deviate from its expected performance. The purpose of this paper is to propose a robust design optimization (RDO) strategy for the 3D grain design of a dual thrust solid rocket motor (DTRM) under uncertainties in design parameters. Design/methodology/approach - The methodology consists of design of 3D complex grain geometry and hybrid optimization approach through genetic algorithm, globally and simulated annealing, locally considering the uncertainties in design parameters. The robustness of optimized data is measured for a worst case parameter deviation using sensitivity analysis through stochastic Monte Carlo simulation considering variance of design parameters mean. Findings - The important achievement that can be associated with this methodology is its ability also to evaluate and optimize the propulsion system performance in a complex scenario of intricate 3D geometry under uncertainty. The study shows the objective function to maximize the average thrust in dual levels could be achieved by the proposed optimization technique while satisfying constraints conditions. Also, this technique proved to be a great help in reducing the design space for optimization and increasing the computational quality. Originality/value - This is the first paper to address the dual thrust solid rocket motor grain design under uncertainties using robust design and hybrid optimization approach.
In order to solve the detour problem at the end of Express delivery,and provide more convenient planning path for the distribution staff,in the genetic algorithm,the crossfactor is removed,and the simulated annealing ...
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In order to solve the detour problem at the end of Express delivery,and provide more convenient planning path for the distribution staff,in the genetic algorithm,the crossfactor is removed,and the simulated annealing acceptance criteria are used to determine the individuals entering the next generation population during the crossover and mutation,adjust each generation crossover and mutation to accept the probability of poor solution and avoid the population to stop *** simulation results show that the improved path planning algorithm not only effectively eliminates the phenomenon of the local optimal solution,but also shortens the algorithm to the original 1/4,the execution time to the original1/3,the Courier distribution total route is shortened by 10%,which has improved distribution efficiency.
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