scholarly journals EXPERT SYSTEM TO CREATE BUILDING DESIGN SCHEME / EKSPERTINĖ SISTEMA STATINIO KONSTRUKCINEI SCHEMAI KURTI

2013 ◽  
Vol 5 (6) ◽  
pp. 601-604
Author(s):  
Žilvinas Steckevičius ◽  
Darius Mačiūnas ◽  
Elena Glėbienė ◽  
Renata Birbalaitė
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Expert System ◽  
Optimal Design ◽  
Finite Difference ◽  
Building Design ◽  
Material Strength ◽  
Design Elements ◽  
Design Scheme ◽  
Linear Load

In this paper the technology for creation of optimal design scheme for building is presented. Optimization of design scheme is based on genetic algorithm. Rectangular perimeter of single-storey structure with a linear load in all its locations is investigated. In such case, finite element, finite difference and other methods are not necessary – in order to evaluate the stress of design elements it is sufficient to use formulas of material strength. Santrauka Šiame darbe apžvelgta optimalios konstrukcinės schemoskūrimo technologija, naudojant genetinį optimizavimo algoritmą.Nagrinėjama stačiakampio perimetro vieno aukšto konstrukcijasu tolygiąja apkrova visose jos vietose. Šiuo atveju nebūtina naudotibaigtinių elementų, baigtinių skirtumų ar kitų metodų. Norintįvertinti konstrukcijos elementų įtempius, užtenka medžiagųatsparumo formulių.

Structural Optimization Scheme for Horizontal Filtering Tank

2014 ◽  
Vol 577 ◽  
pp. 310-313
Author(s):  
Ping Yang ◽  
Zhou De Qu ◽  
Min Li
Keyword(s):  
Finite Element ◽  
Optimal Design ◽  
Finite Element Model ◽  
Element Model ◽  
Structural Instability ◽  
Optimization Scheme ◽  
Design Scheme ◽  
Operation Process ◽  
The Impact ◽  
The Finite Element Model

Based on the impact of some horizontal filtering tank’s instability in operation process on production, the present paper discusses the optimal design scheme for horizontal filtering tank structure with the help of finite element. Theoretical guidance will be given to enterprise from the perspective of finite element for the purpose of improving the horizontal filtering tank through constructing the finite element model for horizontal filtering tank with Creo parametric software, conducting simulation with workbench software[1] and finally arriving at the reasonable design scheme after analysis, thus avoiding the structural instability caused by the over-constraint of structural leg support beam and filter plate under-constraint.

Structural Design Optimization of Side/Rear Impact Guards Using a Coupled Genetic Algorithm Finite Element Method

2004 ◽  
Author(s):  
De-Shin Liu ◽  
Nan-Chun Lin ◽  
Chao-Chin Huang ◽  
Yin-Lee Meng
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Optimal Design ◽  
Computational Time ◽  
Design Parameters ◽  
Fe Model ◽  
Passenger Cars ◽  
Rear Impact ◽  
Structural Design Optimization ◽  
Energy Absorbing

Underride protective structure can reduce serious injures when passenger cars collide with the rear end or side of the heavy vehicle. This paper describes the use of Genetic Algorithm (GA) coupled with a dynamic, inelastic and large deformation finite element (FE) code LS-DYNA to search optimal design of the Side/Rear impact guards. In order to verify the accuracy of the FE model, the simulation results were compared with real experiments follow with the regulation ECE R73. The validated FE model then used to study the optimal design base on under running distance and total amount of energy absorbing capacity. The results from this study shown that this newly developed method not only can found multi-objective design parameters but also can reduce computational time significantly.

Behaviors of Composite Circular Struts in Space Environment: Analyses and Experiments

2004 ◽  
Vol 261-263 ◽  
pp. 797-802
Author(s):  
Chul Kim ◽  
Jong Heun Lee ◽  
J.H. Kim ◽  
Hoon Sang Choi
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Composite Materials ◽  
Optimal Design ◽  
Thermal Analyses ◽  
Space Environment ◽  
Stacking Sequence ◽  
Finite Element Analyses ◽  
Axial Deformation ◽  
Generic Algorithms

The optimal stacking sequence and wall thickness of the composite strut tubes were determined to minimize thermal strains during orbital operation using generic algorithms and finite element analyses. From the results of previous thermal analyses of composite struts with various stacking sequences, the axial deformation is a matter of prime importance. For this reason, the optimization focuses to minimize the axial strains. The balanced and symmetric stacking sequences are used to minimize the radial and the twisting deformations. The genetic algorithm is known to be very effective for the discrete optimization such as stacking sequences of composite materials. As a result, the thermal deformations of the strut with an optimal stacking sequence are almost zero. The optimal strut tube consists of 6 plies and the weight of a composite strut is 22.4% that of aluminum strut. Finite element analyses showed that the optimal design of composite strut tubes withstood combined launch loads without buckling and failure. To validate the analyses, four composite struts were fabricated and their thermal strains were measured under the temperature increase of 100°C. The thermal and vibration experiments showed excellent correlations with analytical results.

scholarly journals Finite Element Based Overall Optimization of Switched Reluctance Motor Using Multi-Objective Genetic Algorithm (NSGA-II)

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 576
Author(s):  
Mohamed El-Nemr ◽  
Mohamed Afifi ◽  
Hegazy Rezk ◽  
Mohamed Ibrahim
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Optimal Design ◽  
Switched Reluctance Motor ◽  
Design Parameters ◽  
Objective Functions ◽  
Nsga Ii ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Reluctance Motor

The design of switched reluctance motor (SRM) is considered a complex problem to be solved using conventional design techniques. This is due to the large number of design parameters that should be considered during the design process. Therefore, optimization techniques are necessary to obtain an optimal design of SRM. This paper presents an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Several dimensions of SRM are considered in the proposed design procedure including stator diameter, bore diameter, axial length, pole arcs and pole lengths, back iron length, shaft diameter as well as the air gap length. The multi-objective design scheme includes three objective functions to be achieved, that is, maximum average torque, maximum efficiency and minimum iron weight of the machine. Meanwhile, finite element analysis (FEA) is used during the optimization process to calculate the values of the objective functions. In this paper, two designs for SRMs with 8/6 and 6/4 configurations are presented. Simulation results show that the obtained SRM design parameters allow better average torque and efficiency with lower iron weight. Eventually, the integration of NSGA-II and FEA provides an effective approach to obtain the optimal design of SRM.

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