AN ADAPTIVE RBF METHOD FOR DESIGN OPTIMIZATION OF BUILDING STRUCTURES

Design of building structures has long been based on a trial-and-error iterative approach. Structural optimization provides practicing engineers an effective and efficient approach to replace the traditional design method. A numerical optimization algorithm, such as a gradient-based method or genetic algorithm (GA), can be applied, in conjunction with a finite element (FE) analysis program. The FE program is used to compute the structural responses, such as forces and displacements, which represent the design constraint functions. In this method, reading and writing the input/output files of the FE program and interface programming are required. Another method to perform structural optimization is to create an approximate constraint function, which involves implicit structural responses. This is referred to as a surrogate or metamodeling method. The structural responses can be expressed as approximate functions, based on a number of preselected sample points. In this study, an adaptive metamodeling method was studied and applied to a building structure. The FE analyses were first performed at the sample points, and metamodels were constructed. A gradient-based optimization algorithm was applied. Additional samples were generated and additional FE analyses were conducted so that the model accuracy could be improved, close to the optimal design points. This adaptive scheme was continued, until the objective function values converged. The method worked well and optimal designs were found within a few iterations.

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BUILDING STRUCTURE OPTIMIZATION BASED ON A HIGH-DIMENSIONAL MODEL REPRESENTATION APPROACH

Proceedings of International Structural Engineering and Construction ◽

10.14455/isec.2020.7(2).str-11 ◽

2020 ◽

Vol 7 (2) ◽

Author(s):

Qian Wang ◽

Joseph Nafash

Keyword(s):

Design Optimization ◽

Model Reduction ◽

Model Representation ◽

High Dimensional ◽

High Dimensional Model Representation ◽

Optimization Approach ◽

Building Structures ◽

Dimensional Model ◽

Gradient Based ◽

Structural Responses

In this study, a model reduction technique based on a high-dimensional model representation (HDMR) approach was investigated and applied to design optimization of building structures. Those structures have long been designed using engineering intuition and an iterative trial-and-error method. In order to evaluate structural responses, a finite element (FE) analysis code is generally required. Gradient-based numerical algorithms and evolutionary algorithms are widely available and can be adopted to the design optimization of structures. An alternative category of optimization methods relies on approximate objective or constraint functions that can be created using various interpolation or regression techniques. In this work, the model reduction was achieved using augmented radial basis functions (RBFs) as component functions of HDMR. After sample points were generated along each variable axis, detailed FE analyses were conducted to evaluate building responses, which were used for constructing RBF-HDMR models of structural responses. The optimization was performed using a standard gradient-based numerical method. The accuracy of the RBF-HDMR could be improved if the optimal design point was added as an additional sample point. One advantage of the proposed optimization approach was that the interface programming with any existing FE code was not necessary. To illustrative the application of the method, a high-rise building was studied and optimized in order to reduce the building’s global torsional responses. The proposed optimization method worked well for the example.

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STRUCTURAL OPTIMIZATION USING AN ADAPTIVE RBF APPROACH

Proceedings of International Structural Engineering and Construction ◽

10.14455/isec.res.2019.164 ◽

2019 ◽

Vol 6 (1) ◽

Author(s):

Erica Jarosch ◽

Qian Wang ◽

Lucas Schmotzer ◽

Yongwook Kim

Keyword(s):

Optimization Algorithm ◽

Optimization Method ◽

Multidisciplinary Optimization ◽

Engineering System ◽

Optimal Point ◽

Analysis And Design ◽

Gradient Based ◽

Sample Points ◽

Optimization Loop ◽

Nested Analysis

This paper presents an adaptive radial basis functions (RBFs) metamodeling method for design optimization of structures. Various numerical techniques have been developed and adopted in structural and multidisciplinary optimization. To evaluate responses of a structural or mechanical engineering system, finite element (FE) analyses are routinely used. An FE code shall be integrated with an optimization algorithm in a nested analysis and design of structures. Therefore, software input/output programming is required. A metamodeling method, on the contrary, expresses structural responses using an approximate function, so that the FE software is not directly coupled in the numerical optimization loop. Any optimization algorithm can be applied to find the optimal design, based on the explicit response functions. In this study, numerical examples were created and FE analyses were first performed at sample points. Subsequently, metamodels were constructed and a gradient-based optimization algorithm was applied. At the optimal point of one adaptive iteration, accuracy of the RBF metamodel was checked, and additional sample points were added to the sample pool to improve the model accuracy. The adaptive iterations continued, until the convergence of the objective function was achieved. The proposed optimization method worked well for a numerical example, and the optimal result was found within a few adaptive iterations.

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Research on the application of 3D reconstruction technology in traditional handicraft design

International Journal of Electrical Engineering Education ◽

10.1177/00207209211005274 ◽

2021 ◽

pp. 002072092110052

Author(s):

GuoLong Zhang

Keyword(s):

Poisson Equation ◽

Optimization Algorithm ◽

Three Dimensional ◽

Reconstruction Algorithm ◽

Social Production ◽

Design Constraint ◽

Reconstruction Process ◽

Key Steps ◽

Shielding Design ◽

Reconstruction Model

The use of computer technology for three-dimensional (3 D) reconstruction is one of the important development directions of social production. The purpose is to find a new method that can be used in traditional handicraft design, and to explore the application of 3 D reconstruction technology in it. Based on the description and analysis of 3 D reconstruction technology, the 3 D reconstruction algorithm based on Poisson equation is analyzed, and the key steps and problems of the method are clarified. Then, by introducing the shielding design constraint, a 3 D reconstruction algorithm based on shielded Poisson equation is proposed. Finally, the performance of two algorithms is compared by reconstructing the 3 D image of rabbit. The results show that: when the depth value of the algorithm is 11, the surface of the rabbit image obtained by the proposed optimization algorithm is smoother, and the details are more delicate and fluent; under different depth values, with the increase of the depth value, the number of vertices and faces of the two algorithms increase, and the optimal depth values of 3 D reconstruction are more than 8. However, the proposed optimization algorithm has more vertices, and performs better in the reconstruction process; the larger the depth value is, the more time and memory are consumed in 3 D reconstruction, so it is necessary to select the appropriate depth value; the shielding parameters of the algorithm have a great impact on the fineness of the reconstruction model. The larger the parameter is, the higher the fineness is. In a word, the proposed 3 D reconstruction algorithm based on shielded Poisson equation has better practicability and superiority.

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A modified simplex based direct search optimization algorithm for adaptive transversal FIR filters

Science Progress ◽

10.1177/00368504211025409 ◽

2021 ◽

Vol 104 (2) ◽

pp. 003685042110254

Author(s):

Armaghan Mohsin ◽

Yazan Alsmadi ◽

Ali Arshad Uppal ◽

Sardar Muhammad Gulfam

Keyword(s):

Optimization Algorithm ◽

Optimization Technique ◽

Fast Convergence ◽

Good Convergence ◽

Optimum Point ◽

Search Optimization ◽

Higher Dimensional ◽

Gradient Based ◽

Improved Accuracy ◽

Quadratic Cost Function

In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead optimization technique is widely used but it suffers from convergence issues in higher dimensional complex problems. Unlike the NM, in this proposed technique we have focused on two issues of the NM approach, one is shape of the simplex which is reshaped at each iteration according to the objective function, so we used a fixed shape of the simplex and we regenerate the simplex at each iteration and the second issue is related to reflection and expansion steps of the NM technique in each iteration, NM used fixed value of [Formula: see text], that is, [Formula: see text] = 1 for reflection and [Formula: see text] = 2 for expansion and replace the worst point of the simplex with that new point in each iteration. In this way NM search the optimum point. In proposed algorithm the optimum value of the parameter [Formula: see text] is computed and then centroid of new simplex is originated at this optimum point and regenerate the simplex with this centroid in each iteration that optimum value of [Formula: see text] will ensure the fast convergence of the proposed technique. The proposed algorithm has been applied to the real time implementation of the transversal adaptive filter. The application used to demonstrate the performance of the proposed technique is a well-known convex optimization problem having quadratic cost function, and results show that the proposed technique shows fast convergence than the Nelder-Mead method for lower dimension problems and the proposed technique has also good convergence for higher dimensions, that is, for higher filter taps problem. The proposed technique has also been compared with stochastic techniques like LMS and NLMS (benchmark) techniques. The proposed technique shows good results against LMS. The comparison shows that the modified algorithm guarantees quite acceptable convergence with improved accuracy for higher dimensional identification problems.

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Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes

Energies ◽

10.3390/en14113287 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3287

Author(s):

Alireza Tabrizikahou ◽

Piotr Nowotarski

Keyword(s):

Life Cycle ◽

Energy Consumption ◽

Structural Optimization ◽

Carbon Emissions ◽

Carbon Emission ◽

Construction Materials ◽

High Energy ◽

Building Structures ◽

Life Cycle Stages ◽

Reduction Of Energy Consumption

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes’ performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works.

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Experimental investigation on arches structural optimization of corn stalk incinerator based on a novel momentum design method

Biomass Conversion and Biorefinery ◽

10.1007/s13399-021-01775-5 ◽

2021 ◽

Author(s):

Xiaozhou Liu ◽

Guangyu Zhu

Keyword(s):

Experimental Investigation ◽

Structural Optimization ◽

Design Method ◽

Corn Stalk

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An innovative second-order design method for the structural optimization of the SpiderFLOAT offshore wind Platform

Ocean Engineering ◽

10.1016/j.oceaneng.2021.108792 ◽

2021 ◽

Vol 228 ◽

pp. 108792

Author(s):

Rick Damiani ◽

Max Franchi

Keyword(s):

Structural Optimization ◽

Design Method ◽

Second Order ◽

Offshore Wind

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Optimization Design of Drawbead in Drawing Tools of Autobody Cover Panel

Journal of Engineering Materials and Technology ◽

10.1115/1.1448523 ◽

2002 ◽

Vol 124 (2) ◽

pp. 278-285 ◽

Cited By ~ 12

Author(s):

Gang Liu ◽

Zhongqin Lin ◽

Youxia Bao

Keyword(s):

Optimization Algorithm ◽

Optimization Design ◽

Design Method ◽

Experimental Results ◽

Hybrid Optimization ◽

Force Model ◽

Hybrid Optimization Algorithm ◽

Design Plan ◽

Formed Part ◽

Restraining Force

In the tooling design of autobody cover panels, design of drawbead will affect the distribution of drawing restraining force along mouth of dies and the relative flowing velocity of the blank, and consequently, will affect the distributions of strain and thickness in a formed part. Therefore, reasonable design of drawbead is the key point of cover panels’ forming quality. An optimization design method of drawbead, using one improved hybrid optimization algorithm combined with FEM software, is proposed in this paper. First, we used this method to design the distribution of drawbead restraining force along the mouth of a die, then the actual type and geometrical parameters of drawbead could be obtained according to an improved drawbead restraining force model and the improved hybrid optimization algorithm. This optimization method of drawbead was used in designing drawing tools of an actual autobody cover panel, and an optimized drawbead design plan has been obtained, by which deformation redundancy was increased from 0% under uniform drawbead control to 10%. Plastic strain of all area of formed part was larger than 2% and the minimum flange width was larger than 10 mm. Therefore, not only better formability and high dent resistance were obtained, but also fine cutting contour line and high assembly quality could be obtained. An actual drawing part has been formed using the optimized drawbead, and the experimental results were compared with the simulating results in order to verify the validity of the optimized design plan. Good agreement of thickness on critical areas between experimental results and simulation results proves that the optimization design method of drawbead could be successfully applied in designing actual tools of autobody cover panels.

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