• Advances in Computational Design
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• v.7 no.1
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• pp.1-17
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• 2022

In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.

• Advances in Computational Design
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• v.7 no.4
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• pp.297-319
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• 2022

Due to their natural and social revelation, also their ease and flexibility, human collective behavior and teamwork sports are inspired to introduce optimization algorithms to solve various engineering and scientific problems. Nowadays, meta-heuristic algorithms are becoming some striking methods for solving complex real-world problems. In that respect in the present study, the authors propose a novel meta-innovative algorithm based on soccer teamwork sport, suitable for optimization problems. The method may be referred to as the Soccer League Optimization-based Championship Algorithm, inspired by the Soccer league. This method consists of two main steps, including: 1. Qualifying competitions and 2. Main competitions. To evaluate the robustness of the proposed method, six different benchmark mathematical functions, and two engineering design problem was performed for optimization to assess its efficiency in achieving optimal solutions to various problems. The results show that the proposed algorithm may well explore better performance than some well-known algorithms in various aspects such as consistency through runs and a fast and steep convergence in all problems towards the global optimal fitness value.

• Steel and Composite Structures
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• v.34 no.3
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• pp.409-421
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• 2020

In the optimized structure sizing, the optimization methods are inserted in this context in order to obtain satisfactory solutions, which can provide more economical structures, besides allowing the consideration of the factors related to the environmental impacts in the structural design. This work proposes a mathematical model for the optimization of steel-concrete composite beams aiming to minimize the monetary cost and the environmental impact, using the Harmonic Search optimization method. Discrete variables were the dimensions of the steel profiles and the thickness of the collaborating slab of the composite steel-concrete beam. The proposed model was implemented in Fortran programming language and based on improvements in the structure of the optimization method proposed by Medeiros and Kripka (2017). To prove the effectiveness and applicability of the model, as well as the Harmonic Search method, analyzes were performed with different configurations of steel-concrete composite beams, in order to provide guidelines that make the use of these systems more streamlined. In general, the Harmonic Search optimization method has proved to be efficient in the search for the optimized solutions, as well as important considerations on the optimization of the monetary and environmental costs of steel-concrete composite beams were obtained from the developed examples.

• Structural Engineering and Mechanics
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• v.55 no.3
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• pp.555-581
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• 2015

Triangular pyramid and Quadrangular pyramid elements for partial double-layer spherical reticulated shells of pyramidal system are investigated in the present study. Macro programs for six typical partial double-layer spherical reticulated shells of pyramidal system are compiled by using the ANSYS Parametric Design Language (APDL). Internal force analysis of six spherical reticulated shells is carried out. Distribution regularity of the stress and displacement are studied. A shape optimization program is proposed by adopting the sequence two-stage algorithm (RDQA) in FORTRAN environment based on the characteristics of partial double-layer spherical reticulated shells of pyramidal system and the ideas of discrete variable optimization design. Shape optimization is achieved by considering the objective function of the minimum total steel consumption, global and locality constraints. The shape optimization of six spherical reticulated shells is calculated with the span of 30m~120m and rise to span ratio of 1/7~1/3. The variations of the total steel consumption along with the span and rise to span ratio are discussed with contrast to the results of shape optimization. The optimal combination of main design parameters for six spherical reticulated shells is investigated, i.e., the number of the optimal grids. The results show that: (1) The Kiewitt and Geodesic partial double-layer spherical reticulated shells of triangular pyramidal system should be preferentially adopted in large and medium-span structures. The range of rise to span ratio is from 1/6 to 1/5. (2) The Ribbed and Schwedler partial double-layer spherical reticulated shells of quadrangular pyramidal system should be preferentially adopted in small-span structures. The rise to span ratio should be 1/4. (3) Grids of the six spherical reticulated shells can be optimized after shape optimization and the total steel consumption is optimized to be the least.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.363-370
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• 2014

A new NURBS-based shape optimization method is proposed. Most shape optimization studies consider only control point positions as design variables. Some shape optimization processes present problems with mesh quality and convergence when control points are constrained to a limited space. If the weights of the control points are regarded as additional design variables, it should be possible to attain a better degree of shape control. In this study, positions and weights of NURBS control points are used as design variables, and a shape optimization algorithm incorporates position optimization and weight optimization steps. This method is applied to shape optimization benchmarking problems to verify its advantages.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.44-51
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• 2019

Designing sophisticate ship structures that satisfy several design criteria simultaneously with minimum weight and cost is an important engineering issue. For a ship structure composed of a shell and stiffeners, this issue is more serious because their mutual effect has to be addressed. In this study, a two-stage optimization method is proposed for the conceptual design of stiffeners in a ship's prow. In the first stage, a topology optimization method is used to determine a potential stiffener distribution based on the optimal results, whereupon stiffeners are constructed according to stiffener generative theory and the material distribution. In the second stage, size optimization is conducted to optimize the plate and stiffener sections simultaneously based on a parametric model. A final analysis model of the ship-prow structure is presented to assess the validity of this method. The analysis results show that the two-stage optimization method is effective for stiffener conceptual design, which provides a reference for designing actual stiffeners for ship hulls.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.608-615
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• 2022

Construction projects are large-scale projects that require extensive construction costs and resources. Especially, scheduling is considered as one of the essential issues for project success. However, the schedule and resource management are challenging to conduct in high-tech construction projects including complex design of MEP and architectural finishing which has to be constructed within a limited workspace and duration. In order to deal with such a problem, this study suggests resource and sequence optimization using constraint programming in construction projects. The optimization model consists of two modules. The first module is the data structure of the schedule model, which consists of parameters for optimization such as labor, task, workspace, and the work interference rate. The second module is the optimization module, which is for optimizing resources and sequences based on Constraint Programming (CP) methodology. For model validation, actual data of plumbing works were collected from a construction project using a five-minute rate (FMR) method. By comparing actual data and optimized results, this study shows the possibility of reducing the duration of plumbing works in construction projects. This study shows decreased overall project duration by eliminating work interference by optimizing resources and sequences within limited workspaces.

• Steel and Composite Structures
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• v.44 no.5
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• pp.603-617
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• 2022

Structural design, in general, is developed through trial and error technique which is guided by standards criteria and based on the intuition and experience of the engineer, a context that leads to structural over-dimensioning, with uneconomic solutions. Aiming to find the optimal design, structural optimization methods have been developed to find a balance between cost, structural safety, and material performance. These methods have become a great opportunity in the steel structural engineering domain since they have as their main purpose is weight minimization, a factor directly correlated to the real cost of the structure. Assuming an objective function of minimum weight with stress and displacement constraints provided by Brazilian standards, the present research proposes the sizing optimization and combined approach of sizing and shape optimization, through a software developed to implement the Simulated Annealing metaheuristic algorithm. Therefore, two steel plane frame layouts, each admitting four typical truss geometries, were proposed in order to expose the difference between the optimal solutions. The assessment of the optimal solutions indicates a notable weight reduction, especially in sizing and shape optimization combination, in which the quantity of design variables is increased along with the search space, improving the efficiency of the optimal solutions achieved.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.72-79
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• 2017

A full treatment of damping material is not an effective method because the damping effect is not significantly increased compared to that obtained by an effective partial damping treatment. Thus, a variety of methodologies has been considered in order to achieve an optimal damping treatment. One of the widely applied approaches is topology optimization. However, the high computational expenses can be an issue in topology optimization. A new efficient convergence criterion, reducible design variable method (RDVM), is applied to reduce computational expense in topology optimization. The idea of RDVM topology optimization is to adaptively reduce the number of design variables based on the history. The iteration repeats until the number of design variables becomes zero. The aim of this research is to adopt RDVM topology optimization into obtaining an optimal damping treatment. In order to demonstrate the effectiveness and efficiency of RDVM topology optimization, optimal damping layouts and computational expenses are compared between conventional and RDVM topology optimization.