Optimization Of Steel Structures Research Articles

Design and Optimization of Steel Structures for Solar Panel Systems

Abstract: Structural components are fundamental for supporting mechanical machines in industrial settings. These structures are designed not only to bear the weight of the machines but also to withstand the vibrations generated during operation. The project at hand focuses on integrating basic structural sections to create a complete mechanical framework. Our goal is to collaborate with an industry specializing in support structures for various electrical units. From our initial analysis, we observed that many of these industries rely on conventional manufacturing practices and past experience to design structures, often leading to overdesign. No finite element analysis (FEA) or theoretical calculations are typically applied. We propose introducing modern FEA techniques and concepts to optimize and refine these designs for improved efficiency.

Local Instability and Deformation Control of Steel Roof of Factory Building in a Smart City

Abstract The traditional control methods of instability and deformation of steel structure neglect the analysis of its natural vibration characteristics, which lead to the poor effect of hysteretic vibration of steel structure nodes, and the stability optimization of steel structure is not ideal. Therefore, a new method to control the local instability and deformation of the steel roof is proposed. According to the steel structure composition of the upper door rigid frame and the connection mode of the frame beam and column, the roof steel structure characteristics of the workshop are analyzed. Multi-order natural frequency method is used to obtain the cumulative modal mass contribution rate of steel structure and analyze the natural vibration characteristics of steel structure. Based on the characteristics of natural vibration and element transfer matrix, the local instability control method of roof steel structure is designed. Simulation of strong vibration, using space analysis of tall-building with wall-elements (SATWE) software analysis of strong vibration under elastic load state, to obtain the external deformation of steel structure, under simulation of vibration deformation control model. Taking a chemical plant as an example, a finite element model was established to simulate the vibration wave, and the numerical simulation results of plastic deformation resistance of steel structure were analyzed. The experimental results show that the proposed method can effectively enhance the stability of steel structure and reduce its deformation degree.

Multiobjective optimal design of reinforced concrete frames using two metaheuristic algorithms

Genetic algorithm (GA) and differential evolution (DE) are metaheuristic algorithms that have shown a favorable performance in the optimization of complex problems. In recent years, only GA has been widely used for single-objective optimal design of reinforced concrete (RC) structures; however, it has been applied for multiobjective optimization of steel structures. In this article, the total structural cost and the roof displacement are considered as objective functions for the optimal design of the RC frames. Using the weighted sum method (WSM) approach, the two-objective optimization problem is converted to a single-objective optimization problem. The size of the beams and columns are considered as design variables, and the design requirements of the ACI-318 are employed as constraints. Five numerical models are studied to test the efficiency of the GA and DE algorithms. Pareto front curves are obtained for the building models using both algorithms. The detailed results show the accuracy and convergence speed of the algorithms.

Topology Optimization of Steel Structure for Waste Incineration Steam Generator Based on DE and PSO

Topology Optimization of Steel Structure for Waste Incineration Steam Generator Based on DE and PSO

A hybrid gradient-based/metaheuristic method for Eurocode-compliant size, shape and topology optimization of steel structures

The production and processing of building materials is responsible for a significant share of global greenhouse gas emissions. Nevertheless, in current building practice, a lot of material is wasted, because load-bearing structures are often grossly overdimensioned. Numerical optimization tools have the potential to reduce the consumption of structural materials, but the lack of customized algorithms prohibits their use in daily design practice. This is because real-life structural optimization problems are complex, involving both discrete and continuous design variables as well as large numbers of building code constraints. In the literature, such problems are usually solved using metaheuristic (often genetic) algorithms, although gradient-based algorithms are better suited for continuous design variables. In this article, a new hybrid gradient-based/metaheuristic algorithm is proposed. It combines gradient-based and metaheuristic methods in a nested approach, exploiting the strengths of both: the ability to handle discrete design variables and fast convergence in terms of continuous design variables. The applicability and usefulness of the new hybrid algorithm is demonstrated in two realistic case studies to minimize the weight of the structure, taking into account all relevant design rules of Eurocode 3. Within identical computing time, the hybrid algorithm obtains significant material savings compared to a conventional genetic algorithm.

Parametric optimization of steel structures based on gradient projection method

The main research goal is the development of a numerical methodology for solving parametric optimization problems of steel structures with orientation on software implementation in a computer-aided design system. The paper has proposed a new mathematical model for parametric optimization problems of steel structures. The design variable vector includes geometrical parameters of the structure (node coordinates), cross-sectional dimensions of the structural members, as well as initial pre-stressing forces introduced into the specified redundant members of the structure. The system of constraints covers load-carrying capacities constraints formulated for all design sections of structural members of the steel structure subjected to all ultimate load case combinations. The displacements constraints formulated for the specified nodes of the steel structure subjected to all serviceability load case combinations have been also included into the system of constraints. The method of the objective function gradient projection onto the active constraints surface with simultaneous correction of the constraints violations has been used for solving the parametric optimization problem. A numerical algorithm for solving the formulated parametric optimization problems of steel structures has been developed in the paper. The comparison of the optimization results of truss structures presented by the paper confirms the validity of the optimum solutions obtained using the proposed numerical methodology.

Evolutionary Structural Optimization of Wind Bracing Connection Plates in Steel Structures

Evolutionary Structural Optimization (ESO) is one of the rules in structural engineering which has received much attention by the researchers. Today, the reduction of construction cost and weight is an important issue in the structure design. The optimization phenomenon is pursuing to fulfill this objective. Thus, presenting a design which could be both safe and economic is of special significance. Despite the valuable researches which have been conducted on optimization of steel structures, the gap of research on ESO of wind bracing connection plates and other metal connections is sensible. The purpose of the present paper is to make an optimal design of these types of connections in the frames with convergent bracing. In this study, the software of Finite Element Method (FEM) of abaqus has been used to design the concentrically (convergent) wind bracing of connection plates based on optimization principles. The Von-Mises stress distribution contour has been presented for two statuses in different angles. In the designed bracing frame, dimensions and thickness of connection plate have been defined as the design variables and the design of optimization is compared with the design of ordinary status and the past works as well. This shows a noticeable reduction in the weight of the optimal designed plate in comparison with the ordinary design.

Optimized design of steel car parks for fully spread fires

ABSTRACTThe design optimization of steel structure is usually carried out by choosing a profile that minimizes the amount of steel, under the boundaries of carrying mechanical loads and being compliant with maximum allowed displacements. The fire verifications are typically performed at a later design stage by applying the amount of insulation needed to keep the profile below its critical temperature during fire. This strategy keeps the steel costs to a minimum, but often results in relatively high costs for insulating the structure, which may nullify the scope of the original design optimization. This study investigates possible beneficial effects of including fire verifications at the early design stage of a structure. The methodology is presented with reference to a steel car park structure insulated with intumescent paint against a fully spread fire and is based on the minimization of the sum of the steel and insulation costs. The results show that the optimization leads to a reduction of 36% of the material costs.The price is also compared to the case of an uninsulated structure designed against local fires. This design assumption allows avoiding fire insulation, but has been challenged by past cases of major fire spread, such as the recent car park in Liverpool. The paper shows that the conservative assumption of a full spread fire corresponds to the doubling of the material costs, when the structure is traditionally optimized by minimizing the amount of steel for the ordinary design conditions. However, the proposed optimization limits the cost increment to 19% of the material costs and just 6% of the total costs of the structure. This increment lies within the expected variation of costs during the realization of a structure and indicates that a higher safety level of steel car parks can be achieved, while maintaining a competitive market price against concrete structures.

Optimization of steel structures with one genetic algorithm according to three international building codes

Among all the optimization techniques, the genetic algorithms (GAs) stand out because of their mathematical simplicity, the no necessity of information about the objective function or the constraint functions, and the possibility of working with any type of structure. Although these features suggest an enormous flexibility for working with different building codes, in general, each one is developed for a particular structure and a particular building code. In a world without borders, where one structure can be calculated in one country, manufactured in other and built in a third one, develop one GA for each building code difficult the construction process and increase its cost. In this paper, one GA capable of working with three different building codes (Spanish, European and American) is researched. After analysing the different constraints and stabilities for them, the objective function is defined. Then, and due the influence that the working parameters have in the optimization result, the effect of each parameter over the behaviour of the GA is analysed and a working range for them is established. Finally, the results of the optimization are compared, showing the heaviest structures with the American code and the lightest structures with the European code.

Optimal Design of Grillage Structures with Steel Crossed Beams using Genetic Algorithms

The optimal problem in the structural design is an important issue in the engineering design. Various authors have analyzed the optimization of steel structures using algorithmic approaches. These techniques are generally grouped in deterministic or meta-heuristic techniques. From the introduction of structural optimization in the 1960’ up to now, various methods have been proposed. A genetic algorithm, is built and applied in this study using MatLab soft R2017a to a crossed beams system. The structural analysis is done with the direct stiffness method with constraints verification based on EuroCode 3:2005 criteria. Results are reported in the study.

Algorithm of numerical optimization of steel structures on basis of minimum weight criterion

The description of the algorithm of steel structures optimal design is described in the article. The calculation model is represented by flat and spatial rod elements. The problem of optimization is resolved with the help of mathematical programming. The material consumption is taken as a criterion of optimality. A wide range of inspections is presented in the form of regulatory requirements for strength, rigidity and local stability. The geometry parameters of the sections are varied, as well as the external geometry of the nodes of the final element model. Both continuous and discrete variations might be possible. The algorithm is implemented in two versions: on the basis of imitating the short-term problem and with the direct reference to the target and restrictive functions at each step of optimization process. The results of the solution of the steel framework optimization problem during on-going and discrete variations of geometric parameters are presented. The solutions obtained are estimated on uniqueness.

A Design Methodology to Support the Optimization of Steel Structures

Steel constructions are widely used in several applications such as structures for buildings, stores, factories, and power plants. The scope of the research is to study a methodology to reduce the weight and the cost related to big frame steel structures during the early design phase, which is the phase where most of the project layout is defined. The main aim of this paper is the development of a platform-tool to support the automatic optimization of a steel structure using virtual prototyping tools and genetic algorithms. The focus is on the design of heavy steel structures for oil & gas power plants. This work describes in detail the design methodology and estimates the weight saving related to the re-design process of a test case structure. The design cases considered in the paper are those relevant to the operating.

Fully Constrained Design: A general and scalable method for discrete member sizing optimization of steel truss structures

Fully Constrained Design (FCD) is a new method for discrete sizing optimization of steel structures that balances computational efficiency with solution quality for application to large-scale problems. The proposed method is based on optimality criteria, but does not require gradient information and handles discrete variables. Based on benchmarking studies, FCD produces superior quality solutions to optimality criteria (>4%), but inferior to heuristic methods (<2%). FCD is approximately 10× less computationally efficient than optimality criteria and 100× more efficient than heuristic methods. We present a successful industry application of FCD that yields cost savings of 19% compared to conventional design methods.

Simulation Analysis and Structure Optimization of Steel Structure Climbing Formwork with Material Properties Used in the Large Angle Leaning Bridge Tower

Steel structure climbing formwork has been widely used in bridge pier and bridge tower, etc. But the design of 30 degrees slope climbing formwork design is rarely involved. The climbing formwork which in the upper surface of leaning bridge tower is affected by concrete buoyancy and the downside is affected by concrete gravity .That cause insufficient stiffness,deformation of the template,non-uniform cross-section of the bridge and large angle deviation which have great harm to the bridge quality .This paper which combined the construction project of Huaibei Xiangwang Bridge establish the mode of climbing formwork, then, import the mode to the Workbench14.5 proceeding simulation analysis. Getting the stress and deformation of the climbing formwork, check the strength and stiffness .Then optimize the structure of climbing formwork to ensure the stiffness and control the deformation of the template. The stress of downside climbing formwork after optimization is uniform and maximum stress is reduced about 30% .This paper provide a reference to the design of the climbing formwork used in the large angle leaning bridge tower.

Performance Based Optimized Design of Steel Structure

During the past two centuries, steel structure has become one of the most popular structural system. How to balance the construction cost, structural properties and other factors is an important aspect needed to be addressed. This paper describes the whole process of performance based optimized design of steel structure. First, the methods on the shape and sizing optimization, cost and others are introduced. Then, the multi-object optimization of steel structure is presented, in which the main aspects of the optimizations are studied. Finally, the design principle and the analytical steps for the multi-object optimization of steel structures are discussed. This paper can be references for the optimization design of steel structures.

Accelerating fuzzy genetic algorithm for the optimization of steel structures

In this paper, the combination of a genetic algorithm and fuzzy logic is used for different types of optimization problems (sizing, topology and geometry) in steel structures. The primary objective is to introduce a new fitness function that uses a real value for the overall satisfaction parameter. By considering a real value instead of a random value for the overall satisfaction parameter, the probability of reaching the global optimum increases. In addition, to decrease the Computation time and to accelerate the convergence rate in the optimization process, a penalty function is added to the fitness function. Also, in spite of the previous methods, fuzzy GA is applied from the first generation of optimization problems. Furthermore, for this process, a similar bilinear membership function is used for the objective function and the constraints. The efficiency and robustness of the proposed approach is demonstrated by several illustrative examples and the results are compared to those of previous studies.

Multi-stage production cost optimization of semi-rigid steel frames using genetic algorithms

The response of a steel structure is closely related to the behavior of its joints. This means that it is necessary to take explicit account of joint properties in order to ensure a consistent approach to design optimization of steel frames. Semi-rigid design has been introduced into steel construction standards such as Eurocode 3 and AISC. However, in the absence of appropriate guidelines, engineers encounter difficulties when bringing in semi-rigid design to everyday engineering practice. Moreover, connection design significantly affects the production cost of steel frame structures. Thus, a realistic optimization of frame design should take into account the effective costs of different stages of production including manufacturing and erection activities. This paper presents a Genetic Algorithm based method for multi-stage cost optimization of steel structures. In the objective function, the total cost of different production stages is minimized. A new cost model is presented that itemizes costs of all stages of production (material supply, manufacturing, erection and foundation). Design examples are used to validate the proposed methodology. Numerical validation shows that the multi-stage design optimization results in substantial cost benefits between 10% and 25% compared to traditional design of steel frames. Furthermore, the developed methodology is shown to be capable of measuring the possible impact of design choices in the early design stage thus assisting designers to make better design decisions.

Reliability based robust design optimization of steel structures

In this work the uncertainty of a structural system is taken into account in the framework of a structural Reliability based Robust Design Optimization (RRDO) formulation where probabilistic constraints are incorporated into the robust design optimization formulation. A robust design optimization problem is formulated as a multi-criteria optimization problem. The Pareto front representing the solution of the RRDO problem is composed by designs with a state of robustness, since their performance is the least sensitive to the variability of the uncertain variables. The cross section dimensions together with other structural parameters, such as the modulus of elasticity, the yield stress and the applied loading, are considered as random variables. For the solution of the RRDO problem, the non-dominant Cascade Evolutionary Algorithm is employed combined with a weighted Tchebycheff metric.

Robust seismic design optimization of steel structures

Stochastic performance measures can be taken into account, in structural optimization, using two distinct formulations: robust design optimization (RDO) and reliability-based design optimization (RBDO). According to a RDO formulation, it is desired to obtain solutions insensitive to the uncontrollable parameter variation. In the present study, the solution of a structural robust design problem formulated as a two-objective optimization problem is addressed, where cross-sectional dimensions, material properties and earthquake loading are considered as random variables. Additionally, a two-objective deterministic-based optimization (DBO) problem is also considered. In particular, the DBO and RDO formulations are employed for assessing the Greek national seismic design code for steel structural buildings with respect to the behavioral factor considered. The limit-state-dependent cost is used as a measure of assessment. The stochastic finite element problem is solved using the Monte Carlo Simulation method, while a modified NSGA-II algorithm is employed for solving the two-objective optimization problem.

Design optimization of steel structures considering uncertainties

In real world engineering applications the uncertainties of the structural parameters are inherent and the scatter from their nominal ideal values is in most cases unavoidable. These uncertainties play a dominant role in structural performance and the only way to assess this influence is to perform Reliability-Based Design Optimization (RBDO) and Robust Design Optimization (RDO). Compared to the basic deterministic-based optimization problem, a RBDO problem considers additional non-deterministic constraint functions, while the RDO yields a design with a state of robustness, so that its performance is the least sensitive to the variability of the uncertain parameters. The first part of this study examines the application of Neural Networks (NN) to the RBDO of large-scale structural systems, while the second part investigates the structural RDO problem. The use of NN in the framework of the RBDO problem is motivated by the approximate concepts inherent in reliability analysis and the time-consuming repeated analyses required by Monte Carlo Simulation. On the other hand the RDO is a multi-criteria optimization problem where the aim is to minimize both the weight of the structure and the variance of the structural response.