Serdar Carbas

Design optimization of steel frames using an enhanced firefly algorithm

Mathematical modelling of real-world-sized steel frames under the Load and Resistance Factor Design–American Institute of Steel Construction (LRFD-AISC) steel design code provisions, where the steel profiles for the members are selected from a table of steel sections, turns out to be a discrete nonlinear programming problem. Finding the optimum design of such design optimization problems using classical optimization techniques is difficult. Metaheuristic algorithms provide an alternative way of solving such problems. The firefly algorithm (FFA) belongs to the swarm intelligence group of metaheuristics. The standard FFA has the drawback of being caught up in local optima in large-sized steel frame design problems. This study attempts to enhance the performance of the FFA by suggesting two new expressions for the attractiveness and randomness parameters of the algorithm. Two real-world-sized design examples are designed by the enhanced FFA and its performance is compared with standard FFA as well as with particle swarm and cuckoo search algorithms.

Comparative Study on Recent Metaheuristic Algorithms in Design Optimization of Cold-Formed Steel Structures

Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to make a major contribution to a more sustainable future of our World because this industry is one of the largest contributors to global warming. The use of cold-formed steel framing in construction industry provides sustainable construction which requires less material to carry the same load compare to other materials and reduces amount of waste mimum design algorithms are developed for cold-formed steel frames made of thin-walled sections using the recent metaheuristic techniques. The algorithms considered are firefly, cuckoo search, artificial bee colony with levy flight, biogeography-based optimization and teaching-learning-based optimization algorithms. The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size cold-formed steel building is optimized by using each of these algorithms and their performance in attaining the optimum designs is compared.

Optimum structural design of spatial steel frames via biogeography-based optimization

Metaheuristic algorithms have provided an efficient tool for designers by which discrete optimum design of real-size steel space frames under design code requirements can be obtained. In this study, the optimum sizing design of steel space frames is formulated according to provisions of Load and Resistance Factor Design—American Institute of Steel Construction. The weight of the steel frame is taken as objective function. The design algorithm selects the appropriate W sections for members of the steel frame such that the frame weight is the minimum and design code limitations are satisfied. The biogeography-based optimization algorithm is utilized to find out the optimum solution of the discrete programming problem. This algorithm is one of the recent additions to metaheuristic techniques which are based on theory of island biogeography where each habitat is assumed to be potential solution for the design problem. The performance of the biogeography-based optimization algorithm is compared with other recent metaheuristic algorithms such as adaptive firefly algorithm, teaching and learning-based optimization, artificial bee colony optimization, dynamic harmony search algorithm, and ant colony algorithm. It is shown that biogeography-based optimization algorithm outperforms other metaheuristic techniques in the design examples considered.

Use of Swarm Intelligence in Structural Steel Design Optimization

In this chapter, the optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Corporation). The weight of the steel frame is taken as the objective function to be minimized. The design optimization problem necessitates selection of steel sections for the members of the steel frame from the available steel profiles lists. This turns the design optimization problem into discrete programming problem. Obtaining the optimum solution of such programming problems is cumbersome with mathematical programming techniques. On the other hand with the use of recently developed metaheuristic techniques that are based on swarm intelligence, the solution of the same problem becomes straightforward. Five different structural optimization algorithms are developed which are based on ant colony optimization, particle swarm optimizer, artificial bee colony algorithm, firefly algorithm, and cuckoo search algorithm, respectively. Two real size steel space frames; one rigidly connected and the other pin jointed are designed using each of these algorithms. The optimum designs obtained by these techniques are compared and performance of each version is evaluated. It is noticed that most of swarm intelligence-based algorithms are simple and robust techniques that determine the optimum solution of structural design optimization problems efficiently without requiring much of a mathematical struggle.

Structural features of cold-formed steel profiles

Using capacity of cold-formed steel sections increases thanks to the opportunities which are offered by the developing technology. Low production cost and variety of profiles that can be produce easy, fast, high quality provide to improve its popularity as a structural material. In production, Sulphur and Phosphorous accumulation region occurs at intersection region of flanges and web of hot rolled steel profile. This causes to decrease strength of profile. Other difference between cold-formed and hot rolled steel sections is that mechanical properties of steel material homogeneously distributes throughout the profile. Both in frame and truss systems, cold-formed steel profiles develop both as main and secondary bearing element. These present variety options to the designers with pure, galvanized, aluminized applications. As with many building materials, mechanical behavior of cold-formed steel profile is quite complex due to the nature of thin walled steel sections. Design and analysis methods of cold-formed steel profile are rapidly shaped day by day. The general theory of beams investigated in past studies make possible analyses of cold-formed steel profile. Moreover, in structural systems, using of cold-formed steel profile provide height strength besides sustainable, environmentalist, green building because it requires less material and cost. Although these profiles have many advantages, use of cold-formed steel profiles in our country structures is rather limited unfortunately. New steel construction regulations in Turkey also do not mention cold-formed thin walled steel structure. Main purpose of this study reviews structural specifications of cold-formed steel profiles which are applied world-wide. A R T I C L E I N F O

Optimum design of purlin systems used in steel roofs

In this study, one existing purlin system which is used in steel roof is optimized by taking into account less cost and bearing maximum load via developed software. This software runs with firefly algorithm which is one of the recent stochastic search techniques. One of the metaheuristic techniques, so-called firefly algorithm imitates behaviors of natural phenomena. Behaviors and communications of firefly are inspired by this algorithm. In optimization algorithm, steel sections, distance between purlins, tensional diagonal braces are determined as design variables. Design loads are taken into account by considering TS498-1997 (Turkish Code) in point of place where structure will be built, outside factors and used materials. Profile list in TS910 is used in selection stage of cross sections of profile. Constraints of optimization are identified in accordance with bending stress, deformation and shear stress in TS648. Design variables of optimization are selected as discrete variables so as to obtain applicable results. Developed software is tested on existing real sample so; it is evaluated with regard to design and performance of algorithm. A R T I C L E I N F O

Mechanical performance comparison of glass and mono fibers added gypsum composites

Gypsum and gypsum based composite are widely preferred in construction industry for various purposes. Mechanical performances of gypsum composite have been enhanced by researchers in order to increase its area of usage. In this research, gypsum composites containing expanded glass were reinforced by glass fibers (GF) and mono polypropylene fibers (MPF). GF and MPF were used up to 1.5%. The flexural strength, compressive strength, and shrinkage behavior of the composites were examined within the scope of this study. 50 x 50 x 50 mm and 40 x 40 x 160 sized specimens were prepared for the mechanical performance tests. It was obtained that flexural and shrinkage behavior of the composite were enhanced with the addition of MPF compared to GF added mixes; however, compressive strength values were not as high as GF reinforced composites. A R T I C L E I N F O Article history: Received 8 November 2017 Revised 7 December 2017 Accepted 18 December 2017

Utilization of Harmony Search Algorithm in Optimal Structural Design of Cold-Formed Steel Structures

The most important concern for structural design engineers is, nowadays, how to design and build a structure which is really sustainable. The course to design and construct of buildings has to be urgently changed if the overall carbon dioxide emission would like to be reduced. Otherwise, the increase in global warming arising out of building construction will continue in a great majority. The application of cold-formed steel skeleton frames increasingly in building trade makes possible sustainable structures. In this study a harmony search algorithm (HSA) and an improved version, called as adaptive harmony search (AHSA) algorithm to obtain optimum design of cold-formed steel frames. These algorithms choose the cold-formed thin-walled C-sections treated as design variables from a list in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design). This selection minimize the weight of the cold-formed steel frame while the design constraints specified by the code are satisfied.