American Institute Of Steel Construction Load And Resistance Factor Design Research Articles

An optimal design approach for steel space frames with T-stub semi-rigid connections considering soil-structure interaction

An optimization technique for designing the steel space frame with T-stub semi-rigid connections and interaction between soil and structure is presented in this article. A three-parameter-based elastic foundation model is utilized to investigate soil-structure interactions (SSI). To enable two-way data transfer for all optimization methods, computer software was developed using C# version 17.8.6, which connects to SAP2000-OAPI version 22. Particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO) are employed for optimal designs. These optimization techniques choose profile sections from a list, including 64W discrete sections from the American Institute of Steel Construction (AISC). The Load and Resistance Factor Design-American Institute of Steel Construction (LRFD-AISC) strength constraints, geometric constraints, inter-storey drift constraints, and displacement constraints are considered during optimization. The first phase entails creating optimal designs for two unique steel space frames that consider SSI but do not include T-stub semi-rigid connections. Following that, the same optimization procedures are carried out with T-stub semi-rigid connections. The parameters needed for the foundation model are obtained through soil surface displacements. Utilizing T-stub semi-rigid connections while considering the interaction between the structure and the soil produces increased structural weight.

ÇELİK ÇERÇEVELERİN FARKLI STOKASTİK YÖNTEMLER KULLANILARAK OPTİMUM BOYUTLANDIRILMASI

Bu çalışmada rijit çelik çerçevelerin Av Arama, Parçacık Sürü ve Büyük Patlama - Büyük Çöküş optimizasyon yöntemlerini temel alan üç farklı optimum tasarım algoritması sunulmuştur. Av Arama optimizasyon algoritması kurt, aslan, yunus gibi hayvanların grupça avlanmalarından esinlenilerek geliştirilmiştir. Grupta yer alan hayvanlar (avcılar) avlarını bir daire içine alır ve yakalarlar. Avcılar, kokularının av tarafından hissedilmemesi için rüzgâra doğru durmazlar. Bu avcılardan her birisi yapısal bir optimizasyon problemi için aday bir çözüm oluşturur. Parçacık Sürü optimizasyon algoritması sürü halinde hareket eden kuş, balık ve böceklerden esinlenerek geliştirilmiş bir yöntemdir. Sürüdeki her hayvan (parçacık) kendi konumunu sürüde bulunan diğer parçacıklara ve kendisinin bir önceki konumuna göre düzenler. Hedefe ulaşıncaya kadar bu süreç devam eder. Büyük Patlama – Büyük Çöküş optimizasyon algoritması evrenin büyük patlama ve büyük çöküş hipotezinden esinlenilmiştir. Büyük Patlama evresinde Merkez Noktası ya da Kütle Merkezi olarak adlandırılan benzersiz bir nokta üretilmektedir. Algoritma kapsamında Kütle Merkezi yakınlarında yeni adaylar belirlenir, uygunlukları hesaplanır ve içlerinden en iyisi seçilir. Çalışma kapsamında üç katlı üç açıklıklı, beş katlı üç açıklıklı ve yedi katlı üç açıklıklı olmak üzere üç adet çelik çerçevenin bu algoritmalar ile en küçük ağırlıkları bulunacak şekilde optimum boyutlandırılmaları yapılmıştır. Boyutlandırma yapılırken LRFD-AISC (Yük ve Dayanım Katsayılarıyla Tasarım (YDKT)) yönetmeliğindeki sınırlayıcıların sağlanması hedeflenmiştir. Ayrıca, üç teknik birbiriyle kıyaslanmış, Parçacık Sürü algoritması 2 örnekte en iyi sonucu bulması açısından diğerlerine kıyasla daha iyi bir performans sergilemiş, Av Arama algoritması da onu takip etmiştir. Her örnek için en küçük ağırlığı bulan tekniğin sonuçları baz alınarak çerçevelerin SAP2000 analiz programı ile yük altında deplasman analizleri yapılmıştır. Son olarak, çerçevelerin en üst kat yanal deplasmanları belirlenmiş ve yorumlarda bulunulmuştur.

Determination of Optimal Configuration for Mega Bracing Systems in Steel Frames using Genetic Algorithm

Mega bracing is one of the recently emphasized methods for lateral bracing of structures. In the present study, various configurations of mega bracing systems in terms of installation angle for lateral bracing of steel structures are evaluated and optimized. The investigated frames are designed and optimized using genetic algorithm (GA) according to LRFD-AISC (load and resistance factor design, american institute of steel construction). Frame analysis is carried out by means of finite element method, while optimization is conducted using GA considering three different types of selection and crossover, simultaneously. The results demonstrate that the optimum angle of mega bracing in steel frames is within the range of 36° to 42° with regard to the frame height and span. Furthermore, with increase in frame height, the employment of optimally distributed mega braces along the height of the frame results in reduction of story drifts and also the frame weight. Additionally, simultaneous utilization of various selection and crossover types in GA optimization leads to an increase in convergence rate of optimum weight of the frame as well as reduction in the required computations.

Biogeography-Based Optimization Algorithm for Designing of Planar Steel Frames

The optimization can be defined as a solution of problem under specific conditions to achieve a specific purpose. Optimization strategies commonly used for solving of various problems and have gained great importance in recent years especially in engineering. Evolving optimization methods over the years has many varieties such as shape optimization, topology optimization, size optimization etc. The latest trend of optimization methods is metaheuristics which are more useful with easy applicable to complex problems regarding to traditional optimization methods. So that metaheuristics have supplanted the traditional methods particularly in engineering by the time. In this study, a planar steel frame which is designed according to the requirements comprised by AISC-LRFD (American Institute of Steel Construction-Load and Resistance Factor Design) has been optimized by aid of biogeography-based optimization (BBO) algorithm.

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.

Optimum design of steel space frames with composite beams using genetic algorithm

This paper presents an optimization process using Genetic Algorithm (GA) for minimum weight by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The stress constraints obeying AISC-LRFD (American Institute of Steel Construction - Load and Resistance Factor Design), lateral displacement constraints being the top and inter-storey drift, mid-span deflection constraints for the beams and geometric constraints are considered for optimum design by using GA that mimics biological processes. Optimum designs for three different space frames taken from the literature are carried out first without considering concrete slab effects in finite element analyses for the constraints above and the results are compared with the ones available in literature. The same optimization procedures are then repeated for the case of space frames with composite (steel and concrete) beams. A program is coded in MATLAB for the optimization processes. Results obtained in the study showed that consideration of the contribution of the concrete on the behavior of the floor beams results with less steel weight and ends up with more economical designs.

Optimum design of steel frames with semi-rigid connections and composite beams

In this paper, an optimization process using Genetic Algorithm (GA) that mimics biological processes is presented for optimum design of planar frames with semi-rigid connections by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The stress constraints as indicated in AISC-LRFD (American Institute of Steel Construction - Load and Resistance Factor Design), maximum lateral displacement constraints and geometric constraints are considered for optimum design. Two different planar frames with semi-rigid connections taken from the literature are carried out first without considering concrete slab effects in finite element analyses and the results are compared with the ones available in literature. The same optimization procedures are then repeated for full and semi rigid planar frames with composite (steel and concrete) beams. A program is developed in MATLAB for all optimization procedures. Results obtained from this study proved that consideration of the contribution of the concrete on the behavior of the floor beams provides lighter planar frames.

Optimum design of grillage structures to LRFD-AISC with teaching-learning based optimization

In this paper, a new efficient optimization algorithm called Teaching---Learning-Based Optimization (TLBO) is used for the optimum design of grillage systems based on the LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Construction). Cross sectional area of W-shapes are considered as discrete design variables. Various grillage structures are designed to show the efficiency of the TLBO algorithm. The results obtained from this study are compared with those reported in the literature. It is concluded that the TLBO algorithm presented in this study can be effectively used in the optimal design of grillage structures.

Optimum design of unbraced steel frames to LRFD–AISC using particle swarm optimization

Particle Swarm method based optimum design algorithm for unbraced steel frames is presented. The Particle Swarm method is a numerical optimization technique that simulates the social behavior of birds, fishes and bugs. In nature fish school, birds flock and bugs swarm not only for reproduction but for other reasons such as finding food and escaping predators. Similar to birds seek to find food, the optimum design process seeks to find the optimum solution. In the particle swarm optimization each particle in the swarm represents a candidate solution of the optimum design problem. In the optimum design algorithm presented the design constraints are imposed in accordance with LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction). In the design of beam-column members the combined strength constraints are considered that take into account the lateral torsional buckling of the member. The algorithm developed selects optimum W sections for beams and columns of unbraced frame from the list of 272W-sections list. This selection is carried out such that design constraints imposed by the LRFD are satisfied and the minimum frame weight is obtained. The efficiency of the algorithm is demonstrated considering a number of design examples.

Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC

Harmony search based optimum design method is presented for the grillage systems. This numerical technique imitates the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The design algorithm considers the serviceability and ultimate strength constraints which are implemented from Load and Resistance Factor Design—American Institute of Steel Construction (LRFD-AISC). It selects the appropriate W-sections for the transverse and longitudinal beams of the grillage system out of 272 discrete W-section designations given in LRFD-AISC. This selection is carried out such that the design limitations described in LRFD-AISC are satisfied and the weight of the system is the minimum. Many design examples are considered to demonstrate the efficiency of the algorithm presented.

Alternative Approaches for Elastic Analysis and Design of Steel Frames. I: Overview

Two methods for analysis and design of steel framing systems are outlined and compared to the current American Institute of Steel Construction (AISC) load and resistance factor design (LRFD) buckling solution or effective length based procedure: an AISC LRFD based notional load approach and a modified elastic approach. Both methods provide a rational means of accounting for the key phenomena that affect system strength, specifically residual stresses (i.e., member inelasticity) and initial geometric imperfections. By accounting for these factors directly within a second-order elastic analysis, the need for effective length factors or buckling solutions is eliminated. Also, these methods provide a more accurate estimate of required internal system forces than current methods. Examples of solutions for a stability critical industrial-type frame are presented to illustrate the application of these methods, and to compare and contrast their results with solutions from both the current AISC LRFD procedures and from rigorous distributed plasticity analysis.

Cost optimization of composite floors using neural dynamics model

AbstractThe design of composite beams is complicated and highly iterative. Depending on the design parameters a beam can be fully composite or partially composite. In the case of design on the basis of the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) one has to consider the plastic deformations. As pointed out by Lorenz, the real advantage of the LRFD code can be realized in the minimum cost design. In this article, we present a general formulation for the cost optimization of composite beams based on the AISC LRFD specifications by including the costs of (a) concrete, (b) steel beam, and (c) shear studs. The problem is formulated as a mixed integer‐discrete non‐linear programming problem and solved by the recently patented neural dynamics model of Adeli and Park (U.S. patent 5,815,394 issued on September 29, 1998). It is shown that use of the cost optimization algorithm presented in this article results in substantial cost savings. Copyright © 2001 John Wiley & Sons, Ltd.

Optimum load and resistance factor design of steel space frames using genetic algorithm

In this paper, an algorithm is presented for the minimum weight design of steel moment-resisting space frames subjected to American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) specification. A genetic algorithm (GA) is utilized herein as the optimization method. Design variables which are cross-sectional areas are discrete and are selected from the standard set of AISC wide-flange (W) shapes. The structure is subjected to wind loading in accordance with the Uniform Building Code (UBC) in conjunction with vertical loads (dead and live loads). Displacement and AISC LRFD stress constraints are imposed on the structure. The algorithm is applied to the design of three space frame structures. The designs obtained using AISC LRFD code are compared to those where AISC Allowable Stress Design (ASD) is considered. The comparisons show that the former code results in lighter structures for the examples presented.

Moment Amplification Factor for P-δ Effect of Steel Beam-Column

The American Institute of Steel Construction load and resistance factor design (AISC-LRFD) Specification states that second-order effects should be considered in the design of frames; however, most designers are experienced only in first-order analysis. To accomplish the second-order design requirement, the AISC-LRFD Specification provides an approximate method to account for the second-order effect bases on first-order analysis, where moment amplification factors B1 and B2 are introduced to account for the P-δ effect (member instability) and PΔ effect (frame instability), respectively. However, the B1 factor of the AISC-LRFD Specification may vary greatly from the exact solution, especially when the member is under a high axial load. In this paper, a new moment amplification factor B1* is proposed for calculating the P-δ effect in the design of steel beam-columns. Parametric studies were performed to examine the accuracy of the proposed moment amplification factor and to compare it with that from theoret...

The effect of ultimate-to-yield ratio on the bearing strength of bolted connections

An experimental study on the effect of end distance on the bearing strength of one-bolt and two-bolt lap connections was undertaken. Two different steels, one with high ultimate-to-yield stress ratio and the other with low ultimate-to-yield stress ratio, were used in the test program to determine the effect of steel strength on bearing capacity for various end distances and spacing. It was found that ultimate-to-yield stress ratios greater than 1.13 do not affect the strength at 6.35 mm displacement, and it is reconfirmed that the bearing strength is proportional to the ultimate stress of the material. The results are compared with the strength predicted by the current American Institute of Steel Construction Load and Resistance Factor Design (AISC-LRFD) Specifications and Eurocode 3.

Optimum Load and Resistance Factor Design of Steel Space-Frame Structures

Minimum weight design of steel moment-resisting space frame structures with or without bracing subjected to the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) specification is presented. The LRFD constraints for moment-resisting frames are highly nonlinear and implicit functions of design variables (cross-sectional areas). The structure is subjected to wind loading according to the Uniform Building Code (UBC) in addition to the vertical loads due to dead and live loads. A scaling procedure is developed that results in fast convergence. The algorithm is applied to minimum weight design of four large high-rise steel building structures ranging in height from 20 to 81 stories and in size from 1,920 to 9,245 members. A comparison of designs of space moment-resisting frames based on the AISC LRFD code with those based on the AISC Allowable Stress Design (ASD) code shows the former results in a lighter structure for the examples presented.