• Structural Engineering and Mechanics
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• v.8 no.2
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• pp.165-180
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• 1999

The cost effectiveness of using steel roof systems for residential buildings is becoming increasingly apparent with the decrease in manufacturing cost of steel components, reliability and efficiency in construction practices, and the economic and environmental concerns. While steel has been one of the primary materials for structural systems, it is only recently that its use for residential buildings is being explored. A comprehensive system for the design of residential steel roof truss systems is presented. In the first stage of the research the design curves obtained from the AISI-LRFD code for the manufactured cross-sections were verified experimentally. Components of the truss systems were tested in order to determine their member properties when subjected to axial force and bending moments. In addition, the experiments were simulated using finite element analysis to provide an additional source of verification. The second stage of the research involved the development of an integrated design approach that would automatically design a lowest cost roof truss given minimal input. A modified genetic algorithm was used to handle sizing, shape and topology variables in the design problem. The developed methodology was implemented in a software system for the purpose of designing the lowest cost truss that would meet the AISI code provisions and construction requirements given the input parameters. The third stage of the research involved full-scale testing of a typical residential steel roof designed using the developed software system. The full scale testing established the factor of safety while validating the analysis and design procedures. Evaluation of the test results indicates that designs using the present approach provide a structure with enough reserve strength to perform as predicted and are very economical.

• Wind and Structures
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• v.29 no.4
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• pp.279-297
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• 2019

Strong winds threaten the safety of vehicles on long-span bridges considerably, which could force traffic authorities to reduce speed limits or even close these bridges to traffic. In order to maintain the safe and economic operation of a bridge, a reasonable evaluation of the driving safety on that bridge is needed. This paper aims at carrying outdriving safety analyses for three types of vehicles on a long-span bridge in crosswinds by considering the aerodynamic interference between the bridge and the vehicles based on the wind-vehicle-bridge coupling vibration analysis. Firstly, CFD numerical simulations along with previously obtained wind tunnel testing results were used to determine the aerodynamic force coefficients of the three types of vehicles on the bridge. Secondly, the dynamic responses of the bridge and the vehicles under crosswinds were simulated, and based on those, the driving safety analyses for the three types of vehicles on the bridge were carried out for both cases considering and not considering the aerodynamic interference between the vehicles and the bridge. Finally, the effect of the aerodynamic interference on the safety of the vehicles was investigated. The results show that the aerodynamic interference between the bridge and the vehicles not only affectsthe accident critical wind speed but also the accident type for all three types of vehicles. Such effects are also different for each of the three types of vehicles being studied.

• Earthquakes and Structures
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• v.23 no.2
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• pp.129-138
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• 2022

One of the objectives to prevent building pounding between two adjacentstructures is to considerseparation distance or decrease relative displacement during seismic excitation. Although the majority of building codes around the world have basically suggested some equations or approximately recommended various distances between structuresto avoid pounding hazard, but a lot of reportsin zone of pounding have obviously shown thatsafety situation or economic consideration are not always provided due to the collisions between buildings and the cost of land, respectively. For this purpose, a dynamic MDOF model by having base isolation system is numerically considered and using various earthquake records, relative displacements are mathematically investigated. Different equations to determine the value of damping ratio are collected and the results of evaluations are listed for comparison among them to present a new equation for determination of impact damping ratio. Presented equation is depends significantly on impact velocity before and after impact based on artificial neural network, which the accuracy of them is investigated and also confirmed. In order to select the optimum equation, hysteresisloop of impact between base of building and rubber bumper is considered and compared with the hysteresis loop of each impact, calculated by different equations. Finally, using representative equation, the effect of thickness, number and stiffness of rubber bumpers are numerically investigated. The results of analysis indicate that stiffness and number of bumpers have significantly affected in zone of impact force while the thickness of bumpers have not shown significant influence to calculate impact force during earthquake. For instance, increasing the number of bumpers, gap size between structures and also the value of stiffness is caused to decrease impact force between models. The final evaluation demonstrates that bumpers are able to decrease peak lateral displacement of top story during impact.

• Steel and Composite Structures
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• v.52 no.3
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• pp.293-312
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• 2024

Researchers are actively investigating the potential for utilizing alternative materials in construction to tackle the environmental and economic challenges linked to traditional concrete-based materials. Nevertheless, conventional laboratory methods for testing the mechanical properties of concrete are both costly and time-consuming. The limitations of traditional models in predicting the tensile strength of concrete composited with geopolymer have created a demand for more advanced models. Fortunately, the increasing availability of data has facilitated the use of machine learning methods, which offer powerful and cost-effective models. This paper aims to explore the potential of several machine learning methods in predicting the tensile strength of geopolymer concrete under different curing conditions. The study utilizes a dataset of 221 tensile strength test results for geopolymer concrete with varying mix ratios and curing conditions. The effectiveness of the machine learning models is evaluated using additional unseen datasets. Based on the values of loss functions and evaluation metrics, the results indicate that most models have the potential to estimate the tensile strength of geopolymer concrete satisfactorily. However, the Takagi Sugeno fuzzy model (TSF) and gene expression programming (GEP) models demonstrate the highest robustness. Both the laboratory tests and machine learning outcomes indicate that geopolymer concrete composed of 50% fly ash and 40% ground granulated blast slag, mixed with 10 mol of NaOH, and cured in an oven at 190°F for 28 days has superior tensile strength.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.