Influence of Polypropylene Length on Stability and Flow of Fiber-reinforced Asphalt Mixtures

Engineers are constantly trying to improve the performance of the flexible pavements. The main surface distress types which cause maintenance and disruption are rutting and fatigue cracking. For solving these problems, many studies have been carried out until now, ranged from changing gradation to adding polymers and fibers to asphalt mixture. In this study, polypropylene additive was selected as fiber additive because of low costing and having good correlation with asphalt pavement. Three type of polypropylene additive in the length 6, 12 and 19 mm were selected and used at five different percentages in the asphalt concrete mixture. Asphalt specimens were analysed by Marshall Analysis and finally tested by Marshall Stability apparatus. Adding polypropylene increased Marshall Stability (38%), and decreased Flow (39%). These results show that polypropylene can be helpful for increasing pavement life

Optimum design of steel building structures using migration-based vibrating particles system

Acknowledgment This research is supported by a research grant of the University of Tabriz (Number: 1615). We sincerely express our gratitude to Assoc. Prof. Saeid Kazemzadeh Azad for providing the required data for the design examples.Peer reviewedPostprin

The Hybrid Invasive Weed Optimization-Shuffled Frog-leaping Algorithm Applied to Optimal Design of Frame Structures

In this article, an efficient hybrid optimization algorithm based on invasive weed optimization algorithm and shuffled frog-leaping algorithm is utilized for optimum design of skeletal frame structures. The shuffled frog-leaping algorithm is a population-based cooperative search metaphor inspired by natural memetic, and the invasive weed optimization algorithm is an optimization method based on dynamic growth of weeds colony. In the proposed algorithm, shuffled frog-leaping algorithm works to find optimal solution region rapidly, and invasive weed optimization performs the global search. Different benchmark frame structures are optimized using the new hybrid algorithm. Three design examples are tested using the new method. This algorithm converges to better or at least the same solutions compared the utilized methods with a smaller number of analyses. The outcomes are compared to those obtained previously using other recently developed meta-heuristic optimization methods

Crystal structure optimization approach to problem solving in mechanical engineering design

PurposeIn this paper, the authors aim to examine and comparatively evaluate a recently-developed metaheuristic called crystal structure algorithm (CryStAl) – which is inspired by the symmetries in the internal structure of crystalline solids – in solving engineering mechanics and design problems.Design/methodology/approachA total number of 20 benchmark mathematical functions are employed as test functions to evaluate the overall performance of the proposed method in handling various functions. Moreover, different classical and modern metaheuristic algorithms are selected from the optimization literature for a comparative evaluation of the performance of the proposed approach. Furthermore, five well-known mechanical design examples are utilized to examine the capability of the proposed method in dealing with challenging optimization problems.FindingsThe results of this study indicated that, in most cases, CryStAl produced more accurate outputs when compared to the other metaheuristics examined as competitors.Research limitations/implicationsThis paper can provide motivation and justification for the application of CryStAl to solve more complex problems in engineering design and mechanics, as well as in other branches of engineering.Originality/valueCryStAl is one of the newest metaheuristic algorithms, the mathematical details of which were recently introduced and published. This is the first time that this algorithm is applied to solving engineering mechanics and design problems.</jats:sec

New design equations for elastic modulus of concrete using multi expression programming

An innovative multi expression programming (MEP) approach is used to derive new predictive equations for tangent elastic modulus of normal strength concrete (NSC) and high strength concrete (HSC). Similar to several building codes, the modulus of elasticity of NSC and HSC is formulated in terms of concrete compressive strength. Furthermore, a generic model is developed for the estimation of the elastic modulus of both NSC and HSC. Comprehensive databases are gathered from the literature to develop the models. For more verification, a parametric analysis is carried out and discussed. The proposed formulas are found to be accurate for the prediction of the elastic modulus of NSC and HSC. The predictions made by the MEP-based models are more accurate than those obtained by the existing models

Fuzzy adaptive Charged System Search for global optimization

This study proposes a new fuzzy adaptive Charged System Search (CSS) for global optimization. The suggested algorithm includes a parameter tuning process based on fuzzy logic with the aim of improving its performance. In this regard, four linguistic variables are defined which configures a fuzzy system for parameter identification of the standard CSS algorithm. This process provides a focus for the algorithm on higher levels of global searching in the initial iterations while the local search is considered in the last iterations. Twenty mathematical benchmark functions, the Competitions on Evolutionary Computation (CEC) regarding CEC 2020 benchmark, three well-known constrained, and two engineering problems are utilized to validate the new algorithm. Moreover, the performance of the new algorithm is compared and contrasted with other metaheuristic algorithms. The obtained results reveal the superiority of the proposed approach in dealing with different unconstraint, constrained, and engineering design problems.Web of Science109art. no. 10751