•Comparative analysis of ammonia and methanol heat pipe is investigated.•Thermal resistance and total mass of heat pipe are considered for the comparative analysis.•Optimization problem of heat pipe ...is developed and solved.•Investigate the effect of geometric parameters on the performance of heat pipe.•Investigate the sensitivity of design variables on the performance of heat pipe.
In this work, a satellite heat pipe operated with the ammonia and methanol are investigated for the multi-objective optimization. Optimization results are used for the comparative analysis of both the heat pipe. Optimization problem of the heat pipe is formed considering minimization of the thermal resistance and total mass of heat pipe and solved using the heat transfer search algorithm. An application example of satellite heat pipe is presented, and results are obtained in the form of Pareto-optimal points. Seven geometric parameters which include the length of evaporator and condenser section, tube wall thickness, vapor core diameter, mesh number of wick, thickness of wick, and diameter of wick wire are investigated in the optimization study. Further, the effect of condenser temperature, heat load, and length of the adiabatic section on ammonia and methanol heat pipe is explored and discussed. Furthermore, the effect of the design variables and its sensitivity to performance parameters of the heat pipe are also presented. Comparative results revel that, for any given value of the total mass of heat pipe, 82.17–57.16% lower thermal resistance is observed with the ammonia heat pipe as compared to methanol heat pipe. Finally, uncertainty propagation analysis of the obtained Pareto solutions are carried out with the different uncertainty levels and observed that the results have relatively good robustness performance for uncertainty less than 5%.
Recently friction stir processing (FSP) has shown keen interest to achieve superplasticity in different aluminum alloys. The pin profile of FSP tool is one of the important process parameter which ...controls the mechanical and metallurgical properties of stir zone (SZ), like other variables of tool rotational speed, travel speed, and tool tilt. The high strength 7075 aluminum (Al-Zn-Mg-Cu) alloy was subjected to FSP to investigate effects of pin profiles on the superplastic behavior. Three different polygonal pin profiles of square, pentagon and hexagon were used. Microstructure, microhardness and grain size measurements were performed for all FSP samples. Fine grain uniform microstructure without cavitation in the SZ was observed in sample produced by square pin only. All polygonal pin profiles indicated sticking of workpiece material around tool pin that resulted in non-uniform grain microstructure in the SZ. Hot tensile testing was carried out for square pin under the superplastic condition of 3×10−4s−1 and 400°C to study the superplastic behavior. Uniform superplastic elongation of 227% was obtained in the gage region of the square pin sample.
•A novel meta-heuristic optimization method is proposed.•A new perspective for optimization is proposed based on the mathematics of heat transfer•Performance of proposed method is checked for ...challenging benchmark optimizationproblems.•The proposed method is better compared to other optimization algorithms.
In this paper, a new metaheuristic optimization algorithm based on the law of thermodynamics and heat transfer is introduced. In the proposed algorithm, the search agents are molecules of the system that interact with each other as well as with the surrounding to attain thermal equilibrium state. The interactions of molecules are through various modes of heat transfer (i.e. conduction, convection and radiation). The performance of the proposed algorithm is investigated by implementing it for the parameter optimization of 24 well defined constrained optimization problems of Congress on Evolutionary Computation 2006 (CEC 2006). The results obtained using the proposed algorithm are compared with the results of some well-known metaheuristic search algorithms available in the literature. The statistical analysis of the experimental work has been carried out by conducting Friedman's rank test and Holm post hoc procedure. The comparative results validate the competitive and efficient performance of the proposed algorithm for solving constraint optimization problems.
Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering ...different natural phenomena. Teaching-Learning-based optimization (TLBO) is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.
Intelligent fault diagnosis gives timely information about the condition of mechanical components. Since rolling element bearings are often used as rotating equipment parts, it is crucial to identify ...and detect bearing faults. When there are several defects in components or machines, early fault detection becomes necessary to avoid catastrophic failure. This work suggests a novel approach to reliably identifying compound faults in bearings when the availability of experimental data is limited. Vibration signals are recorded from single ball bearings consisting of compound faults, i.e., faults in the inner race, outer race, and rolling elements with a variation in rotational speed. The measured vibration signals are pre-processed using the Hilbert–Huang transform, and, afterward, a Kurtogram is generated. The multiscale-SinGAN model is adapted to generate additional Kurtogram images to effectively train machine-learning models. To identify the relevant features, metaheuristic optimization algorithms such as teaching–learning-based optimization, and Heat Transfer Search are applied to feature vectors. Finally, selected features are fed into three machine-learning models for compound fault identifications. The results demonstrate that extreme learning machines can detect compound faults with 100% Ten-fold cross-validation accuracy. In contrast, the minimum ten-fold cross-validation accuracy of 98.96% is observed with support vector machines.
This paper presents an efficient multi-objective improved teaching–learning based optimization (MO-ITLBO) algorithm for solving multi-objective optimization problems. The proposed algorithm uses a ...grid-based approach in order to keep diversity in the external archive. Pareto dominance is incorporated into the MO-ITLBO algorithm in order to allow this heuristic to handle problems with several objective functions. The qualities of the solution are computed based on the Pareto dominance notion. The performance of the MO-ITLBO algorithm is assessed by applying it on a set of standard test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009) competition. The results obtained using the proposed algorithm is compared with the other state-of-the-art algorithms available in the literature. Moreover, the performance of the MO-ITLBO algorithm is also compared with the multi-objective version of the basic teaching–learning based optimization algorithm (MO-TLBO). The statistical analysis of the experimental work is also carried out by conducting Friedman’s rank test and Holm post hoc procedure. The results show that the proposed approach is competitive and effective compared to other algorithms contemplated in this work and it can also find the result with greater precision.
In the present study, the Gas metal arc welding (GMAW) based Wire-arc additive manufacturing (WAAM) process was used to fabricate a multi-layered structure at optimized process parameters on SS316L ...using metal wire of SS316L. The multi-layered structure's microstructure, macrostructure, and mechanical properties (tensile test, impact test, microhardness, and fractography) were examined at three locations at the top, middle, and bottom sides of the structure. Macrostructure at different zones has confirmed an appropriate bonding between the two layers, complete fusion without oxidation, and free from defects and unwanted geometries. Microstructure results have observed a colony of columnar dendrites in the bottom zone, coarser grains with vertical growth along with the residual ferrite in the middle zone, and vertical dendritic structure with residual ferrite in skeletal shape in the top zone. Results of all tensile properties for top, middle and bottom zone developed by the WAAM process fall in the range values of wrought SS 316L. The microhardness values were shown a consistent behavior across the built structure in all three zones. The obtained average value for the impact test has shown better strength than commercially used wrought SS 316L. The results of fractured tensile and fracture impact test specimens revealed many dimples, which suggests a good ductility of the as-built structure. Thus, the obtained results have shown that the built structure using the GMAW-based WAAM process matches the standards for industrial applications.
To develop ultrafine grains (UFG) in 6.35 mm thick magnesium alloy, stationary shoulder friction stir processing (SSFSP) with steel and copper backing plates was conducted. Steel backing plate ...produced uniform fine grains (FG) size of 4.98, 4.75, 4.12 μm in top, middle, bottom of the stir zone (SZ), respectively. In contrast, copper backing plate tailored microstructure from FG (4.1 μm) in the top to UFG (0.96 μm) in the bottom of SZ. SSFSP produced uniform and gradient microstructures, altering temperature gradient by placing steel and copper backing plates, respectively. It is worth to note that UFG microstructure achieved without usage of external cooling, owning to the copper backing plate. Most of the grains found under ~2 μm size in UFG microstructure. FG and UFG microstructures contributed to the enhancement in the ductility and strength, respectively. UFG resulted in significant improvement in hardness and tensile strength by ~80% and 24% of the base material, respectively. The intensity of strong basal texture throughout the thickness found independent of the backing plate type. Microstructure evolutions across the SZ thickness for both processing conditions are discussed using electron back scattered diffraction (EBSD).
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Many engineering structures are subjected to dynamic excitation, which may lead to undesirable vibrations. The multiple natural frequency bounds in truss optimization problems can improve dynamic ...behaviour of structures. However, shape and size variables with frequency bounds are challenging due to its characteristic, which is non-linear, non-convex, and implicit with respect to the design variables. As the main contribution, this work proposes an improved version of a recently proposed Symbiotic Organisms Search (SOS) called an Improved SOS (ISOS) to tackle the above-mentioned challenges. The main motivation is to improve the exploitative behaviour of SOS since this algorithm significantly promotes exploration which is a good mechanism to avoid local solution, yet it negatively impacts the accuracy of solutions (exploitation) as a consequence. The feasibility and effectiveness of ISOS is studied with six benchmark planar/space trusses and thirty functions extracted from the CEC2014 test suite, and the results are compared with other meta-heuristics. The experimental results show that ISOS is more reliable and efficient as compared to the basis SOS algorithm and other state-of-the-art algorithms.
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