Faculty of Engineering

Permanent URI for this communityhttps://hdl.handle.net/10679/10

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Enhancing the performance of Piezoelectric Energy Harvester under electrostatic actuation using a robust metaheuristic algorithm
(Elsevier, 2023-02) Firouzi, Behnam; Abbasi, Ahmad; Şendur, Polat; Mechanical Engineering; ŞENDUR, Polat; Firouzi, Behnam; Abbasi, Ahmad
This study proposes a novel shape optimization methodology based on evolutionary algorithms to maximize the harvesting energy from piezoelectric energy harvester stimulated by the β-emitted radioisotope. The parametric width function is used to model the piezoelectric layer non-prismatically. All the geometrical dimensions as well as parameters related to the parametric width function are optimized using the metaheuristic algorithms The piezoelectric layer partially covers the beam to obtain the optimal location of the piezoelectric layer. The pull-in instability causes the discharge in the system, and the piezoelectric layer converts the vibration of the released microcantilever into electricity. The nonlinear effects of electrostatic force and geometry are taken into account, and the differential equations governing the system are discretized utilizing the exact mode shapes of the system considering the geometrical effects of non-uniform microcantilever and the piezoelectric layer. The robust chaotic Harris Hawk optimization (RCHHO) algorithm is proposed for finding the optimal shape of the system. The performance of the proposed algorithm is compared with various metaheuristic algorithms in the literature. After optimizing the shape of the piezoelectric layer, the maximum voltage produced with the optimal model using the presented method was 8.105 times that of the classic model with rectangular piezoelectric layer used in previous works. Moreover, the maximum energy and average energy harvested in the optimal model were 61 and 7.22 times, respectively, of the non-optimal model.
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Identification and evaluation of cracks in electrostatically actuated resonant gas sensors using Harris Hawk / Nelder Mead and perturbation methods
(Techno-Press, 2021-01) Firouzi, Behnam; Abbasi, Ahmad; Şendur, Polat; Mechanical Engineering; ŞENDUR, Polat; Firouzi, Behnam; Abbasi, Ahmad
In this paper we study the static deflection, natural frequency, primary resonance of an electrostatically actuated cracked gas sensor. Besides, a novel hybrid metaheuristic algorithm is proposed to detect the location and depth of possible crack on the microcantilever systems. The gas sensor configuration consists of a microcantilever with a rigid plate attached to its end. The nonlinear effects of the electrostatic force and fringing field are taken into account in the mathematical model. The crack is represented by a rotational spring. In the first part, the effect of crack on the static and dynamic pull-in instability are studied. The equations of motion are solved by the application of the perturbation methods. Next, an inverse problem is formulated to predict the location and depth of the crack in the gas sensor. For that purpose, the weighted squared difference of the analytical and predicted frequency response is considered as the objective function. The location and depth of the crack in the microsystem are determined using the hybrid Harris Hawk and Nelder Mead optimization algorithms. The accuracy and efficiency of the proposed algorithm are compared with the HHO, DA, GOA, and WOA algorithms. Taguchi design of experiments method is used in order to tune the parameters of optimization algorithms systematically. It is shown that the proposed algorithm can predict the exact location and depth of the open-edge crack on an electrostatically actuated microbeam with proof mass.
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Identification of unbalance characteristics of rotating machinery using a novel optimization-based methodology
(Springer, 2022-02-26) Abbasi, Ahmad; Firouzi, Behnam; Şendur, Polat; Ranjan, G.; Tiwari, R.; Mechanical Engineering; ŞENDUR, Polat; Abbasi, Ahmad; Firouzi, Behnam
In this study, a novel optimization-based method is proposed to determine the parameters of a rotating unbalance in a rotor-bearing system. For that purpose, the weighted sum of squared difference between the analytical and predicted unbalance response due to rotational unbalance is considered as the objective function. A hybrid algorithm integrating salp swarm algorithm and Nelder–Mead algorithms is presented for detecting unbalance magnitude and phase as the unbalance parameters. Parameters of the aforementioned optimization algorithm are determined systematically using the Taguchi design of experiments method. The efficiency of the proposed method is compared with various optimization algorithms in the literature. The optimization method is validated with different unbalances experimentally to consider the real-world conditions. The results show the superiority of the proposed hybrid algorithm in terms of the accuracy of the unbalance parameters and computational efficiency.
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Improvement of the computational efficiency of metaheuristic algorithms for the crack detection of cantilever beams using hybrid methods
(Taylor & Francis, 2022-07-03) Firouzi, Behnam; Abbasi, Ahmad; Şendur, Polat; Mechanical Engineering; ŞENDUR, Polat; Firouzi, Behnam; Abbasi, Ahmad
This study examines the capability of various optimization algorithms and proposes novel hybrid algorithms for more precise prediction of open-edge cracks in cantilever beams. The natural frequencies of the beam with a crack are obtained by modal analysis and experimentally validated by impact testing. The performance of Harris hawk optimization (HHO), electrostatic discharge algorithm (ESDA), pathfinder algorithm (PFA) and Henry gas solubility optimization (HGSO) algorithms from the literature is evaluated to determine the location and depth of an open-edge crack for an Euler-Bernoulli beam. Then, hybrid algorithms (HHO-NM, ESDA-NM and PF-NM) are proposed to improve the results of the aforementioned algorithms. Simulation results show that the proposed hybrid algorithms yield much more precise results with fewer function evaluations than the previously introduced algorithms and, therefore, have superior crack detection capability. Statistical post hoc analysis shows that the proposed hybrid algorithm can be considered a high-performance algorithm, which can significantly improve the efficiency of crack detection applications.
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Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings
(Springer, 2022-12) Abbasi, Ahmad; Firoozi, Behnam; Şendur, Polat; Heidari, A. A.; Tiwari, R.; Mechanical Engineering; ŞENDUR, Polat; Abbasi, Ahmad; Firoozi, Behnam
Bearing is one of the most fundamental components of rotary machinery, and its fatigue life is a crucial factor in designing. The design optimization of tapered roller bearing (TRB) is a complex design problem because various arrays of designing parameters and functional requirements should be fulfilled. Since there are many design variables and nonlinear constraints, presenting an optimal design of TRBs poses some challenges for metaheuristic algorithms. The Harris hawks optimization (HHO) algorithm is a robust nature-inspired method with unique exploitation and exploration phases due to its time-varying structure. However, this metaheuristic algorithm may still converge to local optima for more challenging problems such as the design of TRBs. Therefore, this study aims to improve the accuracy and efficiency of the shortcomings of this algorithm. The performance of the proposed algorithm is first evaluated for the TRB optimization problem. The TRB optimization design has nine design variables and 26 constraints because of geometrical dimensions and strength conditions. The productivity of the proposed method is compared with diverse metaheuristic algorithms in the literature. The results demonstrate the significant development of dynamic load capacity in comparison to the standard value. Furthermore, the enhanced version of the HHO algorithm presented in this study is benchmarked with various well-known engineering problems. For supplementary materials regarding algorithms in this research, readers can refer to https://aliasgharheidari.com.
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On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks
(Springer Nature, 2021-04) Abbasi, Ahmad; Firouzi, Behnam; Şendur, Polat; Mechanical Engineering; ŞENDUR, Polat; Abbasi, Ahmad; Firouzi, Behnam
A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer model of the microchannel, the slip flow velocity and temperature jump boundary conditions have been taken into account. A variety of materials and fluids have also been evaluated to determine the optimal design of the microchannel. Since the main objective of this paper is to assess the search and exploration ability of the novel Harris Hawks algorithm, results are also benchmarked with those of commonly used particle swarm optimization, bees optimization algorithm, grasshopper optimization algorithm, whale optimization algorithm and dragonfly algorithm. Finally, results are compared to the analytical results and results obtained by the application of genetic algorithms. Results show that the Harris hawks algorithm has a superior performance in minimizing the entropy generation of the microchannel. The algorithm is also more computationally efficient compared to the aforementioned algorithms. Moreover, optimization results indicate that the use of copper for the microchannel and ammonia as the coolant leads to minimal entropy generation and, therefore, is considered as the best design. Considering the poor corrosive characteristics of copper, aluminum as the microchannel material is proposed as an alternative.

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