Browsing by Author "Firouzi, Behnam"

Now showing 1 - 8 of 8

Metadata only
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.
Metadata only
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.
Metadata only
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.
Metadata only
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.
Open Access
A new deep learning restricted boltzmann machine for energy consumption forecasting
(MDPI, 2022-08) Xu, A.; Tian, M. W.; Firouzi, Behnam; Alattas, K. A.; Mohammadzadeh, A.; Ghaderpour, E.; Firouzi, Behnam
A key issue in the desired operation and development of power networks is the knowledge of load growth and electricity demand in the coming years. Mid-term load forecasting (MTLF) has an important rule in planning and optimal use of power systems. However, MTLF is a complicated problem, and a lot of uncertain factors and variables disturb the load consumption pattern. This paper presents a practical approach for MTLF. A new deep learning restricted Boltzmann machine (RBM) is proposed for modelling and forecasting energy consumption. The contrastive divergence algorithm is presented for tuning the parameters. All parameters of RBMs, the number of input variables, the type of inputs, and also the layer and neuron numbers are optimized. A statistical approach is suggested to determine the effective input variables. In addition to the climate variables, such as temperature and humidity, the effects of other variables such as economic factors are also investigated. Finally, using simulated and real-world data examples, it is shown that for one year ahead, the mean absolute percentage error (MAPE) for the load peak is less than 5%. Moreover, for the 24-h pattern forecasting, the mean of MAPE for all days is less than 5%.
Metadata only
A new path following scheme: safe distance from obstacles, smooth path, multi-robots
(Springer, 2023-04) Mohammadzadeh, A.; Firouzi, Behnam; Firouzi, Behnam
Robot routing is one of the most important topics in mobile robotics. The goal is to find a continuous path from an initial position to an end destination that is collision-free and optimal or near-optimal. Due to the growing trend of using automatic moving tools in industrial automation, and their application for various purposes such as transportation of goods, and service in industrial and hospital environments, many researchers have decided to conduct research in this field and route planning. The main challenge is to find a short route with a lack of collision with obstacles. This study examines path design for mobile robots and proposes a new and efficient idea for routing. Besides the short distance of the route and lack of collision with obstacles, the proposed method investigates other factors such as the safe distance from obstacles, path smoothness, and multiple robots. The results show the superior precision and speed of the proposed algorithm compared to similar algorithms. The suggested approach finds the shortest path with a safe distance from obstacles, in a minimum time. The major contributions of this method are summarized below: (1) a biogeographical algorithm is formulated for robot routing. (2) To improve the basic biogeographical algorithm, basic operations of the particle swarm optimization and genetic algorithm are integrated with it. (3) In addition to the shortest path problem, other problems such as path smoothness with a new idea and the safe distance from obstacles are included. Path smoothing is performed without involving it in the cost function, and merely through interpolation of the points found by the algorithm. (4) The proposed algorithm results in a good efficiency and finds the appropriate solution in a few iterations.
Metadata only
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.
Open Access
A type-2 fuzzy controller for floating tension-leg platforms in wind turbines
(MDPI, 2022-03) Firouzi, Behnam; Alattas, K. A.; Bakouri, M.; Alanazi, A. K.; Mohammadzadeh, A.; Mobayen, S.; Fekih, A.; Firouzi, Behnam
This paper proposes a type-2 fuzzy controller for floating tension-leg platforms in wind turbines. Its main objective is to stabilize and control offshore floating wind turbines exposed to oscillating motions. The proposed approach assumes that the dynamics of all units are completely unknown. The latter are approximated using the proposed Sugeno-based type-2 fuzzy approach. A nonlinear Kalman-based algorithm is developed for parameter optimization, and linear matrix inequalities are derived to analyze the system’s stability. For the fuzzy system, both rules and membership functions are optimized. Additionally, in the designed approach, the estimation error of the type-2 fuzzy approach is also considered in the stability analysis. The effectiveness and performance of the proposed approach is assessed using a simulation study of a tension leg platform subject to various disturbance modes.