Steady flow of a power law fluid through a tapered non-symmetric stenotic tube

Ahmad, Riaz; Farooqi, Asma; Zhang, Jiazhong; Ali, Nasir

doi:10.2478/amns.2019.1.00022

Cited by 23 publications

(16 citation statements)

References 13 publications

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“…One was the conventional ZMP trajectory and the other was the variable ZMP trajectory considering the environmental change, but all achieved stable walking. Figure 9(b), 3D simulation, shows that the CoM adjustment of the stabilization system achieves stable walking, which indicated that the walking pattern of biped robot was sensitive to the change of CoM trajectory [29][30][31][32]. Hence, predictive control can generate stable walking pattern by controlling the CoM motion, which is consistent with the real-time slight adjustment of CoG trajectory during human walking to adapt the change of road condition to achieve stable walking.…”

Section: Simulation Experiments and Analysissupporting

confidence: 55%

Stable walking of biped robot based on center of mass trajectory control

Jing

Zheng

2020

Open Physics

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The effect of center of mass (CoM) trajectory on stable walking of biped robot was studied in this study. The method of predictive control by controlling CoM trajectory to generate stable walking patterns was discussed, which simulated the principle of adjusting center of gravity in advance during human walking to adapt to the change of road conditions. As for uncertainty of robot modeling and the influence of environment, adding variable zero moment point for variable predictive control system can achieve self-adaptive adjustment of CoM trajectory to generate stable walking patterns. The simulation experiment results indicated that walking stability of biped robot was sensitive to the change of CoM trajectory. As long as CoM trajectory was adjusted well, stable walking of biped robot can be controlled even in the presence of disturbances. It is proved that the method of predictive control by controlling CoM motion to generate stable walking pattern is consistent with reality.

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Section: Simulation Experiments and Analysissupporting

confidence: 55%

Stable walking of biped robot based on center of mass trajectory control

Jing

Zheng

2020

Open Physics

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“…Particles (parameters) in PSO determine their new location by following the current optimum particle in the problem space. It has been found to be effective while applied to various optimization problems including artificial neural networks [31], mechanical engineering design optimization problems [32][33][34], and chaotic systems [35][36][37]. Moreover, it is easy for it to achieve high accuracy with fast converging speed [38,39].…”

Section: Particle Swarm Optimization Algorithm Pso Firstmentioning

confidence: 99%

Application of Radial Basis Function Neural Network Coupling Particle Swarm Optimization Algorithm to Classification of Saudi Arabia Stock Returns

Rashedi

Ismail

Hamadneh

et al. 2021

Journal of Mathematics

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Artificial intelligence (AI) based business process optimization has a significant impact on a country’s economic development. We argue that the use of artificial neural networks in business processes will help optimize these processes ensuring the necessary level in the functioning and compliance with the foundations of sustainable development. In this paper, we proposed a mathematical model using AI to detect outliers in the daily return of Saudi stock market (Tadawul). An outlier is defined as a data point that deviates too much from the rest of the observations in a data sample. Based on the Engle and Granger Causality test, we selected inflation rate, repo rate, and oil prices as input variables. In order to build the mathematical model, we first used the Tukey method to detect outliers in the stock return data from Tadawul that are collected during the period from October 2011 to December 2019. In this way, we categorized the stock return data into two classes, namely, outliers and nonoutliers. These data are further used to train artificial neural network in conjunction with particle swarm optimization algorithm. In order to assess the performance of the proposed model, we employed the mean squared error function. Our proposed model is signified by the mean squared error value of 0.05. The proposed model is capable of detecting outlier values directly from the inflation rate, repo rate, and oil prices. The proposed model can be helpful in developing and applying intelligent optimization techniques to solve problems in business processes.

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“…Moreover, Riaz et al [24] investigated the study of heat and mass transfer in the MHD Oldroyd-B fluid with ramped wall temperature using local and nonlocal differential operators. Additionally, the recent studies on modern fractional differential operators and viscoelastic fluids can be traced out in [25][26][27][28][29][30][31][32][33][34][35][36][37][38]. For this problem, the noninteger differentiable operator is chosen for the fractional MHD Oldroyd-B model which is developed under thermal radiation, ramp velocity, and ramp temperature associated with physical initial and boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

Study of Heat Transfer under the Impact of Thermal Radiation, Ramped Velocity, and Ramped Temperature on the MHD Oldroyd-B Fluid Subject to Noninteger Differentiable Operators

Saeed

Khan

Riaz

et al. 2020

Journal of Mathematics

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This theoretical study explores the impact of heat generation/absorption with ramp wall velocity and ramp wall temperature on the magnetohydrodynamic (MHD) time-dependent Oldroyd-B fluid over an unbounded plate embedded in a porous surface. The mathematical analysis of fractional governing partial differential equations has been established using systematic and powerful techniques of Laplace transform with its numerical inversion algorithms. The fractionalized solutions have been traced out separately through all fractional differential operators. Nondimensional parameters along with Laplace transformation are used to find the solution of temperature and velocity profiles. Fractional time derivatives are used to analyze the impact of fractional parameters (memory effect) on the dynamics of the fluid. While making a comparison, it is observed that the fractional-order model is the best to explain the memory effect as compared to classical models. The obtained solutions are plotted graphically for different values of physical parameters. Our results suggest that the velocity profile decreases by increasing the effective Prandtl number. Furthermore, the existence of an effective Prandtl number may reflect the control of the thickness of momentum and enlargement of thermal conductivity.

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Steady flow of a power law fluid through a tapered non-symmetric stenotic tube

Cited by 23 publications

References 13 publications

Stable walking of biped robot based on center of mass trajectory control

Stable walking of biped robot based on center of mass trajectory control

Application of Radial Basis Function Neural Network Coupling Particle Swarm Optimization Algorithm to Classification of Saudi Arabia Stock Returns

Study of Heat Transfer under the Impact of Thermal Radiation, Ramped Velocity, and Ramped Temperature on the MHD Oldroyd-B Fluid Subject to Noninteger Differentiable Operators

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