Ishtiaq Ali

Optimal Homotopy Asymptotic Solutions of Couette and Poiseuille Flows of a Third Grade Fluid with Heat Transfer Analysis

In this paper, analytical analysis of the steady flow of an incompressible third grade fluid between two parallel plates is carried out, and the effect of heat transfer is taken into account. Three different types of flows namely, Couette flow, Poiseuille flow and generalized Couette flow, all depending upon the relative motion of the plates, are studied. The solutions are obtained for the developed non-linear equations using Optimal Homotopy Asymptotic Method (OHAM). This method provides a simple strategy to control the convergence region of the approximating solution series where ever necessary.

Utilization bound for periodic task set with composite deadline

Due to polynomial time complexity, utilization based tests are desired for online feasibility analysis of periodic task systems. However, the associated disadvantage with these tests is that they propose a bound on system utilization, which trade processor utilization for performance. On the contrary, response time based tests share pseudo-polynomial time complexity, which are very expensive in terms of analysis time and therefore, impractical for analyzing feasibility of online systems. Realizing the advantage of utilization based tests over response time tests, attempts are being made to propose utilization based exact tests that achieve 100% CPU utilization for the system by modifying task parameters such as restricting task periods to be harmonic. We show that in systems where task deadlines are large, better results are obtained by making the task deadlines harmonic. The paper proposes a novel solution to feasibility problem of periodic task system under the assumption of composite deadline by providing a utilization based exact test with an upper bound of 1 and complexity O(n).

Minimizing Response Time Implication in DVS Scheduling for Low Power Embedded Systems

Recently, a lot of work has been done on minimizing energy consumption of real time embedded systems by exploiting hardware characteristics of latest processors. However, these techniques are effective to energy reduction at the expense of delayed responsiveness; a feature highly discouraged in real time embedded systems. As opposed to the previous works, we value response time of higher importance than energy reduction after reliability, when a tradeoff is involved. In this paper, we present a novel technique for scheduling mixed tasks on single dynamic voltage scaling enabled processor. The proposed algorithm, preserves all timings constraints for hard periodic tasks under worst case execution time scenario, improves responsiveness to periodic tasks and, saves as much energy as possible for hybrid workload.

Effect of Couple Stresses on Flow of Third Grade Fluid between Two Parallel Plates using Homotopy Perturbation Method

In this paper, an analytical analysis of the steady flow of an incompressible, third grade fluid between two parallel plates is carried out where the effect of couple stresses is taken into account. Depending on the relative motion of the plates, four different problems are studied: Couette flow, Plug flow, plane Poiseuille flow and generalized plane Couette flow. The solutions are obtained for the developed non-linear equations using the traditional perturbation method as well as the recently introduced homotopy perturbation method. Analytical expressions are given for the velocity field. It is observed that the homotopy perturbation method is more well-organized and flexible than the traditional perturbation method.

Enhanced Differential Evolution and Crow Search Algorithm Based Home Energy Management in Smart Grid

In this paper, we used two techniques: Enhanced Differential Evolution (EDE) and Crow Search Algorithm (CSA), in order to evaluate the performance of Home Energy Management System (HEMS). The total load is categorized into three groups based on their energy consumption pattern, and time of use of appliances. Critical Peak Pricing (CPP) scheme is used to calculate electricity bill. Our goals are electricity cost reduction, energy consumption minimization, Peak to Average Ratio (PAR) minimization, and user comfort maximization. However, there is trade-off between multiple objectives (goals). The simulation results show that, there is trade-off between PAR and total cost, and there is trade-off as well between PAR and waiting time. The simulation results also show that CSA performs better in terms of total cost and user comfort than EDE and unscheduled.

A kinetic flux vector splitting scheme for shallow water equations incorporating variable bottom topography and horizontal temperature gradients

This paper is concerned with the derivation of a well-balanced kinetic scheme to approximate a shallow flow model incorporating non-flat bottom topography and horizontal temperature gradients. The considered model equations, also called as Ripa system, are the non-homogeneous shallow water equations considering temperature gradients and non-uniform bottom topography. Due to the presence of temperature gradient terms, the steady state at rest is of primary interest from the physical point of view. However, capturing of this steady state is a challenging task for the applied numerical methods. The proposed well-balanced kinetic flux vector splitting (KFVS) scheme is non-oscillatory and second order accurate. The second order accuracy of the scheme is obtained by considering a MUSCL-type initial reconstruction and Runge-Kutta time stepping method. The scheme is applied to solve the model equations in one and two space dimensions. Several numerical case studies are carried out to validate the proposed numerical algorithm. The numerical results obtained are compared with those of staggered central NT scheme. The results obtained are also in good agreement with the recently published results in the literature, verifying the potential, efficiency, accuracy and robustness of the suggested numerical scheme.

Application of Legendre spectral-collocation method to delay differential and stochastic delay differential equation

Explicit solutions to delay differential equation (DDE) and stochastic delay differential equation (SDDE) can rarely be obtained, therefore numerical methods are adopted to solve these DDE and SDDE. While on the other hand due to unstable nature of both DDE and SDDE numerical solutions are also not straight forward and required more attention. In this study, we derive an efficient numerical scheme for DDE and SDDE based on Legendre spectral-collocation method, which proved to be numerical methods that can significantly speed up the computation. The method transforms the given differential equation into a matrix equation by means of Legendre collocation points which correspond to a system of algebraic equations with unknown Legendre coefficients. The efficiency of the proposed method is confirmed by some numerical examples. We found that our numerical technique has a very good agreement with other methods with less computational effort.

Comparison of BFA and EWA in Home Energy Management System Using RTP

With the usage of demand side management (DSM) techniques, consumers such as residential, commercial and industrial are more flexible to use electricity according to their need. Many techniques are proposed to manage electricity cost, load, peak to average ratio (PAR) and user comfort of consumer appliances. In this paper we proposed a technique Earthworm Optimization Algorithm (EWA) that is developed for residential area in SG and compare with the Bacterial Foraging Algorithm (BFA). These algorithms are used for the scheduling the appliance load in real time pricing. Both algorithms are used to shifting the load from on-peak hours to off-peak hours in RTP and reduced the electric cost and PAR. We compare both algorithms in terms of electricity cost, PAR and used comfort. Our simulation results show that the EWA outperformed the BFA in terms of electricity cost however, BFA reduced the PAR as compared to EWA.

Demand Side Management Using Strawberry and Enhanced Differential Evolution Algorithms

Today, electricity is the most worthwhile resource which makes human life very easy. To overcome the gap among demand and supply of electricity, new techniques and methods are being explored. However, electricity demand is increasing constantly, which causes serious crisis. To tackle this problem, demand side management integrated with traditional grids through intercommunication between utility and customers. In this research work, we comparatively look over the two meta-heuristic algorithms: strawberry algorithm (SBA) and enhanced differential evolution (EDE) algorithm in terms of cost minimization, peak to average ratio reduction and maximizing user comfort. For electricity bill calculation, critical peak pricing (CPP) scheme is used. Simulation results show that both optimization techniques work significantly to achieve the desired objectives. SBA performs better then EDE in term of cost minimization while EDE performs better then SBA in terms of user comfort (UC) maximization, PAR reduction and energy consumption minimization.

Home Energy Management Based on Harmony Search Algorithm and Crow Search Algorithm

In this work, we evaluated the performance of home energy management system (HEMS) using two meta-heuristic optimization algorithms: harmony search algorithm (HSA) and crow search algorithms (CSA). For electricity bill calculation we use real time pricing (RTP) signals. Our main objectives are optimization of energy consumption, electricity cost minimization and peak to average ratio (PAR) reduction. Our results depict that CSA performs better than HSA in term of cost and HSA perform better than CSA in term of PAR reduction and user comfort (UC) maximization. Results also verify that there will always be trade-off between electricity cost and waiting time.