International Journal of Engineering Research in Africa Vol. 56

Abstract: The prototyping of dryer design and performance by application of the trial-and-error technique in one-factor-at-a-time (OFAT) testing is completely arbitrary, expensive and time consuming. Reducing product development lead-time and cost while concurrently improving customer satisfaction for a good manufacturer enhance rapid response to market demand which is a highly effective way of improving returns on investment. In this study a numerical model for the digital prototyping of the rectangular passive greenhouse dryer design and the optimization of the batch process in the solar dryer was developed. An interactive, user-friendly computer package ANSYS 14.0 was used to develop an empirical model. The package was used among others, for the response surface methodology (RSM) optimization to specify the dryer parameters that maximize the dryer mean temperature. The factorial experiments in a central composite design (CCD) revealed that only the inlet vent dimensions influence the mean temperature within the greenhouse dryer. The parametric analysis for robust design yielded the inlet vent height of 0.27m and inlet vent width of 0.45m as the optimum design variables that maximize the mean temperature of the drying air as 320.48K (47.30 °C). The numerical approach established facilitated the prototyping and optimization of the batch process in the passive greenhouse dryer.The prototyping of dryer design and performance by application of the trial-and-error technique in one-factor-at-a-time (OFAT) testing is completely arbitrary, expensive and time consuming. Reducing product development lead-time and cost while concurrently improving customer satisfaction for a good manufacturer enhance rapid response to market demand which is a highly effective way of improving returns on investment. In this study a numerical model for the digital prototyping of a rectangular passive greenhouse dryer design and the optimization of the batch process in the solar dryer was developed. Multiple regression was used as the data-analytic system for the factorial experiment to develop an empirical model, predict the response variable and then test hypothesis in an interactive, user-friendly computer package ANSYS 14.0. The package was further used for the response surface methodology (RSM) optimization to specify the dryer parameters that maximize the dryer mean temperature. The factorial experiments in a central composite design (CCD) revealed that only the inlet vent dimensions influence the mean temperature within the dryer. Appraisal of the model through the coefficient of determination ( =0.99973) showed that the model can account for 99.973% variability observed in the dryer mean temperature consequently, the suitability of RSM for the analysis of the dryer variables. The parametric analysis for robust design yielded the inlet vent height of 0.27m and inlet vent width of 0.45m as the optimum design variables that maximize the mean temperature of the drying air as 320.48K (47.30°C). The numerical approach established facilitated the prototyping and optimization of the batch process in the passive dryer.

Abstract: Estimating the state-of-charge of a lead-acid battery at remote seismic nodes is a key factor in managing the available power. Optimal management enables the continuous acquisition of seismic data of an area. This paper presents the management of lead-acid batteries at remote seismic nodes, using the Neural Network model's historical data to estimate the battery's state-of-charge. Powersim (PSIM) simulation tool was used to implement photovoltaic energy harvesting system with a buck mode converter and maximum power point tracking algorithm to acquire historical data. A backpropagation neural network technique for training the historical dataset of hourly points in 500 days on the Matlab platform is adopted, and a feedforward neural network is employed due to the irregularities of the input data. The neural network model's hidden layer contains the transfer function of the Tansig Function to produce the model output of state-of-charge estimations. Besides, this paper is based on the management of estimating the state-of-charge of the lead-acid battery near-realtime instead of relying on the vendor's lifecycle information. The simulated results show the simplicity and optimal estimations of state-of-charge of the lead-acid battery with RMSE of 0.023%.

Abstract: The generation system is an important part of the power system. The problem of generator maintenance scheduling is provided to construct optimal generators preventive maintenance schedules. It aims to improve economic benefits and achieve reliable operation of the power system while satisfying the system and maintenance constraints. In this paper, the binary crow search algorithm is proposed for solving the scheduling problem. This model would schedule maintenance scheme and commitment status of generating units while the objective functions are achieved. The crow search algorithm is a new meta-heuristic optimizer, which has its implementation very simple and easy compared to other optimization techniques. To verify the robustness and effectiveness of the proposed binary crow search optimizer, three test systems namely 6–unit, 21–unit system, and IEEE reliability test system are considered over the planning horizon of 52 weeks. The proposed optimizer is implemented in the MATLAB programming environment. Techno-economic aspects are considered for the generator's maintenance scheduling problem as reliability enhancement economic cost-minimizing issues. The proposed binary crow search optimizer is developed for single and multi-objective frameworks. The simulation results show the proposed binary crow search technique effectiveness and feasibility compared with previously optimizer in solving the generators maintenance scheduling problem with better convergence rate.

Abstract: Nowadays, the cloud computing technology combined with the new generation networks and internet of things facilitate the networking of numerous smart devices. Moreover, the advent of the smart web requires massive data backup from the smart connected devices to the cloud. Unfortunately, the publication of several of these data, such as medical information and financial transactions, could lead to serious privacy breaches, which is becoming the most serious issue in cloud of things. For instance, passive attacks can launched in order to get access to private information. For this reason, several data anonymization techniques have emerged in order to keep data as confidential as possible. However, these different techniques are making the data unusable the most of time. Meanwhile, differential privacy that has been used in a number of cyber physical systems recently emerged as an efficient technique for ensuring the privacy of cloud of things stored data. In this exploratory paper, we study the guarantees of differential privacy of a multi-level anonymization scheme of data graphs. The considered scheme disturbs the structure of the graph by adding false edges, groups the vertices in distinct sets and permutes the vertices in these groups. Particularly, we demonstrated the guarantees that the anonymized data by this algorithm remain exploitable while guaranteeing the anonymity of users.

Abstract: This paper reviews transportation sustainability from theoretical and experiential approaches collected from previous journal papers and books published on the latest ten years. Application of sustainable policies was faced many problems and limitations. This study assigns the available literature researches related to theoretical and applied sustainability in transportation and road construction fields in addition to self-organized steps. Also, the transport sustainability issues, aspects, visions, challenges, and benefits have been presented. Finally, it discusses the future theoretical and experiential research approaches that can connect the current long-winded literature on transportation sustainability which may generate a number of probable future research directions.