Investigating the Performance of Non-standard Overcurrent Relay with Integration of Photovoltaic Distributed Generation in Power Distribution System

The electricity demand is increasing daily, so the generation power should be raised to fulfil that demand. Renewable distributed generation-based photovoltaic sources are one of the best solutions to satisfy the Power Distribution System (PDS) as long as the fossil resources are on the verge of extinction. At the same time, connecting the Photovoltaic Distributed Generation (PVDG) to the PDS may cause issues with the system's technical parameters, such as a protection system based on overcurrent relays, unless they are optimally allocated. In this context, this paper will be devoted to optimally allocating multiple PVDG units in the PDS using the Slime Mould Algorithm (SMA), meanwhile studying the impact of that optimal integration on the overcurrent protection system that will be represented and based on various chosen non-standard overcurrent relays (NS-OCRs) which many researchers develop, and trying to figure out and pick up the best type that provides improvement to the protection system including the minor impact on the coordination time interval. To achieve the maximum and best of the requested results, a multi-objective function was proposed to be minimized based on the sum of total active power loss, total voltage deviation, and total operating time of the relays

Composition of Aspectual Requirements: A Multi-criteria Process for Conflict Resolution.

In Aspect Oriented Software Development, aspects are not only used at the programming level but also tend to arise at the requirements analysis and software architecture design. We previously proposed an approach named AspeCiS (An aspect-oriented Approach to Develop a Cooperative Information System) to develop a Cooperative Information System from existing Information Systems by using their artifacts such as existing requirements and design elements. This approach include an important step in which the aspectual requirements composition problem is considered to be one of the remaining challenges. So, when multiple aspectual requirements share the same join point, undesired behavior may emerge and a conflict resolution process must be triggered. This study presents a conflict resolution process among aspects during the requirements engineering level: A priority value is computed for each aspect and it allows identifying a dominant aspectual requirement on the basis of stakeholder priority. This process is more formal than those currently proposed, which requires a trade-off negotiation to resolve conflicts

Predicting Damage in Notched Functionally Graded Materials Plates through extended Finite Element Method based on computational simulations

Presently, Functionally Graded Materials (FGMs) are extensively utilised in several industrial sectors, and the modelling of their mechanical behaviour is consistently advancing. Most studies investigate the impact of layers on the mechanical characteristics, resulting in a discontinuity in the material. In the present study, the extended Finite Element Method (XFEM) technique is used to analyse the damage in a Metal/Ceramic plate (FGM-Al/SiC) with a circular central notch. The plate is subjected to a uniaxial tensile force. The maximum stress criterion was employed for fracture initiation and the energy criterion for its propagation and evolution. The FGM (Al/SiC) structure is graded based on its thickness using a modified power law. The plastic characteristics of the structure were estimated using the Tamura-Tomota-Ozawa (TTO) model in a user-defined field variables (USDFLD) subroutine. Validation of the numerical model in the form of a stress-strain curve with the findings of the experimental tests was established following a mesh sensitivity investigation and demonstrated good convergence. The influence of the notch dimensions and gradation exponent on the structural response and damage development was also explored. Additionally, force-displacement curves were employed to display the data, highlighting the fracture propagation pattern within the FGM structure

A new multi-criteria decision process to prioritise requirements

International audienceMost software projects have more candidate requirements than can be realised within the time and cost constraints. This paper presents a novel multi-criteria decision analysis process to prioritise requirements. The novelty of the presented idea is three-fold. Firstly, to prioritise requirements, it distinguishes two categories of requirements according to their level of abstraction: low-level requirements and high-level requirements. Then, it relates business goals to the requirements of low-level which contribute to their fulfilment. This will improve the completeness and traceability of requirements. Secondly, requirements prioritisation is based on their degree of contribution to the identified business goals and their importance. So, business goals become the evaluation criteria. Finally, this process takes into account relationships and dependencies that may exist between business goals. At this end, we employ analytic hierarchy process (AHP) method to give weights to business goals and Choquet integral to calculate a global score, i.e. priority, for requirements

Hydrochemistry and origin of principal major elements in the groundwater of the Béchar–Kénadsa basin in arid zone, South-West of Algeria

Béchar region is located in the southwest of Algeria, characterized by an arid climate with a Saharan tendency. It is subject to an increasing demand for water like all the great agglomerations due to the economic and demographic development. The groundwater of region is deteriorating because of the economic development, and the rapid growth of population. This article is devoted to the study of hydrochemistry and processes of mineralization of groundwater in this region. The results of physicochemicals analyses shows the same chemical facies of the chloride and sulphate-calcium and magnesium type, with high mineralization from North-East to South-West to the outlet of Béchar–Kénadsa basin. The determination of the mineralization origin and the main major elements were approached by multivariate statistical treatment and geochemical. This method has identified the main chemical phenomena involved in the acquisition of mineralization of water in this aquifer. These phenomena are mainly related to the dissolution of evaporite formations, the infiltration of runoff water and direct ion exchange and mixing. However, the high mineralization anomaly is observed at the centre of Béchar–Kénadsa basin progressively by going to the outlet of this basin

Roles of Machine Learning and Deep Learning for Supporting E-Learning Processes and Learning Outcomes through The Lens Of System\u27s View of E-Learning Success Model

Machine learning and deep learning are two core research domains in artificial intelligence. In recent years, the roles of artificial intelligence in education—the fundamental concepts of artificial intelligence, machine learning, and deep learning- have been extensively investigated. However, relatively scant attention has been paid to the roles of artificial intelligence(AI), especially machine learning (ML) and deep learning (DL), in supporting the e-learning process and outcomes. The primary objective of this study is to investigate the roles of two artificial intelligence subfields, ML and DL, in managing each of the six components of distance learning systems through the lens of the system\u27s view of the e-learning success model. AI and computer and information technologies have enabled an intelligent learning environment facilitating personalized adaptive learning development. Further, managing dropouts in online education has been an important issue. DL can predict potential obstacles and areas where students will likely struggle by analyzing historical learning management systems (LMS) data and learning patterns. With this insight, educators and platforms can provide targeted support and resources to help students overcome challenges before they lead to dropout

Numerical study of the mechanical behaviour and damage of fgm bent pipes under internal pressure and combined bending moment

The main objective of this work is the numerical prediction of the mechanical behaviour up to the damage of the bends of the functionally graded material (FGM) type ceramic/metal pipes. Firstly, the effective elastoplastic proper-ties of bent FGM pipes were determined using the homogenisation law by the Mori–Tanaka models for the elastic part and TTO (Tamura-Tomota-Ozawa) for the plastic part based on a rule of mixtures per function in the form of a power law. Our work also aims at the use of a meshing method (UMM) to predict the behaviour of the FGM by finite element in the mesh of the model. The analysis was performed using the UMM technique for different loading cases and volume fraction distribution. Two stages are necessary for the analysis of the damage: the first is the model of initiation of the damage established by the criterion of maximum deformation named MAXPE and the second is criterion of the energy of the rupture according to the theory Hillerborg used to determine damage evolution. Both stages involve a 3D finite element method analysis. However, for damage, the XFEM technique was used in our UMM method to predict crack initiation and propagation in FGM pipe bends. The results of the numerical analysis concerning the mechanical behavior showed, that if the nature of the bent pipes is in FGM, a good reduction of the various stresses compared to those where the nature of the pipe is metallic material. The results were presented in the form of a force–displacement curve. The validation of the proposed numerical methodology is highlighted by comparisons of current results with results from the literature, which showed good agreement. The analysis took into account the effect of the main parameters in a bent FGM pipe under internal pressure and bending moment on the variation of the force–strain curves

Experimental Investigation of the Absorption Behavior of Date Palm Fiber Reinforced Iso-Polyester Composites: Artificial Neuron Network (ANN) Modeling

The present article attempts to study absorption properties of bio-composites reinforced with date palm fibers. The effect of fiber loading on water absorption at room temperature 25 degrees C was investigated. The weight gain was measured of bio-composites immersed in distilled water, seawater and rainwater, for more than 670 hours, until reaching the saturation with a measurement interval between 24 and 48 hours. To understand absorption phenomenon, scanning electron microscopy was used. Porosity rate was determined using image J software. It was noted the water absorption rate of the bio composites reached 16.20%, 16.33%, 21.94%, 41.99% for seawater, 16.41%, 16.52%, 20.84%, 30.08% for distilled water, and 14.00%, 14.04%, 19.30%, 36.94% for rainwater, respectively. The absorption increases when increasing fiber content. The diffusion coefficient of bio-composites has minimum and maximum values of about 1.94 x 10(-6)mm(2)/s and 3.99 x 10(-6)mm(2)/s, respectively. Palm fibers are highly porous. The porosity value was higher than 51%. To predict the absorption rate, artificial neural network method was used. The ANN models obtained are very well correlated with the experimental data where the values of the correlation coefficient of the datasets are all beyond 0.99 and the average error value was estimated at 3 x 10(-5)