Search

In Liquid Composite Molding (LCM), a fabric can be formed by highly double curved punch geometries. During the forming step, various types of defects can appear and may have a significant influence on the mechanical properties of the final composite materials. Till now, these defects have not been fully studied and/or understood. The aim of this study was to understand the mechanisms leading to the forming of mesoscopic defects (buckles and sliding), as well as their effect on the behavior of composite materials. To achieve this goal, an experimental machine was designed and built. The machine generates different types of defects, with controlled and adjusted amplitudes (calibrated defects) in samples of a fabric. These samples were then used to manufacture composite samples with calibrated defects, by an LCM process, in order to test and compare them with composite samples without defects. Thanks to this machine, calibrated forming defects that simulate the defects of an LCM process were generated, and the experimental parameters corresponding to the appearance of these defects were defined for two types of fabrics based on glass and carbon fibers. This work provides insight into the forming mechanisms of the buckle and sliding defects that occur during an LCM process.

© 2021 John Wiley & Sons, Ltd. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1002/cta.3023

Geopolymers produced with metakaolin (MK) and thermally untreated phosphate sludge (PS) are beneficial and environmentally advantageous materials, but their fragility limits its applications. The present research aims to evaluate the influence of polypropylene fibers PPF inclusion in MK/PS based geopolymers in view of overcoming the brittleness of these materials. The geopolymer matrix was prepared by mixing the thermally untreated phosphate sludge with the metakaolin in a proportion of 50% by weight, then short polypropylene fibers (PPFs) as reinforcement material were incorporated in amounts of 0.25, 0.50, 1, and 1.5%. Composite performances were assessed in the fresh state through flow measurement, and in the hardened state through the properties of the composites under bending and compressive loading conditions. In addition, the fiber/matrix interfacial contact area was examined using scanning electron microscopy (SEM). The outcomes demonstrate that the PPF incorporation of up to 1.5% by weight into MK/PS based geopolymer paste significantly improves the flexural strength with an increase of 41% (6.41 and 9.62 MPa), as well as leads to a slight decrease of compressive strength and density. The findings of the current research reveals also that MK/PS based geopolymers can achieve a high ductility with an adequate reinforcement.

Wide-area damping controllers (WADCs) are effective means of improving the damping of inter-area oscillations and thereby ensuring a secure operation of modern highly stressed interconnected power systems; however, their implementation costs are high. Therefore, the controller must be well configured and designed to ensure its cost-effectiveness. Several techniques have been proposed in the literature to design effective controllers and good results have been achieved. However, some important practical aspects that could potentially impact the performance of the designed controller have not been addressed or studied in sufficient detail in these previous works. One such aspect is assessing the performance of the designed controllers under major system upsets resulting in large deviations in the frequency and fluctuations in the power. These may lead to controller saturation which could negatively impact its damping performance or even cause instability. In this paper, the impact of such large upsets is investigated on several test systems via extensive small- and large-signal analyses and it is shown that, during severe transients, controller saturation may occur and persist over a long period of time, posing a potential threat to the power system stability. This paper presents a very effective solution to alleviate this problem and help design more robust WADCs. The simulation results show that the proposed solution works well and leads to improved power system stabilisers performance during transient upsets.

During the present work, we compared the adsorption of heavy metals (Cu, Co, Ni and Pb) using the natural clay (Sale-Morocco) as a potential adsorbent in the treatment synthetic wastewater. The natural clay was characterized and identified using X-ray diffraction (XRD) analysis. Then, the adsorbent mass, the contact time, the pH of the solution and the initial concentration ions for varying heavy metals (Cu, Co, Ni and Pb) were measured and investigated. The optimal contact time necessary for the efficient adsorption of various heavy metals investigated (Cu, Co, Ni and Pb) are 85, 84, 85 and 83 min, respectively. The pH of the solution tested of different heavy metals Cu, Co, Ni and Pb are 8.5, 8, 8 and 8.5, respectively. Further, the initial concentration ions for the adsorption capacity of different heavy metals Cu, Co, Ni and Pb are 145, 140, 140 and 135 ppm, respectively. The elimination yield values of the heavy metals such as Cu, Co, Ni and Pb using natural clay studied are 86, 85.5, 84 and 85%, respectively. Freundlich and Langmuir adsorption isotherms again support our experimental data and natural clay could be investigated as a potential adsorbent for the adsorption of different heavy metals (Cu, Co, Ni and Pb) contained in the treatment synthetic wastewater.

In order to optimize and reduce the rate of inorganic micropollutants discharged by various metal facilities, according to wastewater treatment standards and environmental protection, we have proceeded by studying the adsorption of heavy metals such as nickel using sea shells-Mehdia-Morocco as a natural adsorbent. After the preparation of the support, we are interested in the analysis of the physico-chemical parameters influencing the removal of heavy metals such as the kinetics (6.5 to 50 mg.L-1), the initial concentration of the nickel solutions (10 mg.L-1) and the pH of the solution (5.5 to 9.5). All the results obtained show that the adsorption process is favourable to physisorption and monolayer. First, the adsorption amount was found to be 4.05 mg.g−1. Among others, the adsorption process is expressed by the second order kinetic law (R2 = 0.999, 1 / n = 0.37). Moreover, the thermodynamic parameters after using Van't Hoff's equation showed that the studied process has an endothermic, stable and spontaneous effect (ΔG ° = −0.37 Kj.mol−1, ΔH° = 47.31 Kj.mol−1 et ΔS° = 150.56 J.mol−1). Finally, the linear isothermal models of Langmuir (R2 = 0.925), Freundlich (R2 > 0.96) and Temkin (R2 = 0.891), show that the binding and elimination of nickel by this shell is rapid with the increase of the above-mentioned parameters.

To operate a cross-dock successfully, an efficient assignment of trucks to docks is one of the key decisions. In this paper, we are interested in the cross-dock assignment of trucks to docks problem, where the number of trucks exceeds the number of docks. The objective is to minimize the cost of transferring goods within the cross-dock while avoiding delivery penalties. This problem being NP-hard, we use Variable Neighborhood Search metaheurisitc (VNS) to solve it approximately. More specifically, we conduct a structured empirical study to compare several VNS configurations and to find which is/are the most effective for this cross-dock problem. In this work, first we analyze the way the search strategy and the neighborhood operators can be combined in a VNS framework according to their efficiency within a local search. Then the best configurations are tested within three VNS variants, namely Basic VNS (BVNS), General VNS (GVNS) using Basic VND (B-VND) and GVNS using Union VND (U-VND) according to the number of used operators and the order of applying these operators. Finally we evaluate the influence of the stopping criterion within these variants. Some significant differences among these configurations are shown and illustrated by conducting the Friedman test.

While the production and usage of pesticides, pharmaceuticals, and personal care products have greatly improved the quality of life for humans, their application has increasingly been contaminating...

The effect of intercritical annealing heat treatment on mechanical and corrosion properties of fer-rite/martensite dual-phase steels with and without deformation by rolling has been investigated in this study. The X70 steel was rolled at intercritical temperatures (760 and 800 °C) with 30% amount of reductions followed by water quenching in order to produce dual-phase microstructure. The experimental results show that microstructures, mechanical and corrosion properties and were strongly affected by intercritical rolling conditions. It is established that the intercritical rolling provides a fibrous structure, and improves the mechanical and corrosion properties of X70 dual phase steel. It was found that after intercritical rolling (DQR), grain refinement and hardness improved significantly compared to intercritical heat-treated steel without rolling (DQ). A carefully conducted comparison of resistance corrosion of the representative specimens obtained after (DQ) and (DQR) treatments has been studied. (DQR) treatment shows better corrosion resistance than (DQ) treatment. The microstructure, mechanical and corrosion properties of the rolled X70 dual phase steel were investigated by optical microscopy, scanning electron microscopy, hardness tests and electrochemical measurements.

Hard coatings based on chromium carbides and chromium borides are widely used in applications that require mechanical performance, i.e., high hardness and low friction coefficient and good corrosion resistance. In this work, we made layers of chromium carbides and chromium borides on the surface of low carbon steel through some specific treatments. For chromium carbides, the cementation in a solid medium followed by electroplating of chromium on the surface and finally the application of annealing treatment at temperatures between 500 and 1100 °C for 1 hour. For chromium borides, the boriding treatment in solid medium at 900 °C for 4 hours followed by chromium electroplating on the steel surface and finally the application of annealing treatment at temperatures at 950 °C for 1 and 2 hours. The obtained results show that, in the first case, the cemented layer and the chromium deposited on the surface combine to form chromium carbides on the treated surface after annealing. Similarly, for the second case, boron diffusion and chromium deposition lead to chromium borides on the treated surface. The characteristics of the chromium carbides and chromium borides obtained are very similar to those of chromium carbides and chromium borides obtained by other processes.

© 2020 by the authors; licensee IIETA, Edmonton, Canada. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/).

The aim of this work is to study the effect of tempering on the corrosion behavior of X70 HSLA (high-strength low alloy) steel weldments in aerated 1 M sulfuric acid solution. Two different temperatures, 450 °C and 650 °C, were selected to investigate the tempering effect on samples used in this study. Through the results obtained from microstructural characterization, tensile tests, microhardness tests, and potentiodynamic tests, it was observed that the mechanical properties were optimal after tempering. Additionally, the polarization resistance increased after tempering by reduction of factors that induce corrosion, such as residual stress. Electrochemical impedance spectroscopy was also performed to clear the mechanism and kinetics of corrosion.

International audience; Advancing in the process of extending the use of composites for structural parts applications, it is inevitable to work on complex shapes. That is the main reason why understanding the complex forming mechanisms and the factors put into play during the process of composite materials is a major interest for both pre-impregnated forming and dry fabric preforming. Thus, the appearance of defects is a major concern and predicting their appearance for optimal product quality is the priority. A great number of authors showed that defects degrade the overall performance of the composite by creating local heterogeneities. Many factors can initiate these defects. This article is an assembly of the development of the literature on this subject. It is an attempt to provide a description for each defect and a classification order following the scale, the behavior mechanisms, the appearance plan. This will help to converge toward an identification of the defects manifesting during the composite forming.

This paper presents the application nonlinear control to regulate the rotor currents and control the active and reactive powers generated by the Doubly Fed Induction Generator used in the Wind Energy Conversion System (WECS). The proposed control strategies are based on Lyapunov stability theory and include back-stepping control (BSC) and super-twisting sliding mode control. The overall WECS model and control scheme are developed in MATLAB/Simulink and the simulation results have shown that the BSC leads to superior performance and improved transient response as compared to the STSMC controller.

The present paper deals with a real-time assessment of a fuzzy –backstepping based control applied to a battery-supercapacitor (SC) hybrid energy storage system (HESS). To properly emulate the behavior of an electric vehicle, the proposed topology is extended to a PMSM drive, that represents the traction part. The proposed control scheme is divided into two parts: The first part plans a fuzzy logic power management approach, to operate the system in a smart way: First, It ensures an optimal load power-sharing, focusing the operation of the involved sources in a safe mode. Second, a quite regulation of both the dc bus and the SC voltage without additional controllers. The second part proposes a back-stepping direct torque control (BS-DTC), associated to a space vector modulation (SVM) strategy, to ensure decoupled torque and flux control of the PMSM machine. The experimental results, conducted on a small-scale system, controlled via two dSPACE 1104 cards, prove the effectiveness of the proposed control techniques, with good performances in dynamic and steady state.

Securing energy supply and speeding up the transition towards a reliable, sustainable, low-carbon energy system are among the major current and future challenges facing Europe. Importing dispatchable solar electricity from North Africa is considered as a potential and attractive option. Nevertheless, as things currently stand, the European Commission focuses mainly on the exploitation of the existing wind power potential in the North Sea, largely ignoring the solar power potential in the Sahara region of North Africa. After discussing the major challenges and issues facing Europe to achieve the assigned ambitious objectives, the paper emphasises the importance of North Africa's solar resources in helping Europe to successfully address the challenge of decarbonising its electricity system, in particular with regards to the security of supply and sustainability. Within these two major challenges, the paper explores the issues of access, barriers and opportunities. The paper highlights why the EU's energy and climate goals will not be achievable without adequate grid expansion and grid-scale energy storage facilities, as well as other innovative measures to manage demand and ensure a secure energy supply. In this respect, the paper shows how the import of dispatchable electricity from North Africa via specific HVDC links could play a key role in helping the EU achieve its energy targets in a cost-effective way without recourse to significant investments in transmission infrastructure and storage facilities. The paper then attempts to identify and analyze the main barriers that continue to inhibit the export of solar electricity from North Africa to Europe. Finally, to make the project more attractive and achievable in the near future, the paper proposes a systematic approach for setting up energy import scenarios. A promising import scenario is presented where energy import via Italy is shown to be a more viable and effective solution than via Spain. Keywords: Renewable energy, Sustainable energy development, European supergrid, CSP-HVDC, Desertec

In recent years, guaranteeing that large-scale interconnected systems operate safely, stably and economically has become a major and emergency issue. A number of high profile blackouts caused by cascading outages have focused attention on this issue. Embedded HVDC (High Voltage Direct Current) links within a larger AC power system are known to act as a “firewall” against cascading disturbances and therefore, can effectively contribute in preventing blackouts. A good example is the 2003 blackout in USA and Canada, where the Quebec grid was not affected due to its HVDC interconnection. In the literature, many works have studied the impact of HVDC on the power system stability, but very few examples exist in the area of its impact on the system security. This paper presents a control strategy for HVDC systems to increase their contribution to system security. A real-time closed-loop control scheme is used to modulate the DC power of HVDC links to alleviate AC system overloads and improve system security. Simulations carried out on a simplified model of the Hydro-Quebec network show that the proposed method works well and can greatly improve system security during emergency situations.

Background: In recent years, demand for electricity has increased considerably, while the expansion of generation and transmission has been very slow due to limited investment in resources and environmental restrictions. Methods: As a result, the power system becomes vulnerable to disturbances and instability. FACTS (Flexible AC Transmission Systems) technology has now been accepted as a potential solution to this problem. This paper deals with the modelling, simulation and fuzzy self-tuning control of a DSTATCOM to enhance the stability and improve the critical fault clearing time (CCT) in a single machine infinite bus (SMIB). A detailed modelling of the D-STATCOM and comprehensive derivation of the fuzzy logic self-tuning control is presented. Results: The dynamic performance of the power system with the proposed control scheme is validated through in a simulation study carried out under Matlab/Simulink and SimPowerSystems toolbox. Conclusion: The results demonstrate a significant enhancement of the power system stability under the simulated fault conditions considered.

For decades, the industry is a huge consumer of resources, generates waste and has serious impacts on our planet. In order to preserve the environment, new economic models are emerging including the circular economy. Circular economy is a system that fits with sustainability and aims to reduce both resources consumption and waste production. Among the components of circular economy, industrial ecology is the collaboration of industries on a territory in order to exchange materials, water or energy through industrial symbiosis. Industrial ecology and industrial symbiosis are more and more present in the literature. However, most of articles in the literature focused on the strategic decision level. In this paper, we focus on tactical decisions, and investigate production planning as a lot sizing problem in a collaborative context involving two actors belong an industrial symbiosis.

Organizations have to deal with increasing challenges in their supply chains. Their decision makers brought to balance economic performance with environmental and social issues. Methods and concepts for jointly optimizing economic, environmental and social cost of operations in supply chains are challenging. Decision support systems could help organizations to support sustainability in their supply chains. A collaborative decision-making framework for sustainable supply chain planning is proposed in this paper. This framework facilitates the development of multi-party collaborative relationships across a network to improve the sustainability of delivered products. It supports a new Information and Communication Technology (ICT) system platform. The platform provides insight for infrastructure and visibility to support supply chain sustainability requirements. The proposed decision support system proposes simultaneously collaboration and sustainability functionalities missing in many existing supply chain planning systems. This system has been evaluated and validated through a pilot program across a range of food supply networks. The work is motivated and applied by a major European research program in the agri-food supply chain.

During this work, we have been able to eliminate and/or reduce the nickel-type (Ni2+) heavy metals contained in the wastewater-model samples by the adsorption technique on natural clay as mineral adsorbent. The present clay was taken from the Ain Dorrij - Ouezzane region of Morocco and characterized by X - Ray Diffraction (RDX) and then applied to the adsorption of the nickel element. The physicochemical parameters such as the pH, the temperature and the concentration of the prepared aqueous samples (nickel adsorption rate (Atomic Adsorption Spectroscopy (AAS)) were optimized as well as for the mass of adsorbent (clay), time and stirring speed. The results obtained during this study have shown that the nickel removal rate is of the order of 70-75% according to the linear forms of the isothermal models (Langmuir and Freundlich) of the adsorption kinetics in a range of time between 30 and 130 min.

In this paper, we propose a segmentation method based on region growing and evolutionary algorithms. Before segmentation, the number of classes is determined by the principle of maximum entropy. The proposed approach is validated on some synthetic and real images and, it shows to be very interesting as decision support in quality control.

This paper introduces a comprehensive Mixed Integer Linear Programming (MILP) model for a sustainable supply chain network design problem, and an efficient Distributed Approximation Approach (DAA) ...

International audience; Cross-docking terminals or hubs are used by many logistics distribution companies and play a critical role in the performance of the global supply chain. Recent studies on Physical Internet cross-docking hubs (PI-hubs) have shown promising results for optimization problems in different structures such as Road-Road, Rail-Road and Road-Rail PI-hubs. This paper addresses the optimization of trucks’ scheduling and PI-containers’ grouping in Rail-Road cross-docking PI-hubs. The study is performed considering uncertainty on trucks’ arrival time. The problem is formulated as a multi-objective chance constrained mixed integer programming model. The objective is to minimize the number of used wagons, PI-containers distance and the total tardiness of inbound trucks according to a Lexicographic Programming order.

Firms are more and more interested in reducing the carbon footprint related to their activity. Their supply chain remains one of the main sources of carbon emissions. Better operational routines and planning adjustments have proven to be an effective way to reduce the carbon emissions but not enough. In this paper, the carbon footprint is taken into consideration in the Demand Driven Material Requirements Planning (DDMRP) strategic buffer positioning problem. The focus is put on the storing activities and transportation, for which a function was proposed to quantify the associated emissions. Two environmental regulations are simulated: carbon emissions tax and carbon emissions cap. These approaches have been implemented in a buffer positioning model with a cost minimization objective function. The resulting models were solved using CPLEX solver for multiple instances. The numerical results provide a better measurement of the buffer positioning impact on the carbon emissions. The observed sensibility of the problem to the environment parameters would give insights for further research work.

International audience; This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure for fibre bed compaction measurements. A glass fibre 2/2 twill weave and a biaxial (±45°) glass fibre non-crimp fabric (NCF) were tested in dry and wet conditions. All participants used the same testing procedure but were allowed to use the testing frame, the fixture and sample geometry of their choice. The results showed a large scatter in the maximum compaction stress between participants at the given target thickness, with coefficients of variation ranging from 38 % to 58 %. Statistical analysis of data indicated that wetting of the specimen significantly affected the scatter in results for the woven fabric, but not for the NCF. This is related to the fibre mobility in the architectures in both fabrics. As isolating the effect of other test parameters on the results was not possible, no statistically significant effect of other test parameters could be proven. The high sensitivity of the recorded compaction pressure near the minimum specimen thickness to changes in specimen thickness suggests that small uncertainties in thickness can result in large variations in the maximum value of the compaction stress. Hence, it is suspected that the thickness measurement technique used may have an effect on the scatter.

In this paper, robust Unknown Input MultiOb-servers (UIMOs) are designed, in the presence of disturbances, for nonlinear systems based on a discrete uncoupled state mul-timodel. The diagnosis is conducted in the presence of actuator and sensor faults. Firstly, a robust detection against disturbances is investigated. Then, a new bank of UIMOs is designed to accomplish the isolation task using generated structured residuals. Sufficient conditions are developed and given in terms of linear matrix inequalities with equality constraints to compute the uncoupled state multiobserver gains. The simulation results prove the efficiency of the proposed scheme of fault detection and isolation and show that the proposed fault detection and isolation technique is suitable for the disturbed Multiple-Input Multiple-Output (MIMO) nonlinear systems.

To make a product, many components: made inside a supply chain or provided by external suppliers, may be needed as specified in the bill of material (BOM). This variety exposes the production process to various risks as stock ruptures for instance. Due to companies efforts to face the volatile demand and market pressure, Work-in-process (WIP) inventories become redundant in flow production lines. Uncertainty became a major flaw of the system, to which many methods were developed and adopted to manage and optimize the use of resources. One of the most recent methods is Demand Driven Material Requirement Planning (DDMRP) that uses buffers: visual indicators of the net flow integrating the real stock, the actual demand and the expected provisions; This paper describes an approach to solve the optimization problem of minimizing the storing costs, under service time constraint for uncapacitated buffer positioning alongside with the buffer allocation following the DDMRP planning methodology in a hybrid MTO/MTS manufacturing system. Finally, numerical examples are applied to test the efficiency and the performance of the developed algorithm.

© 2020 John Wiley & Sons Ltd. This is the accepted version of the following article: Belabbas, B, Denai, M, Allaoui, T. Hierarchical energy management and control to improve the reliability and efficiency of wind farms connected to the grid. Int Trans Electr Energ Syst. 2020;e12400., which has been published in final form at https://doi.org/10.1002/2050-7038.12400.

The purpose of this paper is to introduce the concept of fuzzy Lyapunov functions to study the notion of stability of equilibrium points for fuzzy dynamical systems associated with fuzzy initial value problems, through the principle of Zadeh. Our contribution consists in a qualitative characterization of stability by a study of the trajectories of fuzzy dynamical systems, using auxiliary functions, and they will be called fuzzy Lyapunov functions. And, among the main results that have been proven is that the existence of fuzzy Lyapunov functions is a necessary and sufficient condition for stability. Some examples are given to illustrate the obtained results.

3D medical image processing with deep learning greatly suffers from a lack of data. Thus, studies carried out in this field are limited compared to works related to 2D natural image analysis, where very large datasets exist. As a result, powerful and efficient 2D convolutional neural networks have been developed and trained. In this paper, we investigate a way to transfer the performance of a two-dimensional classiffication network for the purpose of three-dimensional semantic segmentation of brain tumors. We propose an asymmetric U-Net network by incorporating the EfficientNet model as part of the encoding branch. As the input data is in 3D, the first layers of the encoder are devoted to the reduction of the third dimension in order to fit the input of the EfficientNet network. Experimental results on validation and test data from the BraTS 2020 challenge demonstrate that the proposed method achieve promising performance., Comment: Multimodal Brain Tumor Segmentation Challenge 2020

International audience; The purpose of this chapter is to study the benefits of collaboration among shippers in less than truckload transportation and to show the role of transhipments in the collaboration. In this chapter, the authors propose a new model for the pickup and delivery problem with transhipment and time windows to study the role of transhipment in the green collaborative transportation. A transportation network with two transportation modes road and sea is considered. Different scenarios are optimized and compared in terms of cost and CO2 emissions: with/without collaboration and with/without transhipment. The proposed model is applied to a case study with real data from three agri-food companies in short sea shipping context. With this model, the total cost and the total amount of CO2 emissions are reduced by using collaboration and transhipment. An experimental study was conducted to illustrate this positive impact.

The present work aims to study the affinity of a component of the thyme essential oil “thymol” to natural Moroccan clay “Rhassoul” using the adsorption technique. The physicochemical characterizations of the purified and modified clay were carried out by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), DTA/TGA, and SEM-EDX. Thymol adsorption tests on the purified Rhassoul (Rh-P) and the modified one by CTAB (Rh-CTAB) were followed by UV-visible spectroscopy. They show that the adsorption isotherms can be described by the Freundlich model and that the kinetics of adsorption is in accordance with the pseudo-second-order model for the two clays. Adsorption capacities obtained were of the order of 6 mg/g for the purified Rhassoul and 16 mg/g for the modified Rhassoul by cetyltrimethylammonium bromide (CTAB). These values show that the modified Rhassoul has a better adsorption capacity compared to the purified Rhassoul.

Dimensionality reduction is widely used in machine learning and big data analytics since it helps to analyze and to visualize large, high-dimensional datasets. In particular, it can considerably help to perform tasks like data clustering and classification. Recently, embedding methods have emerged as a promising direction for improving clustering accuracy. They can preserve the local structure and simultaneously reveal the global structure of data, thereby reasonably improving clustering performance. In this paper, we investigate how to improve the performance of several clustering algorithms using one of the most successful embedding techniques: Uniform Manifold Approximation and Projection or UMAP. This technique has recently been proposed as a manifold learning technique for dimensionality reduction. It is based on Riemannian geometry and algebraic topology. Our main hypothesis is that UMAP would permit to find the best clusterable embedding manifold, and therefore, we applied it as a preprocessing step before performing clustering. We compare the results of many well-known clustering algorithms such ask-means, HDBSCAN, GMM and Agglomerative Hierarchical Clustering when they operate on the low-dimension feature space yielded by UMAP. A series of experiments on several image datasets demonstrate that the proposed method allows each of the clustering algorithms studied to improve its performance on each dataset considered. Based on Accuracy measure, the improvement can reach a remarkable rate of 60%.

The aim of this study is based on natural clay as an adsorbent in the elimination of polyphenols from olive mill wastewater (OMW). This clay was analyzed using XRD, SEM/EDX, FTIR, surface area measurement (BET method), thermal analysis (TGA/DTA), and X-ray fluorescence (XRF) and then used in adsorption experiments. The results reveal that the best quantity of adsorption of polyphenols is 161 mg/g at the temperature of 25°C, but they decrease at 35°C and 45°C. A great agreement with pseudo-second-order and Freundlich model is represented by kinetic and isotherms models, and several parameters such as ΔG0, ΔS0, and ΔH0 were determined using the thermodynamic function relationship.

Object detection is considered as the cornerstone of many modern applications such as Drone vision and Self-driven cars. Object detectors, mainly those which are based on Convolutional Neural Net-works (CNNs) have received great attention from many researchers because they were able to yield remarkable results. However, most of them fail when it comes to detecting overlapping and small objects in images. There are two families of detectors: the first family detects more objects but with imprecise bounding boxes, while those of the second family do the opposite. In this paper, we propose a solution to this problem by combining the two families, in a way similar to classifier combination. Our solution has been validated through the combination of two famous detectors, Faster R-CNN which detects more objects and YOLO which produces accurate bounding boxes. However, it is more general and it can be applied to other detectors. The evaluation of our method has been applied to the PASCAL VOC dataset and it gave promising results.

Collaboration in supply chains by sharing resources has an important role in Physical Internet. It allows the participating supply chains reducing their own and common objective costs. Due to a lack of literature, we focus on hub location problem in collaborative context of two distribution networks belong to different supply chains. The uncertainty corresponding to the supplementary cost included in the setup cost of establishing a shared hub facility is taken into account. Three cases of collaboration and four cost sharing strategies are investigated. Our work allows to verify whether a collaboration proposes better decision and how the total cost is shared among each network to obtain profitable solutions.

International audience; Micromechanical tests are reliable tools to study the failure mechanisms in composites reinforced with continuous fibers. This paper presents an overview of various analytical models developed to study the pullout(push-back) behavior of a fiber embedded in a matrix block to characterize the fiber/matrix interfacial adhesion.Two approaches can be distinguished: one based on a maximum stress criterion (shear lag) and the other basedon fracture mechanics. This article gives an overview of the analytical models reported in the literature tomeasure the shear strength and critical fracture energy at the interface, the parameters influencing theseproperties, the geometry of the model, embedded length of the fiber, fiber diameter and loading conditions(opening width between the knife-edges for example), including components (fiber, matrix, interface), manufacturing route and the resulting defects

The hospital emergency department (ED), which constitutes a complex system with random demands, is the primary facility for urgent health issues. Overcrowding and the limited resources affect the waiting time of patients in the ED. In this research, we model the healthcare services in the ED of a university hospital in Tunisia. We consider simultaneously six patient queues. The goal is to optimize the human and material resources required to reduce the average total patient waiting time. We focus particularly on the medical staff (physicians and nurses) and beds in the ED. We propose a stochastic mixed-integer programming model, which can be solved by a sample average approximation approach. Here, we use the solver ILOG CPLEX Optimization Studio. We compare the performance obtained from the optimization model with what exists currently in the ED under consideration. The results of the experimental study demonstrate that the proposed approach improves the average total patient waiting time by up to 23.24%.

International audience; This paper presents an experimental study of the effect of mesoscopic buckles defect and reinforcement shear, which result from forming, on the low velocity impact behavior of a composite laminate. The material studied is a glass/polyester composite with three layers of mat and one layer of taffeta fabric. To assess the properties induced on the final composite, plates with different amplitudes of calibrated defects and deformations were manufactured. First, the healthy material, which serves as a reference, was subjected to three levels of impact energy to observe the evolution of its behavior and damage mechanisms. Results of the impact tests and observations performed on the materials with calibrated defects identified a negative effect of buckling on elastic parameters and revealed greater damage relative to the healthy material. The reinforcement shear had a beneficial effect on the impact properties of the laminate, which was attributed to the increase in local fiber density.

The sequencing of DNA goes through a step of fragment assembly, this step is known as DNA fragment assembly problem (FAP). Fragment assembly is considered as an NP-hard problem, which means there is no known polynomial-time exact approach, hence the need for meta-heuristics. Three major strategies are widely used to tackle this problem: greedy graph-based algorithms, de Bruijn graphs, and the overlay-layout-consensus (OLC) approach. In this paper, we propose an adaptation of the novel crow search algorithm (CSA) to solve the DNA fragment assembly problem following the OLC model. In order to accelerate the search process and improve the quality of the solutions, we combined CSA with a local search method. Using this combination we were able to obtain very accurate solutions for all the instances of the DNA fragment assembly problem we tested. In fact, our algorithm outperformed all other algorithms designed for the same purpose. Our contribution consists in the implementation of a new assembler for the DNA fragment assembly problem capable of finding for the first time the optimal solutions for 20 out of 30 instances. The approach we proposed to adapt CSA for a discrete optimization problem is a novelty. We preserved the semantics of the original algorithm by applying standard operators from evolutionary algorithms. Following the same approach can make adapting new algorithms for discrete problems more accessible and more efficient compared to mapping algorithms designed for continuous optimization to combinatorial problems.

This is an open access article distributed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/

In the last decade, there have been several initiatives for the deployment of cross-Mediterranean HVDC (High Voltage Direct Current) links to enable the transmission of electrical power from renewable energy sources between North Africa and Europe. These initiatives were mainly driven by the potential economic, environmental and technical benefits of these HVDC interconnections. In previous studies on these projects, some technical aspects of critical importance have not been addressed or studied in sufficient detail. One of these key aspects relates to the impact and possible benefit of these HVDC links on the dynamic performance of the European system which is the major focus of this paper. Several issues relating to the dynamic performance of the system are addressed here. Based on the experience gained from existing AC/DC projects around the world, this paper shows that the HVDC links between North Africa and Europe can greatly improve the dynamic performance of the European system especially in the southern regions. In addition, some challenges on the operation and control of these HVDC links are highlighted and solutions to overcome these challenges are proposed. This review paper, therefore, serves as a preliminary study for further detailed investigation of specific impacts or benefits of these interconnections on the overall performance of the European system.

This paper proposes the application of a dynamic voltage restorer (DVR) to enhance the power quality and improve the low voltage ride through (LVRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation system. In this system, the photovoltaic (PV) plant and the wind turbine generator (WTG) are connected to the same point of common coupling (PCC) with a sensitive load. The WTG consists of a DFIG generator connected to the network via a step-up transformer. The PV system is connected to the PCC via a two-stage energy conversion (dc–dc converter and dc–ac inverter). This topology allows, first, the extraction of maximum power based on the incremental inductance technique. Second, it allows the connection of the PV system to the public grid through a step-up transformer. In addition, the DVR based on fuzzy logic controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the LVRT grid code. The results of the LVRT capability, voltage stability, active power, reactive power, injected current, and dc link voltage, speed of turbine, and power factor at the PCC are presented with and without the contribution of the DVR system.

This paper addresses the optimization of the truck to door assignment problem in cross-docks. It defines a new form of horizontal collaboration between suppliers by sharing the platform’s resources to enhance service level and reduce economical costs. Moreover, this study proposes to solve the problem by considering an uncertain transfer time, that is frequently observed in real-world cross-docks. Due to imprecise arrival time of trucks, equipment breakdown, or workload variation, etc, the actual transfer time tends to be shorter or longer than the prefixed one. This uncertainty is modeled as a triangular fuzzy number then a Fuzzy Chance Programming model has been proposed to solve the problem using possibilistic measures. The efficiency and robustness of both (deterministic and fuzzy) proposed models are tested empirically and obtained results confirm the positive effect of collaboration and uncertainty handling.

Grid-scale electrical energy storage (EES) systems are enabling technologies to enhance the flexibility and reliability of electricity grids with high penetration of intermittent renewable energy sources such as solar and wind. They allow excess of generation to be stored for later use and can respond quickly to power fluctuations. Unfortunately, there is no single type of EES technology that can effectively fulfill all the desired requirements. Hybrid EES (HEES), combining two or more EES, are an emerging, viable solution. While batteries have a higher energy density, supercapacitors (SC) have a higher power density and are characterized by a fast discharge rate. The combination of both technologies results in a HESS solution which can address the challenges associated with the large-scale deployment of distributed renewable energy sources and enhance the grid reliability. The goal is to design a power management strategy to enhance the performance of the HEES. This paper proposes various robust design methods for the control of the power electronics converters and enhance the performance of the power management of the HEES. These robust design strategies are based on pole placement, linear matrix inequalities (LMI), particle swarm optimization (PSO) and genetic algorithm (GA). The performance of these control schemes is compared in terms of the transient response time and robustness. The results obtained demonstrate the effectiveness of the power management strategy (PMS) for the photovoltaic (PV) system with HEES and the enhanced robustness of the controllers using GA and PSO-based tuning techniques.

This paper presents a simulation study of standalone hybrid Distributed Generation Systems (DGS) with Battery Energy Storage System (BESS). The DGS consists of Photovoltaic (PV) panels as Renewable Power Source (RPS), a Diesel Generator (DG) for power buck-up and a BESS to accommodate the surplus of energy, which may be employed in times of poor PV generation. While off-grid DGS represent an efficient and cost-effective energy supply solution particularly to rural and remote areas, fluctuations in voltage and frequency due to load variations, weather conditions (temperature, irradiation) and transmission line short-circuits are major challenges. The paper suggests a hierarchical Power Management (PM) and controller structure to improve the reliability and efficiency of the hybrid DGS. The first layer of the overall control scheme includes a Fuzzy Logic Controller (FLC) to adjust the voltage and frequency at the Point of Common Coupling (PCC) and a Clamping Bridge Circuit (CBC) which regulates the DC bus voltage. A maximum power point tracking (MPPT) controller based on FLC is designed to extract the optimum power from the PV. The second control layer coordinates among PV, DG and BESS to ensure reliable and efficient power supply to the load. MATLAB Simulink is used to implement the overall model of the off-grid DGS and to test the performance of the proposed control scheme which is evaluated in a series of simulations scenarios. The results demonstrated the good performance of the proposed control scheme and effective coordination between the DGS for all the simulation scenarios considered.