Search results for: Launcher vehicles

Authors: Mokhtar Djeddou, Amine Mehel, Georges Fokoua, Anne Tanière, Patrick Chevrier

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Commuters' exposure to air pollution, particularly to particle matter, inside vehicles is a significant health issue. Assessing particles concentrations and characterizing their distribution is an important first step to understand and propose solutions to improve car cabin air quality. It is known that particles dynamics is intimately driven by particles-turbulence interactions. In order to analyze and model pollutants distribution inside the car the cabin, it is crucialto examine first the single-phase flow topology and turbulence characteristics. Within this context, Computational Fluid Dynamics (CFD) simulations were conducted to model airflow inside a full-scale car cabin using Reynolds Averaged Navier-Stokes (RANS)approach combined with the first order Realizable k- εmodel to close the RANS equations. To validate the numerical model, a campaign of velocity field measurements at different locations in the front and back of the car cabin has been carried out using hot-wire anemometry technique. Comparison between numerical and experimental results shows a good agreement of velocity profiles. Additionally, visualization of streamlines shows the formation of jet flow developing out of the dashboard air vents and the formation of large vortex structures, particularly in the back seats compartment. These vortex structures could play a key role in the accumulation and clustering of particles in a turbulent flow

Keywords: car cabin, CFD, hot wire anemometry, vortical flow

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Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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Authors: Nitin Dewangan, Nitin Kattula, Megha Anawat

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Hydraulic reservoir is the key component in the mobile construction vehicles; most of the off-road earth moving construction machinery requires bigger side hydraulic reservoirs. Their reservoir construction is very much non-uniform and designers used such design to utilize the space available under the vehicle. There is no way to find out the space utilization of the reservoir by oil and validity of design except virtual simulation. Computational fluid dynamics (CFD) helps to predict the reservoir space utilization by vortex mapping, path line plots and dwell time prediction to make sure the design is valid and efficient for the vehicle. The dwell time acceptance criteria for effective reservoir design is 15 seconds. The paper will describe the hydraulic reservoir simulation which is carried out using CFD tool acuSolve using automated mesh strategy. The free surface flow and moving reference mesh is used to define the oil flow level inside the reservoir. The first baseline design is not able to meet the acceptance criteria, i.e., dwell time below 15 seconds because the oil entry and exit ports were very close. CFD is used to redefine the port locations for the reservoir so that oil dwell time increases in the reservoir. CFD also proposed baffle design the effective space utilization. The final design proposed through CFD analysis is used for physical validation on the machine.

Keywords: reservoir, turbulence model, transient model, level set, free-surface flow, moving frame of reference

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Authors: Ran Etgar, Yuval Cohen, Erel Avineri

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One of the major challenges of transportation in medium sized inner-cities (such as Tel-Aviv) is the last-mile solution. Personal rapid transit (PRT) seems like an applicable candidate for this, as it combines the benefits of personal (car) travel with the operational benefits of transit. However, the investment required for large area PRT grid is significant and there is a need to economically justify such investment by correctly evaluating the grid capacity. PRT main elements are small automated vehicles (sometimes referred to as podcars) operating on a network of specially built guideways. The research is looking at a specific concept of elevated PRT system. Literature review has revealed the drawbacks PRT modelling and simulation approaches, mainly due to the lack of consideration of technical and operational features of the system (such as headways, acceleration, safety issues); the detailed design of infrastructure (guideways, stations, and docks); the stochastic and sessional characteristics of demand; and safety regulations – all of them have a strong effect on the system performance. A highly detailed model of the system, developed in this research, is applying a discrete event simulation combined with an agent-based approach, to represent the system elements and the podecars movement logic. Applying a case study approach, the simulation model is used to study the capacity of the system, the expected throughput of the system, the utilization, and the level of service (journey time, waiting time, etc.).

Keywords: capacity, productivity measurement, PRT, simulation, transportation

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Authors: Aravind G., Arshinder Kaur, Pushpavanam S.

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There is a strong emphasis on shifting to electric vehicles (EVs) throughout the globe for reducing the impact on global warming following the Paris climate accord. Lithium-ion batteries (LIBs) are predominantly used in EVs, and these can be a significant threat to the environment if not disposed of safely. Lithium is also a valuable resource not widely available. There are several research groups working on developing an efficient recycling process for LIBs. Two routes - pyrometallurgical and hydrometallurgical processes have been proposed for recycling LIBs. In this paper, we focus on life cycle assessment (LCA) as a tool to quantify the environmental impact of these recycling processes. We have defined the boundary of the LCA to include only the recycling phase of the end-of-life (EoL) of the battery life cycle. The analysis is done assuming ideal conditions for the hydrometallurgical and a combined hydrometallurgical and pyrometallurgical process in the inventory analysis. CML-IA method is used for quantifying the impact assessment across eleven indicators. Our results show that cathode, anode, and foil contribute significantly to the impact. The environmental impacts of both hydrometallurgical and combined recycling processes are similar across all the indicators. Further, the results of LCA are used in developing a multi-objective optimization model for the design of lithium-ion battery recycling network. Greenhouse gas emissions and cost are the two parameters minimized for the optimization study.

Keywords: life cycle assessment, lithium-ion battery recycling, multi-objective optimization, network design, reverse supply chain

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Authors: Abdullahi Musa, Yakubu Kukure Enebe Ibrahim, Adeshina Gujumbola

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The emergence of multidrug resistance in clinical Escherichia coli has been associated with plasmid-mediated genes. DNA transfer among bacteria is critical to the dissemination of resistance. Plasmids have proved to be the ideal vehicles for dissemination of resistance genes. Plasmids coding for antibiotic resistance were long being recognized by many researchers globally. The study aimed at determining the antibiotic susceptibility pattern of ESBL E. coli isolates claimed to be multidrug resistance using disc diffusion method. Antibacterial activity of the test isolates was carried out using disk diffusion methods. The results showed that, majority of the multidrug resistance among clinical isolates of ESBL E. coli was as a result of acquisition of plasmid carrying antibiotic-resistance genes. Production of these ESBL enzymes by these organisms which are normally carried by plasmid and transfer from one bacterium to another has greatly contributed to the rapid spread of antibiotic resistance amongst E. coli isolates, which lead to high economic burden, increase morbidity and mortality rate, complication in therapy and limit treatment options. To curtail these problems, it is of significance to checkmate the rate at which over the counter drugs are sold and antibiotic misused in animal feeds. This will play a very important role in minimizing the spread of resistance bacterial strains in our environment.

Keywords: Escherichia coli, plasmid, multidrug resistance, ESBL, pan drug resistance

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Authors: Vatasta Koul, Vaibhav Sharma, Ayush Gupta, Rajesh Yadav

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Exploratory missions to Mars and Titan have increased recently with various endeavors to find an alternate home to humankind. The use of surface rovers has its limitations due to rugged and uneven surfaces of these planetary bodies. The use of aerial robots requires the complete aerodynamic characterization of these vehicles in the atmospheric conditions of these planetary bodies. The dynamic stall phenomenon is extremely important for rotary wings performance under low Reynolds number that can be encountered in Martian and Titan’s atmosphere. The current research focuses on the aerodynamic characterization and exploration of the dynamic stall phenomenon of two different airfoils viz. E387 and Selig-Donovan7003 in Martian and Titan’s atmosphere at low Reynolds numbers of 10000 and 50000. The two-dimensional numerical simulations are conducted using commercially available finite volume solver with multi-species non-reacting mixture of gases as the working fluid. The k-epsilon (k-ε) turbulence model is used to capture the unsteady flow separation and the effect of turbulence. The dynamic characteristics are studied at a fixed different constant rotational extreme of angles of attack. This study of airfoils at different low Reynolds number and atmospheric conditions on Mars and Titan will be resulting in defining the aerodynamic characteristics of these airfoils for unmanned aerial missions for outer space exploration.

Keywords: aerodynamics, dynamic stall, E387, SD7003

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Authors: E. K. Hardwick, L. B. Siwela, J. G. Falconer, M. E. Mathibela, W. Rolfe

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Lithium-ion battery (LiB) demand has increased with the advancement in technologies. The applications include electric vehicles, cell phones, laptops, and many more devices. Typical components of the cathodes include lithium, cobalt, nickel, and manganese. Recycling the spent LiBs is necessary to reduce the ecological footprint of their production and use and to have a secondary source of valuable metals. A hydrometallurgical method was investigated for the recovery of cobalt and nickel from LiB cathodes. The cathodes were leached using a chloride solution. Ion exchange was then used to recover the chloro-complexes of the metals. The aim of the research was to determine the efficiency of a chloride leach, as well as ion exchange operating capacities that can be achieved for LiB recycling, and to establish the optimal operating conditions (ideal pH, temperature, leachate and eluant, flowrate, and reagent concentrations) for the recovery of the cathode metals. It was found that the leaching of the cathodes could be hindered by the formation of refractory metal oxides of cathode components. A reducing agent was necessary to improve the leaching rate and efficiency. Leaching was achieved using various chloride-containing solutions. The chloro-complexes were absorbed by the ion exchange resin and eluted to produce concentrated cobalt, nickel, lithium, and manganese streams. Chromatographic separation of these elements was achieved. Further work is currently underway to determine the optimal operating conditions for the recovery by ion exchange.

Keywords: cobalt, ion exchange, leachate formation, lithium-ion batteries, manganese, nickel

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Authors: Sara Mostowfi, Hassan Sadeghinaeini, Sana Behnamasl, Leila Ensaniat, Maryam Mostafaee

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Nowadays, most of product producers, e.g. home appliance, electronic machines and vehicles focus on quality and comfort, and promise consumers ease of use and pleasurable experiences during product using. Consumers make their purchase decisions according to two needs: functional and emotional needs. Functional needs are fulfilled by product functionality, besides emotional needs are related to psychologists’ aspects of production. Emotions are distinctive elements which should be added to products and services to lead them up. In this case, the authors’ survey conducted pleasurable and hedonomic aspects in products of a home appliance company in Iran. In this regard, three samples of home appliance were selected: mixer, rice cooker, iron. Fifteen women (20-60) participated in this study. Every user evaluated each product by questionnaire based on 7 point semantic differential scale. After analyzing the results with statistical methods, results showed that 90% of users aren’t satisfied with hedonic and pleasurable criteria in interaction with these products. They notified that regarding hedonomics and pleasurable criteria’s they will have better ease of use and functionality. Our findings show a significant association between products’ features and user satisfaction. It seems that industrial design has a significant impression on the company’s products and with regard the pleasurable criteria the company sales will be more successful.

Keywords: home appliance, interaction, pleasure, hedonomy, ergonomy

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Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

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Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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Authors: Jean-Paul Kapuya Bulaba Nyembwe, John Omomoluwa Ogundiran, Manuel Carlos Gameiro da Silva

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Indoor environmental quality (IEQ) remains a global concern because it impacts people's comfort, health, performance, and general well-being. People spend a significant amount of time in buildings or while commuting, hence ensuring the minimal risk in indoor spaces by ensuring suitable IEQ. IEQ studies are limited regarding developing sub-Saharan countries, whereas there is also a huge risk and concern for the current population and geometric growth as many cities in the region will become mega-cities by 2040 (World Bank report). The absence of suitable IEQ regulations and energy poverty are reasons to assess the IEQ gaps for increased awareness of sustainable interventions to minimize the associated risk. This study evaluates the gaps and potential hazards that exist in the IEQ of sub-Saharan countries using empirical studies of hospital occupants and BRT bus passengers and drivers. The Surveys were conducted in 3 cities of the Democratic Republic of Congo and Lagos metropolis of Nigeria. The results suggest that gaps exist in IEQ for these regions. The gaps indicate existential risk to people’s health, comfort, and well-being. The inferential conclusions are that there is a need for further scientific studies, improvement in IEQ conditions, and ensuring suitable regulations for developing sub-Saharan countries.

Keywords: health hazards, hospitals indoor environmental quality, indoor spaces, occupants, sub-Saharan countries, vehicles

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Authors: Vijaykumar Patel, P. Bahadur

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Microstructural evolution of a cationic gemini surfactant 12-4-12 micelles in the presence of bile salts has been investigated using different techniques. A negative value of interaction parameter evaluated from surface tension measurements is a signature of strong synergistic interaction between oppositely charged surfactants. Both the bile salts compete with each other in inducing the micellar transition of 12-4-12 micelles depending on their hydrophobicity. Viscosity measurements disclose that loading of bile salts induces morphological changes in 12-4-12 micelles; sodium deoxycholate is more efficient in altering the aggregation behaviour of 12-4-12 micelles compared to sodium cholate and presents pronounced increase in viscosity and micellar growth which is suppressed at elevated temperatures. A remarkable growth of 12-4-12 micelles in the presence of sodium deoxycholate at low pH has been ascribed to the solubilization of bile acids formed in acidic medium. Small angle neutron scattering experiments provided size and shape of 12-4-12/bile salt mixed micelles are explicated on the basis of hydrophobicity of bile salts. The location of bile salts in micelle was determined from nuclear overhauser effect spectroscopy. The present study characterizes 12-4-12 gemini-bile salt mixed systems which significantly enriches our knowledge, and such a structural transition provides an opportunity to use these bioamphiphiles as delivery vehicles and in some pharmaceutical formulations.

Keywords: gemini surfactants, bile salts, SANS (small angle neutron scattering), NOESY (nuclear overhauser effect spectroscopy)

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Authors: Dario Basile, Manuela De Maddis, Raffaella Sesana, Pasquale Russo Spena, Roberto Maiorano

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Nowadays, the reduction of CO₂ emissions and the decrease in energy consumption are the main aims of several industries, especially in the automotive sector. To comply with the increasingly restrictive regulations, the automotive industry is constantly looking for innovative techniques to produce lighter, more efficient, and less polluting vehicles. One of the latest technologies, and still developing, is based on the fabrication of the body-in-white and car parts through the stamping of Aluminum Tailor Welded Blanks. Tailor Welded Blanks (TWBs) are generally the combination of two/three metal sheets with different thicknesses and/or mechanical strengths, which are commonly butt-welded together by laser sources. The use of aluminum TWBs has several advantages such as low density and corrosion resistance adequate. However, their use is still limited by the lower formability with respect to the parent materials and the more intrinsic difficulty of laser welding of aluminum sheets (i.e., internal porosity) that, although its use in automated industries is constantly growing, remains a process to be further developed and improved. This study has investigated the effect of the main laser welding process parameters (laser power, welding speed, and focal distance) on the mechanical properties of aluminum TWBs made of 6xxx series. The research results show that a narrow weldability window can be found to ensure welded joints with high strength and limited or no porosity.

Keywords: aluminum sheets, automotive industry, laser welding, mechanical properties, tailor welded blanks

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Authors: Aadiv Shah, Hari Nair, Vedant Mittal, Alice Cheeran

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Present-day agricultural practices such as blanket spraying not only lead to excessive usage of pesticides but also harm the overall crop yield. This paper introduces an algorithm to optimize the traversal of an unmanned aerial vehicle (UAV) in constrained environments. The proposed system focuses on the agricultural application of targeted spraying for locust elimination. Given a satellite image of a farm, target zones that are prone to locust swarm formation are detected through the calculation of the normalized difference vegetation index (NDVI). This is followed by determining the optimal path for traversal of a UAV through these target zones using the proposed algorithm in order to perform pesticide spraying in the most efficient manner possible. Unlike the classic travelling salesman problem involving point-to-point optimization, the proposed algorithm determines an optimal path for multiple regions, independent of its geometry. Finally, the paper explores the idea of implementing reinforcement learning to model complex environmental behaviour and make the path planning mechanism for UAVs agnostic to external environment changes. This system not only presents a solution to the enormous losses incurred due to locust attacks but also an efficient way to automate agricultural practices across the globe in order to improve farmer ergonomics.

Keywords: locust, NDVI, optimization, path planning, reinforcement learning, UAV

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Authors: Allen Yushark Fosu, Ndue Kanari, James Vaughan, Alexandre Changes

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Spodumene is a lithium-bearing mineral of great interest due to increasing demand of lithium in emerging electric and hybrid vehicles. The conventional method of processing the mineral for the metal requires inevitable thermal transformation of α-phase to the β-phase followed by roasting with suitable reagents to produce lithium salts for downstream processes. The selection of appropriate reagent for roasting is key for the success of the process and overall lithium recovery. Several researches have been conducted to identify good reagents for the process efficiency, leading to sulfation, alkaline, chlorination, fluorination, and carbonizing as the methods of lithium recovery from the mineral.HSC Chemistry is a thermochemical software that can be used to model metallurgical process feasibility and predict possible reaction products prior to experimental investigation. The software was employed to investigate and explain the various reagent characteristics as employed in literature during spodumene roasting up to 1200°C. The simulation indicated that all used reagents for sulfation and alkaline were feasible in the direction of lithium salt production. Chlorination was only feasible when Cl2 and CaCl2 were used as chlorination agents but not NaCl nor KCl. Depending on the kind of lithium salt formed during carbonizing and fluorination, the process was either spontaneous or nonspontaneous throughout the temperature range investigated. The HSC software was further used to simulate and predict some promising reagents which may be equally good for roasting the mineral for efficient lithium extraction but have not yet been considered by researchers.

Keywords: thermochemical modelling, HSC chemistry software, lithium, spodumene, roasting

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Robert S. Giachetti, Emanuele Grossi

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Loosening of bolted joints in rotating machines can adversely affect their performance, cause mechanical damage, and lead to injuries. In this paper, two potential loosening phenomena in rotating applications are discussed. First, ‘precession,’ is governed by thread/nut contact forces, while the second is based on inertial effects of the fastened assembly. These mechanisms are reviewed within the context of historical usage of left-handed fasteners in rotating machines which appears absent in the literature and common machine design texts. Historically, to prevent loosening of wheel nuts, vehicle manufacturers have used right-handed and left-handed threads on different sides of the vehicle, but most modern vehicles have abandoned this custom and only use right-handed, tapered lug nuts on all sides of the vehicle. Other classical machines such as the bicycle continue to use different handed threads on each side while other machines such as, bench grinders, circular saws and brush cutters still use left-handed threads to fasten rotating components. Despite the continued use of left-handed fasteners, the rationale and analysis of left-handed threads to mitigate self-loosening of fasteners in rotating applications is not commonly, if at all, discussed in the literature or design textbooks. Without scientific literature to support these design selections, these implementations may be the result of experimental findings or aged institutional knowledge. Based on a review of rotating applications, historical documents and mechanical design references, a formal study of the paradoxical nature of left-handed threads in various applications is merited.

Keywords: rotating machinery, self-loosening fasteners, wheel fastening, vibration loosening

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Authors: Onur Kaya, Ilknur Tukenmez

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In this study, we consider vehicle routing problems on networks with alternative direct links between nodes, and we analyze a multi-objective problem considering the financial, environmental and social objectives in this context. In real life, there might exist several alternative direct roads between two nodes, and these roads might have differences in terms of their lengths and durations. For example, a road might be shorter than another but might require longer time due to traffic and speed limits. Similarly, some toll roads might be shorter or faster but require additional payment, leading to higher costs. We consider such alternative links in our problem and develop a mixed integer linear programming model that determines which alternative link to use between two nodes, in addition to determining the optimal routes for different vehicles, depending on the model objectives and constraints. We consider the minimum cost routing as the financial objective for the company, minimizing the CO2 emissions and gas usage as the environmental objectives, and optimizing the driver working conditions/working hours, and minimizing the risks of accidents as the social objectives. With these objective functions, we aim to determine which routes, and which alternative links should be used in addition to the speed choices on each link. We discuss the results of the developed vehicle routing models and compare their results depending on the system parameters.

Keywords: vehicle routing, alternative links between nodes, mixed integer linear programming, triple bottom line accounting

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Authors: Mukhtiar Singh, Sumeet Nagar

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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.

Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem

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Authors: Naoum Abderrahmane, Boumehed Meriem, Alshaqaqi Belal

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Background subtraction algorithm is a larger used technique for detecting moving objects in video surveillance to extract the foreground objects from a reference background image. There are many challenges to test a good background subtraction algorithm, like changes in illumination, dynamic background such as swinging leaves, rain, snow, and the changes in the background, for example, moving and stopping of vehicles. In this paper, we propose an efficient and accurate background subtraction method for moving object detection in video surveillance. The main idea is to use a developed fast-independent component analysis (ICA) algorithm to separate background, noise, and foreground masks from an image sequence in practical environments. The fast-ICA algorithm is adapted and adjusted with a matrix calculation and searching for an optimum non-quadratic function to be faster and more robust. Moreover, in order to estimate the de-mixing matrix and the denoising de-mixing matrix parameters, we propose to convert all images to YCrCb color space, where the luma component Y (brightness of the color) gives suitable results. The proposed technique has been verified on the publicly available datasets CD net 2012 and CD net 2014, and experimental results show that our algorithm can detect competently and accurately moving objects in challenging conditions compared to other methods in the literature in terms of quantitative and qualitative evaluations with real-time frame rate.

Keywords: background subtraction, moving object detection, fast-ICA, de-mixing matrix

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Saul Emilio Rivero Mejia, Estefanya Marin Tabares, Carlos Andres Rodriguez Toro, Katherine Bolano Restrepo, Sarita Santa Cortes

Abstract:

Medellin is the Colombian city with the best public transportation system in the country, which is composed of two subway lines, five metro cables, two Bus Rapid Transit lines, and a streetcar. But despite the above, the Aburra Valley, the area in which the city is located, comparatively speaking, has a lower number of urban roads per inhabitant built, compared to the national average. In addition, since there is approximately one vehicle for every three inhabitants in Medellin, the problems of congestion and environmental pollution have become more acute over the years, and it has even been necessary to implement restrictive measures to the use of private vehicles on a permanent basis. In that sense, due to the limitations of physical space, the low public investment in road infrastructure, it is necessary to opt for mobility alternatives according to the above. Within the options for the city, there is what is known as micromobility. Micromobility is understood as those small and light means of transport used to travel short distances, which use electrical energy, such as skateboards and bicycles. These transport alternatives have a high potential for use by the city's young population, but this requires an adequate infrastructure and also state regulation. Taking into account the above, this paper will analyze the current state and future of micro mobility in the city of Medellin, making a prospective analysis, supported by a PEST (political, economic, social and technological) analysis. Based on the above, it is expected to identify the growth of demand for these alternative means and its impact on the mobility of the city in the medium and short term.

Keywords: electric, micromobility, transport, sustainable

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Authors: Bhanu Pant, Sanjay H. Upadhyay

Abstract:

Frequently, the upper stage of high-performance launch vehicles utilizes cryogenic tank-submerged pressurization gas bottles with high volume-to-weight efficiency to achieve a direct gain in the satellite payload. Titanium alloys, owing to their high specific strength coupled with excellent compatibility with various fluids, are the materials of choice for these applications. Amongst the Titanium alloys, there are two alloys suitable for cryogenic applications, namely Ti6Al4V-ELI and Ti5Al2.5Sn-ELI. The two-phase alpha-beta alloy Ti6Al4V-ELI is usable up to LOX temperature of 90K, while the single-phase alpha alloy Ti5Al2.5Sn-ELI can be used down to LHe temperature of 4 K. The high-pressure gas bottles submerged in the LH2 (20K) can store more amount of gas in as compared to those submerged in LOX (90K) bottles the same volume. Thus, the use of these alpha alloy gas bottles stored at 20K gives a distinct advantage with respect to the need for a lesser number of gas bottles to store the same amount of high-pressure gas, which in turn leads to a one-to-one advantage in the payload in the satellite. The cost advantage to the tune of 15000$/ kg of weight is saved in the upper stages, and, thereby, the satellite payload gain is expected by this change. However, the processing of alpha Ti5Al2.5Sn-ELI alloy gas bottles poses challenges due to the lower forgeability of the alloy and mode of qualification for the critical severe application environment. The present paper describes the processing and challenges/ solutions during the development of these advanced gas bottles for LH2 (20K) applications.

Keywords: titanium alloys, cryogenic gas bottles, alpha titanium alloy, alpha-beta titanium alloy

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Authors: Leonardo E. Pacheco, Carlos A. Díaz

Abstract:

An alternative way of addressing the difficult to recover the useless heat is through an ejector refrigeration cycle for vehicles applications. A group of thermo-compressor supply the mechanical compressor function at conventional refrigeration compression system. The thermo-compressor group recovers the thermal energy from waste streams (exhaust gases product in internal combustion motors, gases burned in wellhead among others) to eliminate the power consumption of the mechanical compressor. These types of alternative cooling system (air-conditioners) present a kind of advantages in both the increase in energy efficiency and the improvement of the COP of the system being studied from their its mechanical simplicity (decrease of moving parts). An ejector refrigeration cycle represents a significant step forward in the optimization of the efficient use of energy in the process of air conditioning and an alternative to reduce the environmental impacts. On one side, with the energy recycling decreases the temperature of the gases thrown into the atmosphere, which contributes to the principal beneficiaries of the average temperature of the planet. In parallel, mitigating the environmental impact caused by the production and handling of conventional cooling fluids commonly available in the market, causing the destruction of the ozone layer. This work had studied the operation of the multiejector cooling system for a truck with a 420 HP engine at different rotation speed. The operation condition limits and the COP of multi-ejector cooling systems applied in a truck are analyzed for a variable rpm range from to 800–1800 rpm.

Keywords: ejector system, exhaust gas, multiejector cooling system, recovery energy

Procedia PDF Downloads 232

Authors: Maedeh Pourmajidian, Joseph R. McDermid

Abstract:

Advanced High Strength Steels are revolutionizing both the steel and automotive industries due to their high specific strength and ability to absorb energy during crash events. This allows manufacturers to design vehicles with significantly increased fuel efficiency without compromising passenger safety. To maintain the structural integrity of the fabricated parts, they must be protected from corrosion damage through continuous hot-dip galvanizing process, which is challenging due to selective oxidation of Mn and Si on the surface of this AHSSs. The effects of process atmosphere oxygen partial pressure and small additions of Sn on the selective oxidation of a medium-Mn C-6Mn-2Si advanced high strength steel was investigated. Intercritical annealing heat treatments were carried out at 690˚C in an N2-5%H2 process atmosphere under dew points ranging from –50˚C to +5˚C. Surface oxide chemistries, morphologies, and thicknesses were determined at a variety of length scales by several techniques, including SEM, TEM+EELS, and XPS. TEM observations of the sample cross-sections revealed the transition to internal oxidation at the +5˚C dew point. EELS results suggested that the internal oxides network was composed of a multi-layer oxide structure with varying chemistry from oxide core towards the outer part. The combined effect of employing a known surface active element as a function of process atmosphere on the surface structure development and the possible impact on reactive wetting of the steel substrates by the continuous galvanizing zinc bath will be discussed.

Keywords: 3G AHSS, hot-dip galvanizing, oxygen partial pressure, selective oxidation

Procedia PDF Downloads 373

Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

Abstract:

Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

Procedia PDF Downloads 348

Authors: Tomaž Tollazzi, Matjaž Šraml, Chiara Gruden, Marko Renčelj

Abstract:

Motorcycle riders are an increasing group of road users. The intrinsic characteristics of powered two-wheelers (PTW) allow them to be particularly flexible, both in urban and extra-urban environments. Nevertheless, crash statistics indicate that riders involved in road accidents are highly likely to suffer severe injuries, underlining the vulnerability of this group of road users. An element that can greatly affect the safety of PTW users is road design, as roads are usually designed for two-track vehicles (cars, buses, and lorries) and usually do not consider the needs of PTWs. Additionally, handling a motorcycle is quite different from driving a car; thus, the behavior of riders is different from that of drivers. The aim of this research was to compare how different road designs are perceived by riders and drivers and to preliminarily assess if riders’ behavior and attention allocation are related. For this research, an eye-tracking experiment was developed outdoors. Both drivers and riders travelled along a route comprising four different road designs and various road layouts, and the output was analyzed both qualitatively and quantitatively. Although it was not possible to carry out a statistical analysis due to the limited number of participants, the results demonstrate that there is a difference in the gaze behavior of drivers and riders, with the latter being far more focused on the left-hand side of the road and concentrating on defined elements of road design. Furthermore, the experiment demonstrated that a higher number of fixations is related to lower speeds. Finally, it was noted that both kinds of road users focus well on the carriageway, leading to the conclusion that the indications given through road markings may be much more effective than vertical signalization, which has rarely been observed.

Keywords: road safety, powered two-wheelers, eye-tracking, gaze behavior

Procedia PDF Downloads 58