Search results for: Tracked Vehicles

Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: willingness to pay, contingent valuation, time value, city toll

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Authors: Rishabh Pandey, Umang Kumar Yadav

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In today’s era of technological advancement, we come across incalculable innovations, almost every day. No doubt that the society has developed a lot in learning and technology, but we should also take into account the problems and inflictions that are occurring. Focusing on the petroleum sector a trending global concern is toward lowering fuel consumption and emissions. It is well known that gasoline is non-renewable source of energy and its burning produces harmful emissions which are adversely affecting the environment, such issues are motivating us to seek alternative solutions that would not require much modification in engine design and help us come out with an outcome. Keeping in mind the importance of environment and human race, we present a factious idea of use of oxyhydrogen gas or HHO gas in place of gasoline in the vehicles and petroleum industry. This technology is prospering, highly efficient, could be used economically and safe, and it will be responsible for changing the future of oil and gas sector in accordance with protection to the environment. In the coming future, we will check the compatibility of HHO generator with fuel engine for production of oxyhydrogen gas with use of water and effect of introducing HHO gas to the combustion on both thermal efficiency and specific fuel consumption. We will also work on the comparison of HHO gas and commercially available gasoline fuel in support of their chemical structures; ignition rate; octane rating; knocking properties; storage; transportation and cost effectiveness and it is trusted that use of HHO gas will be ecofriendly as no harmful emissions are produced, rather the only emission is water. Additionally, this paper will include the use of HHO cell in fuel engines and challenges faced in installing it in the current period and provide effective solutions for the same.

Keywords: fuel, gas, generator, water

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Imran Ullah Khana, Mohd Hafiz Dzarfan Othmanb, Haslenda Hashima, Takeshi Matsuurad, A.F. Ismailb, M. Rezaei-DashtArzhandib, I. Wan Azelee

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Biogas upgrading is a widely studied and discussed topic, and its utilization as a natural gas substitute has gained significant attention in recent years. The production of biomethane provides a versatile application in both heat and power generation and as a vehicular fuel. This paper systematically reviews the state of the art of biogas upgrading technologies with upgrading efficiency, methane (CH4) loss, environmental effect, development and commercialization, and challenges in terms of energy consumption and economic assessment. The market situation for biogas upgrading has changed rapidly in recent years, giving membrane separation a significant market share with traditional biogas upgrading technologies. In addition, the potential utilization of biogas, efficient conversion into bio-compressed natural gas (bio-CNG), and storage systems are investigated in depth. Two storing systems for bio-CNG at filling stations, namely buffer and cascade storage systems are used. The best storage system should be selected on the basis of the advantages of both systems. Also, the fuel economy and mass emissions for bio-CNG and CNG-filled vehicles are studied. There is the same fuel economy and less carbon dioxide (CO2) emission for bio-CNG. Based on the results of comparisons between the technical features of upgrading technologies, various specific requirements for biogas utilization and the relevant investment, and operating and maintenance costs, future recommendations are made for biogas upgrading.

Keywords: biogas upgrading, cost, utilization, bio-CNG, storage, energy

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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: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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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: Biao Hu, Mark E. J. Cutler, Alexandra C. Morel

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Global climate change introduces both opportunities and challenges for crop productivity, with differences in temperature stress across latitudes and crop types, one of the most important meteorological factors impacting crop productivity. The development and productivity of crops are particularly impacted when temperatures occur outwith their preferred ranges, which has implications for global agri-food sector. This study investigated the spatiotemporal dynamics of heat stress and cold stress on UK arable lands for rapeseed cropping between 1961 and 2020, using a 1 km spatial resolution temperature dataset. Stress indices, including heat stress index (fHS) defined as the ratio of “Tmax - Tcrit_h” to “Tlimit_h - Tcrit_h” where Tmax, Tcrit_h and Tlimit_h represent the daily maximum temperature (°C), critical high temperature threshold (°C) and limiting high temperature threshold (°C) of rapeseed crop respectively; cold degree days (CDD) as the difference between daily Tmin (minimum temperature) and Tcrit_l (critical low temperature threshold); and a normalized rapeseed production loss index (fRPL) as the product of fHS and attainable rapeseed yield in the same land pixel were established. The values of fHS and CDD, percentages of days experiencing each stress and fRPL were investigated. Results found increasing fHS and the areas impacted by heat stress during flowering (from April to May) and reproductive (from April to July) stages over time, with the mean fHS being negatively correlated with latitude. This pattern of increased heat stress agrees with previous research on rapeseed cropping, which have been noted at global scale in response to changes in climate. The decreasing number of CDD and frequency of cold stress suggest cold stress decreased during flowering, vegetative (from September to March next year) and reproductive stages, and the magnitude of cold stress in the south of the UK was smaller to that compared to northern regions over the studied periods. The decreasing CDD matches observed declining cold stress of global rapeseed and of other crops such as rice in the northern hemisphere. Notably, compared with previous studies which mainly tracked the trends of heat stress and cold stress individually, this study conducted a comparative analysis of the rate of their changes and found heat stress of rapeseed crops in the UK was increasing at a faster rate than cold stress, which was seen to decrease during flowering. The increasing values of fRPL, with statistically significant differences (p < 0.05) between regions of the UK, suggested an increasing loss in rapeseed due to heat stress in the studied period. The largest increasing trend in heat stress was observed in South-eastern England, where a decreasing cold stress was taking place. While the present study observed a relatively slowly increasing heat stress, there is a worrying trend of increasing heat stress for rapeseed cropping into the future, as the cases of other main rapeseed cropping systems in the northern hemisphere including China, European counties, the US, and Canada. This study demonstrates the negative impact of global warming on rapeseed cropping, highlighting the adaptation and mitigations strategies for sustainable rapeseed cultivation across the globe.

Keywords: rapeseed, UK, heat stress, cold stress, global climate change, spatiotemporal analysis, production loss index

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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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 80