Search results for: under vehicle inspection

Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Onur Ozveri, Korkut Karabag, Cagri Keles

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It is an important issue that the occurring of production downtime and repair costs when machines fail in the machine intensive production industries. In the case of failure of more than one machine at the same time, which machines will have the priority to repair, how to determine the optimal repair time should be allotted for this machines and how to plan the resources needed to repair are the key issues. In recent years, Business Process Management (BPM) technique, bring effective solutions to different problems in business. The main feature of this technique is that it can improve the way the job done by examining in detail the works of interest. In the industries, maintenance and repair works are operating as a process and when a breakdown occurs, it is known that the repair work is carried out in a series of process. Maintenance main-process and repair sub-process are evaluated with process management technique, so it is thought that structure could bring a solution. For this reason, in an international manufacturing company, this issue discussed and has tried to develop a proposal for a solution. The purpose of this study is the implementation of maintenance and repair works which is integrated with process management technique and at the end of implementation, analyzing the maintenance related parameters like quality, cost, time, safety and spare part. The international firm that carried out the application operates in a free region in Turkey and its core business area is producing original equipment technologies, vehicle electrical construction, electronics, safety and thermal systems for the world's leading light and heavy vehicle manufacturers. In the firm primarily, a project team has been established. The team dealt with the current maintenance process again, and it has been revised again by the process management techniques. Repair process which is sub-process of maintenance process has been discussed again. In the improved processes, the ABC equipment classification technique was used to decide which machine or machines will be given priority in case of failure. This technique is a prioritization method of malfunctioned machine based on the effect of the production, product quality, maintenance costs and job security. Improved maintenance and repair processes have been implemented in the company for three months, and the obtained data were compared with the previous year data. In conclusion, breakdown maintenance was found to occur in a shorter time, with lower cost and lower spare parts inventory.

Keywords: ABC equipment classification, business process management (BPM), maintenance, repair performance

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Authors: S. Shankar Bharathi

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Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

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Authors: Mohammad Ali Hasanzadeh, Thierry Van Elslander, Eddy Van De Voorde

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About 90 percent of world merchandise trade by volume being carried by sea. Maritime transport remains as back bone behind the international trade and globalization meanwhile all seaborne goods need using at least two ports as origin and destination. Amid seaborne traded cargos, container traffic is a prosperous market with about 16% in terms of volume. Albeit containerized cargos are less in terms of tonnage but, containers carry the highest value cargos amongst all. That is why efficient handling of containers in ports is very important. Accidents are the foremost causes that lead to port inefficiency and a surge in total transport cost. Having different port safety management systems (PSMS) in place, statistics on port accidents show that numerous accidents occur in ports. Some of them claim peoples’ life; others damage goods, vessels, port equipment and/or the environment. Several accident investigation illustrate that the most common accidents take place throughout transport operation, it sometimes accounts for 68.6% of all events, therefore providing a safer workplace depends on reducing collision risk. In order to quantify risks at the port area different variables can be used as exposure measurement. One of the main motives for defining and using exposure in studies related to infrastructure is to account for the differences in intensity of use, so as to make comparisons meaningful. In various researches related to handling containers in ports and intermodal terminals, different risk exposures and also the likelihood of each event have been selected. Vehicle collision within the port area (10-7 per kilometer of vehicle distance travelled) and dropping containers from cranes, forklift trucks, or rail mounted gantries (1 x 10-5 per lift) are some examples. According to the objective of the current research, three categories of accidents selected for collision risk assessment; fall of container during ship to shore operation, dropping container during transfer operation and collision between vehicles and objects within terminal area. Later on various consequences, exposure and probability identified for each accident. Hence, reducing collision risks profoundly rely on picking the right risk exposures and probability of selected accidents, to prevent collision accidents in container terminals and in the framework of risk calculations, such risk exposures and probabilities can be useful in assessing the effectiveness of safety programs in ports.

Keywords: container terminal, collision, seaborne trade, risk exposure, risk probability

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: Mohamed Ahmed Khali

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Numbers of deep well anode ground beds (GBs) have been retrieved due to un operated anode chains. New identical magnetite anode chains(MAC) have been installed at Raslanuf complex impressed current Cathodic protection(ICCP) system, distributed at different plants(Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB associated severely corroded wellhead casings were well maintained and/ or replaced by new fabricated and modified ones. The main cause of wellhead casings internal corrosion was discussed, and the conducted remedy action to overcome future corrosion problem is presented. All GB connected anode junction boxes (AJBs) and shunts were closely inspected, maintained, and necessary replacement/and or modification were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB associated Transformer-Rectifiers units (TRUs) were subjected to through inspection, and necessary maintenance has been performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated. An alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded, and all obtained test results are presented. DC current outputs has been adjusted, and DC current outputs of each MAC has been recorded for each GB AJB.

Keywords: magnatite anode, deep well, ground bed, cathodic protection, transformer rectifies, impreced current, junction box

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Authors: Giovanni Masala, Stefania Marica

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Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values.

Keywords: ARMA-GARCH process, electricity load, fitting tests, Fourier series, Monte Carlo simulation, non-linear regression

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Authors: S. Siddharth, Saravana Kumar

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All Metros across the world tend to have a large number of bridges and there have been concerns about the safety of these bridges. As the traffic in most cities in India is heterogeneous, Trucks and Heavy vehicles traverse on our roads on an everyday basis this will lead to structural damage on the long run. All bridges are designed with a maximum Load limit and this limit is seldom checked. We have hence come up with an idea to check the load of all the vehicles entering the bridge and block the bridge with barricades if the vehicle surpasses the maximum load , this is done to catch hold of the perpetrators. By doing this we can avoid further structural damage and also provide an effective way to enforce the law. If our solution is put in place structural damage and accidents would be reduced to a great deal and it would also make the law enforcement job easier.

Keywords: heterogeneous, structural, load, law, heavy, vehicles

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Authors: Shubha T., Latha H. K. E., Yogananth Karuppiah

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Accessing and sharing automobiles will become much simpler thanks to the wide range of automotive use cases made possible by digital keys. This study aims to provide digital keys to car owners and drivers so they can lock or unlock their automobiles and start the engine using a smartphone or other Bluetooth low energy-enabled mobile device. Private automobile owners can digitally lend their car keys to family members or friends without having to physically meet them, possibly for a certain period of time. Owners of company automobile fleets can electronically distribute car keys to staff members, possibly granting access for a given day or length of time. Customers no longer need to physically pick up car keys at a rental desk because automobile owners can digitally transfer keys with them.

Keywords: NFC, BLE, CCC, digital key, OEM

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Authors: Satya Pradhan, Venky Nanniyur

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As the software industry transitions from a license-based model to a subscription-based Software-as-a-Service (SaaS) model, many software development groups are using a hybrid development model that incorporates Agile and Waterfall methodologies in different parts of the organization. The traditional metrics used for measuring software quality in Waterfall or Agile paradigms do not apply to this new hybrid methodology. In addition, to respond to higher quality demands from customers and to gain a competitive advantage in the market, many companies are starting to prioritize quality as a strategic differentiator. As a result, quality metrics are included in the decision-making activities all the way up to the executive level, including board of director reviews. This paper presents key challenges associated with measuring software quality in organizations using the hybrid development model. We introduce a framework called Prevention-Inspection-Evaluation-Removal (PIER) to provide a comprehensive metric definition for hybrid organizations. The framework includes quality measurements, quality enforcement, and quality decision points at different organizational levels and project milestones. The metrics framework defined in this paper is being used for all Cisco systems products used in customer premises. We present several field metrics for one product portfolio (enterprise networking) to show the effectiveness of the proposed measurement system. As the results show, this metrics framework has significantly improved in-process defect management as well as field quality.

Keywords: quality management system, quality metrics framework, quality metrics, agile, waterfall, hybrid development system

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Authors: Leon C. Prieto, Simone T. A. Phipps

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There is a need to promote social entrepreneurship in order to solve some of the complex problems facing various countries in Africa (poverty, unemployment, crime, HIV, etc.). For example, one possible consequence of the HIV/AIDS crisis in Zimbabwe and elsewhere is a deterioration in the educational opportunities for orphans and other vulnerable children. Given that high returns are associated with education, the loss of education for a large segment of the population would likely worsen the already dire economic consequences of the HIV/AIDS crisis. Using a systems approach, this paper argues that social entrepreneurship can be used as a vehicle to promote national human resource development, which will assist in the alleviation of societal ills on the national level as well as throughout Africa.

Keywords: human resource development, pan-african, social entrepreneurship, social enterprise

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Authors: Sekkak Abdelmalek

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The aim of this paper is to establish an energy balance of the drivetrain of a low power electric vehicle (around ten kilowatts). The study is based on two topologies of power electronics converter, the voltage source inverter and cascaded H-Bridge inverter. For each of these solutions, two voltage levels are studied for the drivetrain. At first a discussion of cascaded H-Bridge inverters will be performed on the potential benefits of this structure for its use to other functions such as macroscopic batteries management system. In a second step, the performances of the traction chain are compared according to the structure of the power converter and the voltage level of the traction chain.

Keywords: power electronics, static converters, cascaded H-Bridge, traction chain, efficiency, losses, batteries balancing

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

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Authors: Zongyan Li, Matt Best

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This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.

Keywords: correlation analysis, F-ratio, levenberg-marquardt, MSE, NARX, neural network, optimisation

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Authors: Keyvan Kashkouli Nejad, Motoaki Sugiura, Atsushi Sato, Takayuki Nozawa, Hyeonjeong Jeong, Sugiko Hanawa , Yuka Kotozaki, Ryuta Kawashima

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The perception of agency/control is altered with presence of discrepancies in the environment or mismatch of predictions (of possible results) and actual results the sense of agency might become altered. Synofzik et al. proposed a two layer model of agency: In the first layer, the Feeling of Agency (FoA) is not directly available to awareness; a slight mismatch in the environment/outcome might cause alterations in FoA, while the agent still feels in control. If the discrepancy passes a threshold, it becomes available to consciousness and alters Judgment of Agency (JoA), which is directly available in the person’s awareness. Most experiments so far only investigate subjects rather conscious JoA, while FoA has been neglected. In this experiment we target FoA by using subliminal discrepancies that can not be consciously detectable by the subjects. Here, we explore whether we can detect this two level model in the subjects behavior and then try to map this in their brain activity. To do this, in a fMRI study, we incorporated both consciously detectable mismatching between action and result and also subliminal discrepancies in the environment. Also, unlike previous experiments where subjective questions from the participants mainly trigger the rather conscious JoA, we also tried to measure the rather implicit FoA by asking participants to rate their performance. We compared behavioral results and also brain activation when there were conscious discrepancies and when there were subliminal discrepancies against trials with no discrepancies and against each other. In line with our expectations, conditions with consciously detectable incongruencies triggered lower JoA ratings than conditions without. Also, conditions with any type of discrepancies had lower FoA ratings compared to conditions without. Additionally, we found out that TPJ and angular gyrus in particular to have a role in coding of JoA and also FoA.

Keywords: agency, fMRI, TPJ, two layer model

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Mikołaj Szyca

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Friction elements of rail vehicle brakes are more and more often made of composite materials that displace cast iron. Materials are tested primarily in terms of their dynamic abilities, but the material structure of brake pads and linings changes during operation. In connection with the above, the changes taking place in the tested rubbing materials were analyzed using X-ray computed tomography in order to obtain data on changes in the structure of the material immediately after production and after a certain number of operating cycles. The implementation of microtomography research for experimental work on new friction materials may result in increasing the potential for the production of new composites by eliminating unfavorable material factors and, consequently, improving the dynamic parameters.

Keywords: composite materials, friction pair, X-ray computed microtomography, railway

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Authors: Timothy E. Frank, Josh R. Aldred, Sophie B. Boulware, Michelle K. Cabonce, Justin H. White

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Materials degrade at different rates in different environments depending on factors such as temperature, aridity, salinity, and solar radiation. Therefore, predicting asset longevity depends, in part, on the environmental conditions to which the asset is exposed. Heating, ventilation, and air conditioning (HVAC) systems are critical to building operations yet are responsible for a significant proportion of their energy consumption. HVAC energy use increases substantially with slight operational inefficiencies. Understanding the environmental influences on HVAC degradation in detail will inform maintenance schedules and capital investment, reduce energy use, and increase lifecycle management efficiency. HVAC inspection records spanning 14 years from 21 locations across the United States were compiled and associated with the climate conditions to which they were exposed. Three environmental features were explored in this study: average high temperature, average low temperature, and annual precipitation, as well as four non-environmental features. Initial insights showed no correlations between individual features and the rate of HVAC component degradation. Using neighborhood component analysis, however, the most critical features related to degradation were identified. Two models were considered, and results varied between them. However, longitude and latitude emerged as potentially the best predictors of average HVAC component degradation. Further research is needed to evaluate additional environmental features, increase the resolution of the environmental data, and develop more robust models to achieve more conclusive results.

Keywords: climate, degradation, HVAC, neighborhood component analysis

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Hananto Prakoso, Jean-Pierre Orfeuil

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The relationship between city size, urban transport efficiency (speed), employment proximity (distance) and accessibility of labour market is rarely examined especially in developing countries. This paper reveals the relationship using 2 points of views (active population and company). Then the analysis is divided according to 3 transport modes (car, public transport and motorcycle) and takes into account the vehicle ownership rate. We employ data across 111 districts in 4 big cities of Indonesia. In our result, speed indicator contributed positively to accessibility of labour market while distance elasticity is negative. In absolute value, elasticity of speed indicator is higher than that of distance.

Keywords: labour market, travel time, travel cost threshold, transportation

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Authors: Riccardo Loggia, Francesca Pizzimenti, Francesco Lelli, Luigi Martirano

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Recent air emission regulations point toward the complete electrification of road vehicles. An increasing number of users are beginning to prefer full electric or hybrid, plug-in vehicle solutions, incentivized by government subsidies and the lower cost of electricity compared to gasoline or diesel. However, it is necessary to optimize charging stations so that they can simultaneously satisfy as many users as possible. The purpose of this paper is to present optimization algorithms that enable simultaneous charging of multiple electric vehicles while ensuring maximum performance in relation to the type of charging station.

Keywords: electric vehicles, charging stations, sharing model, fast charging, car park, power profiles

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Authors: S. M. Yasir Arafat

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Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day.

Keywords: automobile, obstacle, safety, sensing

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

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Authors: C. Paglia, C. Mosca

Abstract:

Synthetic resin floorsare often used in sport infrastructure. These organic materials are often in contact with a bituminous substrate, which in turn is placed on the ground. In this work, the damage of a basket resin field surface was characterized by means of visual inspection, optical microscopy, resin thickness measurements, adhesion strength, water vapor transmission capacity, capillary water adsorption, granulometry of the bituminous conglomerate, the surface properties, and the water ground infiltration speed. The infiltration speed indicates water pemeability. This was due to its composition: clean sand mixed with gravel. Relatively good adhesion was present between the synthetic resin and the bituminous layer. The adhesion resistance of the bituminous layer was relatively low. According to the required bitumoniousasphalt-concrete mixes AC 11 S, the placed material was more porous. Insufficient constipation was present. The spaces values were above the standard limits, while the apparent densities were lower compared to the conventional AC 11 mixtures. The microstructure outlines the high permeability and porosity of the bituminous layer. The synthetic resin wasvapourproof and did not exhibit capillary adsorption. It exhibited a lower thickness as required, and no multiple placing steps were observed. Multiple cavities were detected along with the interface between the bituminous layer and the resin coating with no intermediate layers. The layer for the pore filling in the bituminous surface was not properly applied. The swelling bubbles on the synthetic pavement were caused by the humidity in the bituminous layer. Water or humidity were present prior to the application of the resin, and the effect was worsened by the upward movement of the water from the ground.

Keywords: resin, floor, damage, durability

Procedia PDF Downloads 162

Authors: Mohamed Ahmed Khalil

Abstract:

The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

Procedia PDF Downloads 121

Authors: Man Young Kim

Abstract:

To reduce the NOx emission in a Diesel vehicle, such various after treatment systems as SCR, LNC, and LNT are frequently visited as promising systems. Among others, urea-based SCR systems are known to be stable, effective technologies that can reduce NOx emissions most efficiently from diesel exhaust systems. In this study, therefore, effect of urea injector installation angle on the evaporation and mixing characteristics is investigated to find optimum operation conditions. It can be found that the injection angle significantly affects the thermal behavior of the urea-water solution in the diesel exhaust gases.

Keywords: selective catalytic reduction (SCR), evaporation, thermolysis, urea-water solution (UWS), injector installation angle

Procedia PDF Downloads 364

Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

Abstract:

Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

Procedia PDF Downloads 79

Authors: Konstantinos Sotiriadis, Michael Tupý, Nikol Žižková, Vít Petránek

Abstract:

The acid attack on cement mortars modified with rubber aggregates and EVA polymer binder was studied. Mortar specimens were prepared using a type CEM I 42.5 Portland cement and siliceous sand, as well as by substituting 25% of sand with shredded used automobile tires, and by adding EVA polymer in two percentages (5% and 10% of cement mass). Some specimens were only air cured, at laboratory conditions, and their compressive strength and water absorption were determined. The rest specimens were stored in acid solutions (HCl, H2SO4, HNO3) after 28 days of initial curing, and stored at laboratory temperature. Compressive strength tests, mass measurements and visual inspection took place for 28 days. Compressive strength and water absorption of the air-cured specimens were significantly decreased when rubber aggregates are used. The addition of EVA polymer further reduced water absorption, while had no important impact on strength. Compressive strength values were affected in a greater extent by hydrochloric acid solution, followed by sulfate and nitric acid solutions. The addition of EVA polymer decreased compressive strength loss for the specimens with rubber aggregates stored in hydrochloric and nitric acid solutions. The specimens without polymer binder showed similar mass loss, which was higher in sulfate acid solution followed by hydrochloric and nitric acid solutions. The use of EVA polymer delayed mass loss, while its content did not affect it significantly.

Keywords: acid attack, mortar, EVA polymer, rubber aggregates

Procedia PDF Downloads 288

Authors: Yendo Hu, Xu-Yu Wu, Dylan Oh

Abstract:

GPS-Denied drones open the possibility of indoor applications, including dynamic arial surveillance, inspection, safety enforcement, and discovery. Indoor swarming further enhances these applications in accuracy, robustness, operational time, and coverage. For micro-drones, power management becomes a critical issue, given the battery payload restriction. This paper proposes an application enabling battery replacement solution that extends the micro-drone active phase without human intervention. First, a framework to quantify the effectiveness of a power management solution for a drone fleet is proposed. The operation-to-non-operation ratio, ONR, gives one a quantitative benchmark to measure the effectiveness of a power management solution. Second, a survey was carried out to evaluate the ONR performance for the various solutions. Third, through analysis, this paper proposes a solution tailored to the indoor micro-drone, suitable for swarming applications. The proposed automated battery replacement solution, along with a modified micro-drone architecture, was implemented along with the associated micro-drone. Fourth, the system was tested and compared with the various solutions within the industry. Results show that the proposed solution achieves an ONR value of 31, which is a 1-fold improvement of the best alternative option. The cost analysis shows a manufacturing cost of $25, which makes this approach viable for cost-sensitive markets (e.g., consumer). Further challenges remain in the area of drone design for automated battery replacement, landing pad/drone production, high-precision landing control, and ONR improvements.

Keywords: micro-drone, battery swap, battery replacement, battery recharge, landing pad, power management

Procedia PDF Downloads 122