Search results for: information fusion and sensors

Authors: Yasser R. Shaban

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A practical multipurpose device for medical isotopes production is most wanted for clinical centers and researches. Unfortunately, the major supply of these radioisotopes currently comes from aging sources, and there is a great deal of uneasiness in the domestic market. There are also many cases where the cost of certain radioisotopes is too high for their introduction on a commercial scale even though the isotopes might have great benefits for society. The medical isotopes such as radiotracers PET (Positron Emission Tomography), Technetium-99 m, and Iodine-131, Lutetium-177 by is feasible to be generated by a single unit named IEMC (Inertial Electrostatic Magnetic Confinement). The IEMC fusion vessel is the upgrading unit of the Inertial Electrostatic Confinement IEC fusion vessel. Comprehensive experimental works on IEC were carried earlier with promising results. The principle of inertial electrostatic magnetic confinement IEMC fusion is based on forcing the binary fuel ions to interact in the opposite directions in ions cyclotrons orbits with different kinetic energies in order to have equal compression (forces) and with different ion cyclotron frequency ω in order to increase the rate of intersection. The IEMC features greater fusion volume than IEC by several orders of magnitude. The particles rate from the IEMC approach are projected to be 8.5 x 10¹¹ (p/s), ~ 0.2 microampere proton, for D/He-3 fusion reaction and 4.2 x 10¹² (n/s) for D/T fusion reaction. The projected values of particles yield (neutrons and protons) are suitable for medical isotope productions on-site by a single unit without any change in the fusion vessel but only the fuel gas. The PET radiotracers are usually produced on-site by medical ion accelerator whereas Technetium-99m (Tc-99m) is usually produced off-site from the irradiation facilities of nuclear power plants. Typically, hospitals receive molybdenum-99 isotope container; the isotope decays to Tc-99mwith half-life time 2.75 days. Even though the projected current from IEMC is lesser than the proton current from the medical ion accelerator but still the IEMC vessel is simpler, and reduced in components and power consumption which add a new value of populating the PET radiotracers in most clinical centers. On the other hand, the projected neutrons flux from the IEMC is lesser than the thermal neutron flux at the irradiation facilities of nuclear power plants, but in the IEMC case the productions of Technetium-99m is suggested to be at the resonance region of which the resonance integral cross section is two orders of magnitude higher than the thermal flux. Thus it can be said the net activity from both is evened. Besides, the particle accelerator cannot be considered a multipurpose particles production unless a significant change is made to the accelerator to change from neutrons mode to protons mode or vice versa. In conclusion, the projected fusion yield from IEMC is a straightforward since slightly change in the primer IEC and ion source is required.

Keywords: electrostatic versus magnetic confinement fusion vessel, ion source, medical isotopes productions, neutron activation

Procedia PDF Downloads 323

Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. Unmanned Aerial Vehicle (UAV) techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. A methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of visible Red-Blue-Green (RGB) and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: aerial thermography, data processing, drone, low-cost, point cloud

Procedia PDF Downloads 110

Authors: Martin Doran, Roy Sterritt, George Wilkie

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NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: autonomic, self-adaption, self-healing, self-optimization

Procedia PDF Downloads 322

Authors: M. Naresh, Pratik Chaturvedi, Srishti Yadav, Varun Dutt, K. V. Uday

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Changes in the Earth’s climate are likely to increase natural hazards such as drought, floods, earthquakes, landslides, etc. The present study focusing on to early warning systems (EWS) of landslides, major issues in Himalayan region without prominence to deforestation, encroachments and un-engineered cutting of slopes and reforming for infrastructural purposes. EWS can be depicted by conducting a series of flume tests using micro-electro mechanical systems sensors data after reaching threshold values under controlled laboratory conditions. Based on the threshold value database, an alert will be sent via SMS.

Keywords: slope-instability, flume test, sensors, early warning system

Procedia PDF Downloads 235

Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Kirubasankar, Sanjeevkumar, Aravindh Nagappan

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This paper addresses a system for monitoring patients using biomedical sensors and displaying it in a remote place. The main challenges in present health monitoring devices are lack of remote monitoring and logging for future evaluation. Typical instruments used for health parameter measurement provide basic information regarding health status. This paper identifies a set of design principles to address these challenges. This system includes continuous measurement of health parameters such as Heart rate, electrocardiogram, SpO2 level and Body temperature. The accumulated sensor data is relayed to a processing device using a transceiver and viewed by the implementation of cloud services.

Keywords: bio-medical sensors, monitoring, logging, cloud service

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Authors: Niyti, Aman Deep, Rajesh Kharab, Sahila Chopra, Raj. K. Gupta

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Relatively long-lived transactinide elements (i.e., elements with atomic number Z≥104) up to Z = 108 have been produced in nuclear reactions between low Z projectiles (C to Al) and actinide targets. Cross sections have been observed to decrease steeply with increasing Z. Recently, production cross sections of several picobarns have been reported for comparatively neutron-rich nuclides of 112 through 118 produced via hot fusion reactions with 48Ca and actinide targets. Some of those heavy nuclides are reported to have lifetimes on the order of seconds or longer. The relatively high cross sections in these hot fusion reactions are not fully understood and this has renewed interest in systematic studies of heavy-ion reactions with actinide targets. The main aim of this work is to understand the dynamics hot fusion reactions 18O+ 248Cm and 22Ne+244Pu (carried out at RIKEN and TASCA respectively) using the collective clusterization technique, carried out by undertaking the decay of the compound nucleus 266Rf∗ into 4n, 5n and 6n neutron evaporation channels. Here we extend our earlier study of the excitation functions (EFs) of 266Rf∗, formed in fusion reaction 18O+248Cm, based on Dynamical Cluster-decay Model (DCM) using the pocket formula for nuclear proximity potential, to the use of other nuclear interaction potentials derived from Skyrme energy density formalism (SEDF) based on semiclassical extended Thomas Fermi (ETF) approach and also study entrance channel effects by considering the synthesis of 266Rf* in 22Ne+244Pu reaction. The Skyrme forces used are the old force SIII, and new forces GSkI and KDE0(v1). Here, the EFs for the production of 260Rf, 261Rf and 262Rf isotope via 6n, 5n and 4n decay channel from the 266Rf∗ compound nucleus are studied at Elab = 88.2 to 125 MeV, including quadrupole deformations β2i and ‘hot-optimum’ orientations θi. The calculations are made within the DCM where the neck-length ∆R is the only parameter representing the relative separation distance between two fragments and/or clusters Ai which assimilates the neck formation effects.

Keywords: entrance channel effects, fusion reactions, skyrme force, superheavy nucleus

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Authors: Ali Alhajeri, Tarig Makki, Mosa Almutahhar, Mohammed Ahmed, Usman Ali

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Metal powder is the raw material used for laser powder-bed fusion (LPBF) additive manufacturing (AM). There are many metal materials that can be used in LPBF. The properties of these materials are varied between each other, which can affect the building part. The objective of this paper is to do an overview of the titanium powders available in LBPF. Comparison between different literature works will lead us to study the similarities and differences between the powder properties such as size, shape, and chemical composition. Furthermore, the results of this paper will point out the significant titanium powder properties in order to clearly illustrate their effect on the build parts.

Keywords: LPBF, titanium, Ti-6Al-4V, Ti-5553, metal powder, AM

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Authors: Muhammad Fawad

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Monitoring and structural health assessment are the primary requirements for the performance evaluation of damaged bridges. This paper highlights the case study of a damaged Reinforced Concrete (RC) bridge structure where the Finite element (FE) modelling of this structure was done using the material properties extracted by the in-situ testing. Analysis was carried out to evaluate the bridge damage. On the basis of FE analysis results, this study proposes a proper Structural Health Monitoring (SHM) system that will extend the life cycle of the bridge with minimal repair costs and reduced risk of failure. This system is based on the installation of three different types of sensors: Liquid Levelling sensors (LLS) for measurement of vertical displacement, Distributed Fiber Optic Sensors (DFOS) for crack monitoring, and Weigh in Motion (WIM) devices for monitoring of moving loads on the bridge.

Keywords: bridges, reinforced concrete, finite element method, structural health monitoring, sensors

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Authors: Juzar Vohra, Ravish Malhotra, Tim Pasang, Mana Azizi, Yuan Tao, Masami Mizutani

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In this paper, dissimilar welding of titanium to stainless steels is reported. Laser Beam Welding (LBW) and Gas Tungsten Arc Welding (GTAW) were employed to join CPTi to SS304. The welds were examined using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). FeTi, Ti2Cr and Fe2Ti dendrites are formed along with beta phase titanium matrix. The hardness values of these phases are high which makes them brittle and leading to cracking along the weld pool. However, it is believed that cracking, hence, fracturing of this weld joint is largely due to the difference in thermal properties of the two alloys.

Keywords: dissimilar metals, fusion welding, intermetallics, brittle

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

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Authors: Daniel Schimmelpfennig

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This paper attempts to delineate the idea to curate the leveling up for whole-systems change. Curation is the act fo select, organize, look after, or present information from a professional point of view through expert knowledge. The trans-paradigmatic, trans-contextual, trans-disciplinary, trans-perspective of trans-media futures studies hopes to enable a move from a monochrome intellectual pursuit towards breathing a higher dimensionality. Progressing to the next level to equip actors for whole-systems change is in consideration of the commonly known symptoms of our time as well as in anticipation of future challenges, both a necessity and desirability. Systems of collective intelligence could potentially scale regenerative, adaptive, and anticipatory capacities. How could such a curation then be enacted and implemented, to initiate the process of leveling-up? The suggestion here is to focus on the metasystem transition, the bio-digital fusion, namely, by merging neurosciences, the ontological design of money as our operating system, and our understanding of the billions of years of time-proven permutations in nature, biomimicry, and biological metaphors like symbiogenesis. Evolutionary cybernetics accompanies the process of whole-systems change.

Keywords: bio-digital fusion, evolutionary cybernetics, metasystem transition, symbiogenesis, transmedia futures studies

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Authors: Han Xue, Zhang Lanyue

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In order to seek more effective feature extraction technology, feature extraction method based on MFCC combined with vector hydrophone is exposed in the paper. The sound pressure signal and particle velocity signal of two kinds of ships are extracted by using MFCC and its evolution form, and the extracted features are fused by using fisher-ratio and correlated distance criterion. The features are then identified by BP neural network. The results showed that MFCC, First-Order Differential MFCC and Second-Order Differential MFCC features can be used as effective features for recognition of underwater targets, and the fusion feature can improve the recognition rate. Moreover, the results also showed that the recognition rate of the particle velocity signal is higher than that of the sound pressure signal, and it reflects the superiority of vector signal processing.

Keywords: vector information, MFCC, differential MFCC, fusion feature, BP neural network

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Authors: Keyur Raval, Steffen Krohn, Bruno Moerschbacher

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Chitin, the biopolymer of the N-acetylglucosamine, is the most abundant biopolymer on the planet after cellulose. Industrially, chitin is isolated and purified from the shell residues of shrimps. A deacetylated derivative of chitin i.e. chitosan has more market value and applications owing to it solubility and overall cationic charge compared to the parent polymer. This deacetylation on an industrial scale is performed chemically using alkalis like sodium hydroxide. This reaction not only is hazardous to the environment owing to negative impact on the marine ecosystem. A greener option to this process is the enzymatic process. In nature, the naïve chitin is converted to chitosan by chitin deacetylase (CDA). This enzymatic conversion on the industrial scale is however hampered by the crystallinity of chitin. Thus, this enzymatic action requires the substrate i.e. chitin to be soluble which is technically difficult and an energy consuming process. We in this project wanted to address this shortcoming of CDA. In lieu of this, we have modeled a fusion protein with CDA and an auxiliary protein. The main interest being to increase the accessibility of the enzyme towards crystalline chitin. A similar fusion work with chitinases had improved the catalytic ability towards insoluble chitin. In the first step, suitable partners were searched through the protein data bank (PDB) wherein the domain architecture were sought. The next step was to create the models of the fused product using various in silico techniques. The models were created by MODELLER and evaluated for properties such as the energy or the impairment of the binding sites. A fusion PCR has been designed based on the linker sequences generated by MODELLER and would be tested for its activity towards insoluble chitin.

Keywords: chitin deacetylase, modeling, chitin binding domain, chitinases

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Authors: Sourabh Yaduvanshi, Varsha Namdeo, Namrata Yaduvanshi

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This study delves into the design and development intricacies of crafting detailed 2D bar charts via d3.js, recognizing its limitations in generating 3D visuals within the DOM. The study combines three.js with d3.js, facilitating a smooth evolution from 2D to immersive 3D representations. This fusion epitomizes the synergy between front-end technologies, expanding horizons in data visualization. Beyond technical expertise, it symbolizes a creative convergence, pushing boundaries in visual representation. The abstract illuminates methodologies, unraveling the intricate integration of this fusion and guiding enthusiasts. It narrates a compelling story of transcending 2D constraints, propelling data visualization into captivating three-dimensional realms, and igniting creativity in front-end visualization endeavors.

Keywords: design, development, front-end technologies, visualization

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Authors: D. Zhao, Y. Wang, G. Chen

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Gas sensors that utilize carbonaceous materials as sensing media offer numerous advantages, making them the preferred choice for constructing chemical sensors over those using other sensing materials. Carbonaceous materials, particularly nano-sized ones like carbon nanotubes (CNTs), provide these sensors with high sensitivity. Additionally, carbon-based sensors possess other advantageous properties that enhance their performance, including high stability, low power consumption for operation, and cost-effectiveness in their construction. These properties make carbon-based sensors ideal for a wide range of applications, especially in miniaturized devices created through MEMS or NEMS technologies. To capitalize on these properties, a group of chemoresistance-type carbon-based gas sensors was developed and tested against various volatile organic compounds (VOCs) and volatile inorganic compounds (VICs). The results demonstrated exceptional sensitivity to both VOCs and VICs, along with the sensor’s long-term stability. However, this broad sensitivity also led to poor selectivity towards specific gases. This project aims at addressing the selectivity issue by modifying the carbon-based sensing materials and enhancing the sensor's specificity to individual gas. Multiple groups of sensors were manufactured and modified using proprietary techniques. To assess their performance, we conducted experiments on representative sensors from each group to detect a range of VOCs and VICs. The VOCs tested included acetone, dimethyl ether, ethanol, formaldehyde, methane, and propane. The VICs comprised carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2), nitric oxide (NO), and nitrogen dioxide (NO2). The concentrations of the sample gases were all set at 50 parts per million (ppm). Nitrogen (N2) was used as the carrier gas throughout the experiments. The results of the gas sensing experiments are as follows. In Group 1, the sensors exhibited selectivity toward CO2, acetone, NO, and NO2, with NO2 showing the highest response. Group 2 primarily responded to NO2. Group 3 displayed responses to nitrogen oxides, i.e., both NO and NO2, with NO2 slightly surpassing NO in sensitivity. Group 4 demonstrated the highest sensitivity among all the groups toward NO and NO2, with NO2 being more sensitive than NO. In conclusion, by incorporating several modifications using carbon nanotubes (CNTs), sensors can be designed to respond well to NOx gases with great selectivity and without interference from other gases. Because the response levels to NO and NO2 from each group are different, the individual concentration of NO and NO2 can be deduced.

Keywords: gas sensors, carbon, CNT, MEMS/NEMS, VOC, VIC, high selectivity, modification of sensing materials

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Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

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Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

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The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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Authors: Tahreem Yousaf, Michael P. Bradley, Jerzy A. Szpunar

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Currently, nuclear fusion is considered one of the most favorable options for future energy generation, due both to its abundant fuel and lack of emissions. For fusion power reactors, a major problem will be a suitable material choice for the Plasma Facing Components (PFCs) which will constitute the reactor first wall. Tungsten (W) has advantages as a PFC material because of its high melting point, low vapour pressure, high thermal conductivity and low retention of hydrogen isotopes. However, several adverse effects such as embrittlement, melting and morphological evolution have been observed in W when it is bombarded by low-energy and high-fluence helium (He) and deuterium (D) ions, as a simulation conditions adjacent to a fusion plasma. Recently, tantalum (Ta) also investigate as PFC and show better reluctance to nanostructure fuzz as compared to W under simulated fusion plasma conditions. But retention of D ions found high in Ta than W. Preparatory to plasma-based ion implantation studies, the effect of D and He ion impact on W and Ta is predicted by using the stopping and range of ions in the matter (SRIM) code. SRIM provided some theoretical results regarding projected range, ion concentration (at. %) and displacement damage (dpa) in W and Ta. The projected range for W under Irradiation of He and D ions with an energy of 3-keV and 1×fluence is determined 75Å and 135 Å and for Ta 85Å and 155Å, respectively. For both W and Ta samples, the maximum implanted peak for helium is predicted ~ 5.3 at. % at 12 nm and for De ions concentration peak is located near 3.1 at. % at 25 nm. For the same parameters, the displacement damage for He ions is observed in W ~ 0.65 dpa and Ta ~ 0.35 dpa at 5 nm. For D ions the displacement damage for W ~ 0.20 dpa at 8 nm and Ta ~ 0.175 dpa at 7 nm. The mean implantation depth is same for W and Ta, i.e. for He ions ~ 40 nm and D ions ~ 70 nm. From these results, we conclude that retention of D is high than He ions, but damage is low for Ta as compared to W. Further investigation still in progress regarding W and T.

Keywords: helium and deuterium ion impact, plasma facing components, SRIM simulation, tungsten, tantalum

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Authors: S. K. Tiwari, Dinesh Kumar Shukla, R. Chandra

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Friction stir welding is a solid state joining process. High strength aluminum alloys are widely used in aircraft and marine industries. Generally, the mechanical properties of fusion-welded aluminum joints are poor. As friction stir welding occurs in the solid state, no solidification structures are created thereby eliminating the brittle and eutectic phases common in fusion welding of high strength aluminum alloys. In this review, the process parameters, microstructural evolution and effect of friction stir welding on the properties of weld specific to aluminum alloys have been discussed.

Keywords: aluminum alloys, friction stir welding (FSW), microstructure, Properties.

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Authors: Hiba Naccache, Rima Hleiss

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Additive manufacturing AM or 3D printing is one of the pillars of Industry 4.0. Compared to traditional manufacturing, AM provides a prototype before production in order to optimize the design and avoid the stock market and uses strictly necessary material which can be recyclable, for the benefit of leaning towards local production, saving money, time and resources. Different types of AM exist and it has a broad range of applications across several industries like aerospace, automotive, medicine, education and else. The Laser Powder Bed Fusion (LPBF) is a metal AM technique that uses a laser to liquefy metal powder, layer by layer, to build a three-dimensional (3D) object. In industry 4.0 and aligned with the numbers 9 (Industry, Innovation and Infrastructure) and 12 (Responsible Production and Consumption) of the Sustainable Development Goals of the UNESCO 2030 Agenda, the AM’s manufacturers committed to minimizing the environmental impact by being sustainable in every production. The LPBF has several environmental advantages, like reduced waste production, lower energy consumption, and greater flexibility in creating components with lightweight and complex geometries. However, LPBF also have environmental drawbacks, like energy consumption, gas consumption and emissions. It is critical to recognize the environmental impacts of LPBF in order to mitigate them. To increase awareness and promote sustainable practices regarding LPBF, the researchers use the Elaboration Likelihood Model (ELM) theory where people from multiple universities in France and Qatar process information in two ways: peripherally and centrally. The peripheral campaigns use superficial cues to get attention, and the central campaigns provide clear and concise information. The authors created a seminar including a video showing LPBF production and a website with educational resources. The data is collected using questionnaire to test attitude about the public awareness before and after the seminar. The results reflected a great shift on the awareness toward LPBF and its impact on the environment. With no presence of similar research, to our best knowledge, this study will add to the literature on the sustainability of the LPBF production technique.

Keywords: additive manufacturing, laser powder bed fusion, elaboration likelihood model theory, sustainable development goals, education-awareness, France, Qatar, specific energy consumption, environmental impact, lightweight components

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Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

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Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor

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Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček

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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.

Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Amira Zrelli, Tahar Ezzeddine

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Measurement and monitoring of temperature, humidity and strain variation are very requested in great fields and areas such as structural health monitoring (SHM) systems. Currently, the use of fiber Bragg grating sensors (FBGS) is very recommended in SHM systems due to the specifications of these sensors. In this paper, we present the theory of Bragg sensor, therefore we try to measure the efficient variation of strain, temperature and humidity (SV, ST, SH) using Bragg sensor. Thus, we can deduce the fundamental relation between these parameters and the wavelength of Bragg sensor.

Keywords: Fiber Bragg Grating Sensors (FBGS), strain, temperature, humidity, structural health monitoring (SHM)

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Authors: Sayed Isahaq Hossain, K. T. Chang, Moustapha Ndour

Abstract:

Inference of the phreatic line through earth dams is of paramount importance because it could be directly associated with piping phenomena which may lead to the dam failure. Normally in the field, the instrumentations such as ‘diver’ and ‘standpipe’ are to be used to identify the seepage conditions which only provide point data with a fair amount of interpolation or assumption. Here in this paper, we employed high-resolution fiber optic cable sensors (FOCS) based on Raman Scattering in order to obtain a very accurate phreatic line and seepage profile. Unlike the above-mention devices which pinpoint the water level location, this kind of Distributed Fiber Optics Sensing gives us more reliable information due to its inherent characteristics of continuous measurement.

Keywords: standpipe, diver, FOCS, monitoring, Raman scattering

Procedia PDF Downloads 325

Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

Abstract:

In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring

Procedia PDF Downloads 205

Authors: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

Abstract:

Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

Procedia PDF Downloads 352

Authors: Zhdanova A. O., Volkov R. S., Kuznetsov G. V., Strizhak P. A.

Abstract:

Fires in different types of facilities are a serious problem worldwide.It is still an unaccomplished science and technology objective to establish the minimum number and type of sensors in automatic systems of compartment fire suppression which would turn the fire-extinguishing agent spraying on and off in real time depending on the state of the fire, minimize the amount of agent applied, delay time in fire suppression and system response, as well as the time of combustion suppression. Based on the results of experimental studies, the conclusion was made that it is reasonable to use a gas analysis system and heat sensors (in the event of their prior activation) to determine the effectiveness of fire suppression (fire-extinguishing composition interacts with the fire). Thus, the concentration of CO in the interaction of the firefighting liquid with the fire increases to 0.7–1.2%, which indicates a slowdown in the flame combustion, and heat sensors stop responding at a gas medium temperature below 80 ºC, which shows a gradual decrease in the heat release from the fire. The evidence from this study suggests that the information received from the video recording equipment (video camera) should be used in real time as an additional parameter confirming fire suppression. Research was supported by Russian Science Foundation (project No 21-19-00009, https://rscf.ru/en/project/21-19-00009/).

Keywords: compartment fires, fire suppression, continuous control of fire behavior, feedback systems

Procedia PDF Downloads 102