Search results for: buried pipeline
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 380

Search results for: buried pipeline

170 Production Optimization through Ejector Installation at ESA Platform Offshore North West Java Field

Authors: Arii Bowo Yudhaprasetya, Ario Guritno, Agus Setiawan, Recky Tehupuring, Cosmas Supriatna

Abstract:

The offshore facilities condition of Pertamina Hulu Energi Offshore North West Java (PHE ONWJ) varies greatly from place to place, depending on the characteristics of the presently installed facilities. In some locations, such as ESA platform, gas trap is mainly caused by the occurrence of flash gas phenomenon which is known as mechanical-physical separation process of multiphase flow. Consequently, the presence of gas trap at main oil line would accumulate on certain areas result in a reduced oil stream throughout the pipeline. Any presence of discrete gaseous along continuous oil flow represents a unique flow condition under certain specific volume fraction and velocity field. From gas lift source, a benefit line is used as a motive flow for ejector which is designed to generate a syphon effect to minimize the gas trap phenomenon. Therefore, the ejector’s exhaust stream will flow to the designated point without interfering other systems.

Keywords: diffuser, ejector, flow, fluent

Procedia PDF Downloads 411
169 Capture of Co₂ From Natural Gas Using Modified Imidazolium Ionic Liquids

Authors: Alaa A. Ghanem, S. E. M. Desouky

Abstract:

Natural gas (NG) is considered one of the most essential global energy sources. NG fields are often far away from the market, and a long-distance transporting pipeline usually is required. Production of NG with high content of CO₂ leads to severe problems such as equipment corrosion along with the production line until refinery.in addition to a high level of toxicity and decreasing in calorific value of the NG. So it is recommended to remove or decrease the CO₂ percent to meet transport specifications. This can be reached using different removal techniques such as physical and chemical absorption, pressure swing adsorption, membrane separation, or low-temperature separation. Many solvents and chemicals are being used to capture carbon dioxide on a large scale; among them, Ionic liquids have great potential due to their tunable properties; low vapour pressure, low melting point, and sensible thermal stability. In this research, three modifiedimidazolium ionic liquids will be synthesized and characterized using different tools of analysis such as FT-IR, 1H NMR. Thermal stability and surface activity will be studied. The synthesized compounds will be evaluated as selective solvents for CO₂ removal from natural gas using PVT cell.

Keywords: natural gas, CO₂ capture, imidazolium ionic liquid, PVT cell

Procedia PDF Downloads 149
168 The Superhydrophobic Surface Effect on Laminar Boundary Layer Flows

Authors: Chia-Yung Chou, Che-Chuan Cheng, Chin Chi Hsu, Chun-Hui Wu

Abstract:

This study investigates the fluid of boundary layer flow as it flows through the superhydrophobic surface. The superhydrophobic surface will be assembled into an observation channel for fluid experiments. The fluid in the channel will be doped with visual flow field particles, which will then be pumped by the syringe pump and introduced into the experimentally observed channel through the pipeline. Through the polarized light irradiation, the movement of the particles in the channel is captured by a high-speed camera, and the velocity of the particles is analyzed by MATLAB to find out the particle velocity field changes caused on the fluid boundary layer. This study found that the superhydrophobic surface can effectively increase the velocity near the wall surface, and the faster with the flow rate increases. The superhydrophobic surface also had longer the slip length compared with the plan surface. In the calculation of the drag coefficient, the superhydrophobic surface produces a lower drag coefficient, and there is a more significant difference when the Re reduced in the flow field.

Keywords: hydrophobic, boundary layer, slip length, friction

Procedia PDF Downloads 117
167 Ta-DAH: Task Driven Automated Hardware Design of Free-Flying Space Robots

Authors: Lucy Jackson, Celyn Walters, Steve Eckersley, Mini Rai, Simon Hadfield

Abstract:

Space robots will play an integral part in exploring the universe and beyond. A correctly designed space robot will facilitate OOA, satellite servicing and ADR. However, problems arise when trying to design such a system as it is a highly complex multidimensional problem into which there is little research. Current design techniques are slow and specific to terrestrial manipulators. This paper presents a solution to the slow speed of robotic hardware design, and generalizes the technique to free-flying space robots. It presents Ta-DAH Design, an automated design approach that utilises a multi-objective cost function in an iterative and automated pipeline. The design approach leverages prior knowledge and facilitates the faster output of optimal designs. The result is a system that can optimise the size of the base spacecraft, manipulator and some key subsystems for any given task. Presented in this work is the methodology behind Ta-DAH Design and a number optimal space robot designs.

Keywords: space robots, automated design, on-orbit operations, hardware design

Procedia PDF Downloads 39
166 SCANet: A Workflow for Single-Cell Co-Expression Based Analysis

Authors: Mhaned Oubounyt, Jan Baumbach

Abstract:

Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

Procedia PDF Downloads 100
165 Determination of the Quantity of Water Absorbed by the Plant When Irrigating by Infiltration in Arid Regions (Case of Ouargla in Algeria)

Authors: Mehdi Benlarbi, Dalila Oulhaci

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Several physical, human and economic factors come into play in the choice of an irrigation system for developing arid and semi-arid regions. Since it is impossible to define or weight quantitatively all the relevant factors in each case, the choice of the system is often based on subjective preferences rather than explicit analysis. Over the past decade, irrational irrigation in the Ouargla region has evolved to a certain extent based largely on water wastage and which may pose risks to the environment both off-site and at the site. In the whole region, the environment is damaged by excess water because the water tables that tend to be high form swamps that pollute nature on the surface. The purpose of our work is a comparison between sprinkler irrigation and drip irrigation using bottles. By irrigating with the aid of the bottle and giving a volume of 4 liters with a flow rate of one (1) liter per hour, the watering dose received varies between 6 and 7 mm without infiltration losses. And for the case of sprinkler irrigation, the dose received may not exceed 2.5mm. E in some cases, we have a quantity of water lost by infiltration. This shows that irrigation using the bottle is much more efficient than sprinkling. Because, on the one hand, a large amount of water is absorbed by the plant and on the other hand, there is no loss by infiltration. The results obtained are very significant because, on the one hand, we reuse local products, and on the other hand, as the bottles are buried, we avoid water losses by evaporation, especially in dry periods and salinization.

Keywords: resources, water, arid, evaporation, infiltration

Procedia PDF Downloads 48
164 Self-Propelled Intelligent Robotic Vehicle Based on Octahedral Dodekapod to Move in Active Branched Pipelines with Variable Cross-Sections

Authors: Sergey N. Sayapin, Anatoly P. Karpenko, Suan H. Dang

Abstract:

Comparative analysis of robotic vehicles for pipe inspection is presented in this paper. The promising concept of self-propelled intelligent robotic vehicle (SPIRV) based on octahedral dodekapod for inspection and operation in active branched pipelines with variable cross-sections is reasoned. SPIRV is able to move in pipeline, regardless of its spatial orientation. SPIRV can also be used to move along the outside of the pipelines as well as in space between surfaces of annular tubes. Every one of faces of the octahedral dodekapod can clamp/unclamp a thing with a closed loop surface of various forms as well as put pressure on environmental surface of contact. These properties open new possibilities for its applications in SPIRV. We examine design principles of octahedral dodekapod as future intelligent building blocks for various robotic vehicles that can self-move and self-reconfigure.

Keywords: Modular robot, octahedral dodekapod, pipe inspection robot, spatial parallel structure

Procedia PDF Downloads 478
163 Machine Learning Strategies for Data Extraction from Unstructured Documents in Financial Services

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

Procedia PDF Downloads 86
162 Multiresolution Mesh Blending for Surface Detail Reconstruction

Authors: Honorio Salmeron Valdivieso, Andy Keane, David Toal

Abstract:

In the area of mechanical reverse engineering, processes often encounter difficulties capturing small, highly localized surface information. This could be the case if a physical turbine was 3D scanned for lifecycle management or robust design purposes, with interest on eroded areas or scratched coating. The limitation partly is due to insufficient automated frameworks for handling -localized - surface information during the reverse engineering pipeline. We have developed a tool for blending surface patches with arbitrary irregularities into a base body (e.g. a CAD solid). The approach aims to transfer small surface features while preserving their shape and relative placement by using a multi-resolution scheme and rigid deformations. Automating this process enables the inclusion of outsourced surface information in CAD models, including samples prepared in mesh handling software, or raw scan information discarded in the early stages of reverse engineering reconstruction.

Keywords: application lifecycle management, multiresolution deformation, reverse engineering, robust design, surface blending

Procedia PDF Downloads 118
161 Accelerating Mobile Innovation, Adoption, and Translational Science within a Large Research Enterprise and Healthcare System

Authors: Stephen Wheat

Abstract:

Institutional mobile application governance and distribution processes are essential to mobile app innovation. The absence of effective processes poses a significant barrier to the development and adoption of mobile apps for use within a research enterprise and also impedes the translational science of applying research apps in clinical and engineering settings. To accelerate mobile app innovation and adoption, Emory University and Emory Healthcare implemented a three-pronged strategy including. I) Mobile app review and distribution policies and processes. II) Mobile app management infrastructure and mobile app foundation components. III) A strategic sourcing strategy based on preferred mobile app development firms. The results have been an increase from five to 56 mobile apps in the pipeline over three years; increased engagement from technology transfer, legal counsel, compliance, and information security; articulation of a coordinated mobile app strategy; and allocation of more institutional resources toward specific mobile technology and mobile application goals.

Keywords: mobile app management, governance, distribution, information security

Procedia PDF Downloads 268
160 Numerical Study of a Butterfly Valve for Vibration Analysis and Reduction

Authors: Malik I. Al-Amayreh, Mohammad I. Kilani, Ahmed S. Al-Salaymeh

Abstract:

This works presents a Computational Fluid Dynamics (CFD) simulation of a butterfly valve used to control the flow of combustible gas mixture in an industrial process setting. The work uses CFD simulation to analyze the flow characteristics in the vicinity of the valve, including the velocity distributions, streamlines and path lines. Frequency spectrum of the pressure pulsations downstream the valves, and the vortex shedding allow predicting the torque fluctuations acting on the valve shaft and the possibility of generating mechanical vibration and resonance. These fluctuations are due to aerodynamic torque resulting from fluid turbulence and vortex shedding in the valve vicinity. The valve analyzed is located in a pipeline between two opposing 90o elbows, which exposes the valve and the surrounding structure to the turbulence generated upstream and downstream the elbows at either end of the pipe. CFD simulations show that the best location for the valve from a vibration point of view is in the middle of the pipe joining the elbows.

Keywords: butterfly valve vibration analysis, computational fluid dynamics, fluid flow circuit design, fluctuation

Procedia PDF Downloads 407
159 Predictive Maintenance: Machine Condition Real-Time Monitoring and Failure Prediction

Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 358
158 Preliminary Study on the Removal of Solid Uranium Compound in Nuclear Fuel Production System

Authors: Bai Zhiwei, Zhang Shuxia

Abstract:

By sealing constraint, the system of nuclear fuel production penetrates a trace of air in during its service. The vapor in the air can react with material in the system and generate solid uranium compounds. These solid uranium compounds continue to accumulate and attached to the production equipment and pipeline of system, which not only affects the operation reliability of production equipment and give off radiation hazard as well after system retired. Therefore, it is necessary to select a reasonable method to remove it. Through the analysis of physicochemical properties of solid uranium compounds, halogenated fluoride compounds are selected as a cleaning agent, which can remove solid uranium compounds effectively. This paper studied the related chemical reaction under the condition of static test and results show that the selection of high fluoride halogen compounds can be removed solid uranium compounds completely. The study on the influence of reaction pressure with the reaction rate discovered a phenomenon that the higher the pressure, the faster the reaction rate.

Keywords: fluoride halogen compound, remove, radiation, solid uranium compound

Procedia PDF Downloads 276
157 Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms

Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 247
156 Numerical Analysis of the Effect of Geocell Reinforcement above Buried Pipes on Surface Settlement and Vertical Pressure

Authors: Waqed H. Almohammed, Mohammed Y. Fattah, Sajjad E. Rasheed

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Dynamic traffic loads cause deformation of underground pipes, resulting in vehicle discomfort. This makes it necessary to reinforce the layers of soil above underground pipes. In this study, the subbase layer was reinforced. Finite element software (PLAXIS 3D) was used to in the simulation, which includes geocell reinforcement, vehicle loading, soil layers and Glass Fiber Reinforced Plastic (GRP) pipe. Geocell reinforcement was modeled using a geogrid element, which was defined as a slender structure element that has the ability to withstand axial stresses but not to resist bending. Geogrids cannot withstand compression but they can withstand tensile forces. Comparisons have been made between the numerical models and experimental works, and a good agreement was obtained. Using the mathematical model, the performance of three different pipes of diameter 600 mm, 800 mm, and 1000 mm, and three different vehicular speeds of 20 km/h, 40 km/h, and 60 km/h, was examined to determine their impact on surface settlement and vertical pressure at the pipe crown for two cases: with and without geocell reinforcement. The results showed that, for a pipe diameter of 600 mm under geocell reinforcement, surface settlement decreases by 94 % when the speed of the vehicle is 20 km/h and by 98% when the speed of the vehicle is 60 km/h. Vertical pressure decreases by 81 % when the diameter of the pipe is 600 mm, while the value decreases to 58 % for a pipe with diameter 1000 mm. The results show that geocell reinforcement causes a significant and positive reduction in surface settlement and vertical stress above the pipe crown, leading to an increase in pipe safety.

Keywords: dynamic loading, finite element, geocell-reinforcement, GRP pipe, PLAXIS 3D, surface settlement

Procedia PDF Downloads 225
155 An Integrated Web-Based Workflow System for Design of Computational Pipelines in the Cloud

Authors: Shuen-Tai Wang, Yu-Ching Lin

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With more and more workflow systems adopting cloud as their execution environment, it presents various challenges that need to be addressed in order to be utilized efficiently. This paper introduces a method for resource provisioning based on our previous research of dynamic allocation and its pipeline processes. We present an abstraction for workload scheduling in which independent tasks get scheduled among various available processors of distributed computing for optimization. We also propose an integrated web-based workflow designer by taking advantage of the HTML5 technology and chaining together multiple tools. In order to make the combination of multiple pipelines executing on the cloud in parallel, we develop a script translator and an execution engine for workflow management in the cloud. All information is known in advance by the workflow engine and tasks are allocated according to the prior knowledge in the repository. This proposed effort has the potential to provide support for process definition, workflow enactment and monitoring of workflow processes. Users would benefit from the web-based system that allows creation and execution of pipelines without scripting knowledge.

Keywords: workflow systems, resources provisioning, workload scheduling, web-based, workflow engine

Procedia PDF Downloads 125
154 High Level Synthesis of Canny Edge Detection Algorithm on Zynq Platform

Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

Procedia PDF Downloads 451
153 Development of a Wall Climbing Robotic Ground Penetrating Radar System for Inspection of Vertical Concrete Structures

Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

Abstract:

This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: climbing robot, dipole antenna, ground penetrating radar (GPR), mobile robots, robotic GPR

Procedia PDF Downloads 246
152 Semantic Indexing Improvement for Textual Documents: Contribution of Classification by Fuzzy Association Rules

Authors: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

Procedia PDF Downloads 118
151 Radio-Frequency Technologies for Sensing and Imaging

Authors: Cam Nguyen

Abstract:

Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

Procedia PDF Downloads 289
150 An Improved Total Variation Regularization Method for Denoising Magnetocardiography

Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

Procedia PDF Downloads 122
149 Sewer Culvert Installation Method to Accommodate Underground Construction in an Urban Area with Narrow Streets

Authors: Osamu Igawa, Hiroshi Kouchiwa, Yuji Ito

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In recent years, a reconstruction project for sewer pipelines has been progressing in Japan with the aim of renewing old sewer culverts. However, it is difficult to secure a sufficient base area for shafts in an urban area because many streets are narrow with a complex layout. As a result, construction in such urban areas is generally very demanding. In urban areas, there is a strong requirement for a safe, reliable and economical construction method that does not disturb the public’s daily life and urban activities. With this in mind, we developed a new construction method called the 'shield switching type micro-tunneling method' which integrates the micro-tunneling method and shield method. In this method, pipeline is constructed first for sections that are gently curved or straight using the economical micro-tunneling method, and then the method is switched to the shield method for sections with a sharp curve or a series of curves without establishing an intermediate shaft. This paper provides the information, features and construction examples of this newly developed method.

Keywords: micro-tunneling method, secondary lining applied RC segment, sharp curve, shield method, switching type

Procedia PDF Downloads 371
148 Array Type Miniaturized Ultrasonic Sensors for Detecting Sinkhole in the City

Authors: Won Young Choi, Kwan Kyu Park

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Recently, the road depression happening in the urban area is different from the cause of the sink hole and the generation mechanism occurring in the limestone area. The main cause of sinkholes occurring in the city center is the loss of soil due to the damage of old underground buried materials and groundwater discharge due to large underground excavation works. The method of detecting the sinkhole in the urban area is mostly using the Ground Penetration Radar (GPR). However, it is challenging to implement compact system and detecting watery state since it is based on electromagnetic waves. Although many ultrasonic underground detection studies have been conducted, near-ground detection (several tens of cm to several meters) has been developed for bulk systems using geophones as a receiver. The goal of this work is to fabricate a miniaturized sinkhole detecting system based on low-cost ultrasonic transducers of 40 kHz resonant frequency with high transmission pressure and receiving sensitivity. Motived by biomedical ultrasonic imaging methods, we detect air layers below the ground such as asphalt through the pulse-echo method. To improve image quality using multi-channel, linear array system is implemented, and image is acquired by classical synthetic aperture imaging method. We present the successful feasibility test of multi-channel sinkhole detector based on ultrasonic transducer. In this work, we presented and analyzed image results which are imaged by single channel pulse-echo imaging, synthetic aperture imaging.

Keywords: road depression, sinkhole, synthetic aperture imaging, ultrasonic transducer

Procedia PDF Downloads 120
147 Evaluating the Use of Manned and Unmanned Aerial Vehicles in Strategic Offensive Tasks

Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

Procedia PDF Downloads 517
146 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

Abstract:

With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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145 Geophysical Approach in the Geological Characterization of a Dam Site: Case of the Chebabta-Dam, Meskiana, Oum El-Bouaghi

Authors: Benhammadi Hocine, Djamel Boubaya, Chaffai Hicham

Abstract:

Meskiana Area is characterized by a semi-arid climate where the water supply for irrigation and industry is not sufficient as the priority goes for domestic use. To meet the increasing population growth and development, the authorities have considered building a new water retaining structure on some major temporary water streams. For this purpose Chebabta site on Oued Meskiana was chosen as the future dam site. It is large enough to store the desired volume of water. This study comes to investigate the conditions of the site and the adequacy of the ground as a foundation for the projected dam. The conditions of the site include the geological structure and mainly the presence of discontinuities in the formation on which the dam will be built, the nature of the lithologies under the foundation and the future lake, and the presence of any hazard. This site characterization is usually carried out using different methods in order to highlight any underground buried problematic structure. In this context, the different geophysical technics remain the most used ones. Three geophysical methods were used in the case of the Chebabta dam site, namely, electric survey, seismic refraction, and tomography. The choice of the technics and the location of the scan line was made on the basis of the available geological data. In this sense, profiles have been established on both banks of Oued Meskiana. The obtained results have allowed a better characterization of the geological structure, defining the limit between the surface cover and the bedrock, which is, in other words, the limit between the weathered zone and the bedrock. Their respective thicknesses were also determined by seismic refraction and electrical resistivity sounding. However, the tomography imaging technic has succeeded in positioning a fault structure passing through the right bank of the wadi.

Keywords: dam site, fault, geophysic, investigation, Meskiana

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144 Determination of the Water Needs of Some Crops Irrigated with Treated Water from the Sidi Khouiled Wastewater Treatment Plant in Ouargla, Algeria

Authors: Dalila Oulhaci, Mehdi Benlarbi, Mohammed Zahaf

Abstract:

The irrigation method is fundamental for maintaining a wet bulb around the roots of the crop. This is the case with localized irrigation, where soil moisture can be maintained permanently around the root system between the two water content extremes. Also, one of the oldest methods used since Roman times throughout North Africa and the Near East is based on the frequent dumping of water into porous pottery vases buried in the ground. In this context, these two techniques have been combined by replacing the pottery vase with plastic bottles filled with sand that discharge water through their perforated walls into the surrounding soil. The first objective of this work is the theoretical determination using CLIMWAT and CROPWAT software of the irrigation doses of some crops (palm, wheat, and onion) and experimental by measuring the humidity of the soil before and after watering. The second objective is to determine the purifying power of the sand filter in the bottle. Based on the CROPWAT software results, the date palm needs 18.5 mm in the third decade of December, 57.2 mm in January, and 73.7 mm in February, whereas the doses received by experimentally determined by means of soil moisture before and after irrigation are 19.5 mm respectively, 79.66 mm and 95.66 mm. The onion needs 14.3 mm in the third decade of December of, 59.1 mm in January, and 80 mm in February, whereas the experimental dose received is 15.07 mm, respectively, 64.54 and 86.8 mm. The total requirements for the vegetative period are estimated at 1642.6 mm for date palms, 277.4 mm for wheat, and 193.5 mm for onions. The removal rate of the majority of pollutants from the bottle is 80%. This work covers, on the one hand, the context of water conservation, sustainable development, and protection of the environment, and on the other, the agricultural field.

Keywords: irrigation, sand, filter, humidity, bottle

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143 Deepnic, A Method to Transform Each Variable into Image for Deep Learning

Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

Abstract:

Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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142 Target and Biomarker Identification Platform to Design New Drugs against Aging and Age-Related Diseases

Authors: Peter Fedichev

Abstract:

We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

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141 Synthesis of La0.8Sr0.05Ca0.15Fe0.8Co0.2O3-δ -Ce0.9Gd0.1O1.95 Composite Cathode Material for Solid Oxide Fuel Cell with Lanthanum and Cerium Recycled from Wasted Glass Polishing Powder

Authors: Jun-Lun Jiang, Bing-Sheng Yu

Abstract:

Processing of flat-panel displays generates huge amount of wasted glass polishing powder, with high concentration of cerium and other elements such as lanthanum. According to the current statistics, consumption of polishing powder was approximately ten thousand tons per year in the world. Nevertheless, wasted polishing powder was usually buried or burned. If the lanthanum and cerium compounds in the wasted polishing powder could be recycled, that will greatly reduce enterprise cost and implement waste circulation. Cathodes of SOFCs are the principal consisting of rare earth elements such as lanthanum and cerium. In this study, we recycled the lanthanum and cerium from wasted glass polishing powder by acid-solution method, and synthesized La0.8Sr0.05Ca0.15Fe0.8Co0.8O3-δ and Gd0.1Ce0.9O2 (LSCCF-GDC) composite cathode material for SOFCs by glycinenitrate combustion (GNP) method. The results show that the recovery rates of lanthanum and cerium could accomplish up to 80% and 100% under 10N nitric acid solution within one hour. Comparing with the XRD data of the commercial LSCCF-GDC powder and the LSCCF-GDC product synthesized with chemicals, we find that the LSCCF-GDC was successfully synthesized with the recycled La & Ce solution by GNP method. The effect of adding ammonia to the product was also discussed, the grain size is finer and recovery rate of the product is higher without the addition of ammonia to the solution.

Keywords: glass polishing powder, acid solution, recycling, composite cathodes of solid oxide fuel, cell (SOFC), perovskite, glycine-nitrate combustion(GNP) method

Procedia PDF Downloads 239