Composite Pipeline Research Articles

Numerical Studies on the Heat Effect of Explosion Suppression by a Heat Pipe

A composite structure with a heat pipe and foamed iron-nickel composite fire suppression is proposed on the basis of the phase-change heat transfer of the heat pipe, which simultaneously attenuates the metal foam explosion energy. A numerical simulation is conducted to evaluate the feasibility of the designed construction for suppressing explosions under various thicknesses and pore diameters of the metal foam. The results demonstrate that when the foam iron-nickel metal is installed in the pipeline, the temperature reduction rate in the pipeline can reach 8.9%. The new heat pipe foam composite structure can reduce the flame temperature to 1600 K within 0.095 s. It is concluded that the heat pipe composite metal foam structure pipeline has a strong effect on suppressing combustion and explosion overpressure. Due to the combined effect of the heat pipe vacuum chamber suction energy and the foamed iron-nickel, the flame temperature decay rate increases. The maximum attenuation rate of the foamed iron-nickel for the gas explosion shock wave reaches 41.76%, and the maximum flame temperature attenuation rate reaches 64.7%. The composite heat pipe structure can quickly disperse and transfer heat, thereby effectively destroying the heat storage environment as soon as possible to prevent a secondary explosion from occurring.

Phantom development applied to industrial tomography in composite material pipeline

Computed tomography allows the images reconstruction and the internal details visualization of the internal structure of the inspected volume, which generates a competitive gain for this technique in relation to the other NDT (Non-Destructive Testing) methods. Within this context, Petrobras has an R&D project in partnership with UFRJ (Federal University of Rio de Janeiro) to develop a field microCT for pipeline inspection with adhesive and laminated joints made of composite material. This work developed phantoms in polymeric material for study some parameters, such as contrast resolution, spatial resolution and dimensional metrology. Four phantoms were projected and manufatured for theses purposal. The objective was to study, measure and qualify parameters for the field microCT. The development and evaluation of these phantoms are presented throughout this work. It was possible to observe a good difference between the materials inserted in the contrast resolution phantom through the grey values measurement. Beyond it, it was achieved a spatial resolution about 200 ?m for this phantom, which is a reasonable value for microCT applied to pipelines inspection. Finally, the statistical analyses shown a good data quality and were very usefull to understand the results, which provide a good traceability for them.

Will a buried composite pipeline system fail at its joints under the effects of overburden soil, pipe operating pressurization, and traffic loads?

In real world applications, buried pipelines span across great lengths. It is inevitable that certain sections of a buried pipeline experience external loads in addition to top soil overburden, such as weights of aboveground buildings and traffic loads located directly above these sections. The present study investigated the effects of overburden soil, pipe internal pressurization, and traffic loads on fiber-reinforced plastic pipelines at various pipe sections with particular emphasis on pipe joints using finite element method. This study includes realistic modeling of traffic loading on service road running across a buried pipeline system, consisting of straight, bent, and joint sections. Our results also revealed that surcharge loading might not be a predominant factor in pipe failure or leakage issues as compared to the cyclic pipe internal pressurization. Moreover, it was also confirmed in our study that the pipe joint remained as the most critical region for pipe failure or leakage issues.

Obtaining Knowledge in Pathology Reports Through a Natural Language Processing Approach With Classification, Named-Entity Recognition, and Relation-Extraction Heuristics.

Robust institutional tumor banks depend on continuous sample curation or else subsequent biopsy or resection specimens are overlooked after initial enrollment. Curation automation is hindered by semistructured free-text clinical pathology notes, which complicate data abstraction. Our motivation is to develop a natural language processing method that dynamically identifies existing pathology specimen elements necessary for locating specimens for future use in a manner that can be re-implemented by other institutions. Pathology reports from patients with gastroesophageal cancer enrolled in The University of Chicago GI oncology tumor bank were used to train and validate a novel composite natural language processing-based pipeline with a supervised machine learning classification step to separate notes into internal (primary review) and external (consultation) reports; a named-entity recognition step to obtain label (accession number), location, date, and sublabels (block identifiers); and a results proofreading step. We analyzed 188 pathology reports, including 82 internal reports and 106 external consult reports, and successfully extracted named entities grouped as sample information (label, date, location). Our approach identified up to 24 additional unique samples in external consult notes that could have been overlooked. Our classification model obtained 100% accuracy on the basis of 10-fold cross-validation. Precision, recall, and F1 for class-specific named-entity recognition models show strong performance. Through a combination of natural language processing and machine learning, we devised a re-implementable and automated approach that can accurately extract specimen attributes from semistructured pathology notes to dynamically populate a tumor registry.

Transient thermal analysis of multilayer pipeline with phase change material

Based on thermal energy storage concept, multilayer composite pipeline with phase change material (PCM) has been proposed recently as an effective method to meet flow assurance challenges in deep water environment by releasing latent heat and extending cool-down time under shut-in condition. This work presents a mathematical model for the start-up and cool-down processes in a multilayer pipeline with an inner steel pipe, an intermediate PCM layer, and an external thermal insulation layer. With enthalpy formulation adopted for the PCM layer, the governing equations for heat conduction in the composite pipe walls and for energy transport in the produced fluid are solved numerically by explicit finite difference methods. The effects of the PCM thickness ratio, the phase change temperature, and the thermal conductivity ratio between the thermal insulation layer and phase change material are investigated. The effect of PCM hysteresis on the transient heat transfer process is also evaluated. It is found that there is an optimal PCM thickness ratio for a given combination of PCM and thermal insulation materials that maximizes the overall cool-down time. The cool-down time and the optimum PCM thickness ratio increase when the phase change temperature decreases. For a given PCM, the optimum PCM thickness ratio decreases for increasing thermal conductivity ratio. There is an interval of thermal conductivity ratio between 0.2 and 0.8 within which the PCM layer with optimum thickness ratio provides a significant increase in the cool-down time.

Implementation of Fourier Transformation with Brain Cancer and CSF Images

Objectives: Medicinal images assume a key part in the diagnosis of tumors as well as Cerebrospinal Fluid (CSF) leak. In a similar way, MRI could be the cutting edge regenerative imaging technology, which permits an angle sectional perspective of the body, which gives convenience to specialists to inspect the affected person. In this study, the authors had attempted the strategy to classify MRI images (4-Dimensional) either at the beginning of production to have a tumor or even can be utilized for tumor recognition. The aim of the study is to address the aforementioned problems associated with the brain cancer due to the leakage of CSF. Methods/Findings: This research is to construct the research framework that can identify cancer damage area or be isolated from tumors and non-tumors quiet by using Fourier transformation. Another research tool, based on Fourier Transform, is the main mathematical method for frequency analysis and has extensive engineering and science applications. Because DFT is omnipresent, there has been extensive study of highways for the DFT account and active research has continued. Application: Several fast algorithms are provided by the DFT partitioning method. In this document, we provide DFT with two rapid implementation algorithms to assess their performance. This study helps the detection of brain cancer due to the process of interfacing the 4-D (4 Dimensional) image segmentation process and Fourier transformation. 4-D is followed by MATLAB software modeling techniques to measure the size of brain damage cells deep inside of CSF. These Methods of light fields can be useful for improving the quality of application editing segmentation and light field composite pipeline, as they reduce boundary artefacts. Keywords: Brain Tumor, Cerebrospinal Fluid, Fourier Transformation, Image segmentation, MRI

Application of Glass Fiber Reinforced Polymer Composite (GFRPC) Escape Pipeline in Tunnel

During the tunnel construction process, unfavorable geological conditions are often encountered. Geological disasters such as collapse, roof fall, water inrush, gas explosion, etc. occur frequently, causing different degrees of property damage and casualties to the construction of the tunnel, seriously affecting harmony during construction. The domestic emergency hedging is mainly the use of 8-10mm steel coils, but the steel is heavy and not suitable for the frequent movement of tunnels. This paper introduces the new Glass Fiber Reinforced Polymer Composite (GFRPC) escape pipeline used in Chongqing Jiuyongyi Jinyunshan Tunnel, and compares the traditional steel coil parameters to provide reference for subsequent tunnel hedging measures.

Numerical Modeling of the Seismic Influence on an Underwater Composite Oil Pipeline

The problem of numerical modeling of the process of initiating seismic activity on the shelf and its destructive effect on composite oil pipelines laid along the seabed is considered. To describe the dynamic behavior of the medium, the determining systems of equations of the theory of elasticity and acoustics with explicit distinguishing all layers are used. The polymeric composite material of the pipeline is described in a visco-elastic orthotropic model. An algorithm that allows estimating the volume of oil pipeline destroyed at the specified level of seismic activity and strength characteristics of the composite is proposed. A distinctive feature of the developed approach involves splitting the problem into two stages: the full wave calculation of the propagation of seismic waves from the earthquake source to the day surface and the calculation of a composite pipeline element as a complexly shaped object of anisotropic material. For the numerical calculation, the grid-characteristic method is used for hexahedral and tetrahedral computational grids.

Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model.

Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires detecting and indexing a long sequence in a 3-D image, and both image feature extraction and sequence modeling are needed to address the problem. In this paper, the powerful fully convolutional neural network (FCN) technique performs both of these tasks simultaneously because FCNs directly encode and decode the spatial interdependence of different components in images. The key module of our proposed framework is a 3-D FCN trained in an end-to-end manner at the spine level to capture the long-range contextual information in CT volumes. The large increase in the calculation due to the full-size image inputs is alleviated by the scale-down of the inputs and the use of an auxiliary FCN to compensate for the loss of details. The composite network pipeline design enables the integration of local image details and global image patterns. Furthermore, explicit spatial and sequential constraints are imposed by the hidden Markov model (HMM) for a higher robustness and a clearer interpretation of network outputs. The proposed framework is quantitatively evaluated on the public dataset from the MICCAI 2014 Computational Challenge on Vertebrae Localization and Identification and demonstrates an identification rate (within 20 mm) of 94.67%, a mean identification rate of 87.97%, and a mean error distance of 2.56 mm on the test set, thus achieving the highest performance reported on this dataset.

MECHANICAL PROPERTIES OF CARBON NANOTUBES-MODIFIED EPOXY GROUT FOR PIPELINE REPAIR SYSTEM

Epoxy grout properties are theoretically important in predicting the behaviour of the composite pipeline repair system. Usually, it is used as an infill material to fill the gap or irregularity on the surface caused by pipe corrosion and ensures a smooth bed before fibre wrapper can be applied to recover the pipeline strength. In this research, the existing commercially available epoxy resin grout has been strengthened by using Carbon Nanotubes (CNTs) at the amount 0.1% of weight fractional to evaluate their apropos behaviour to the neat epoxy grout. The various mechanical tests were performed on this modified grout to identify its compression, tensile, flexural and lap shear strength. In addition, the dispersion process of CNTs was carried out by using ultrasonication and three-roll mill technique to ensure an optimum enhancement in the properties of the polymer matrix. By comparing the strength, 0.1% of CNTs filler has significantly improved the strength of grout in flexural, tensile and shear bonding but not in compression. In addition, the results also indicate that CNTs filler has increased the modulus of elasticity of the infill material. Therefore, it demonstrates the intrinsic potential of the CNTs in modifying the properties of the epoxy grout.

Deep Learning-Based Damage, Load and Support Identification for a Composite Pipeline by Extracting Modal Macro Strains from Dynamic Excitations

Modal macro strain-based damage identification is a promising approach since it has the advantages of high sensitivity and effectiveness over other related methods. In this paper, a basalt fiber-reinforced polymer (BFRP) pipeline system is used for analysis by using long-gauge distributed fiber Bragg grating (FBG) sensors. Dynamic macro strain responses are extracted to form modal macro strain (MMS) vectors. Both longitudinal distribution and circumferential distribution plots of MMS are compared and analyzed. Results show these plots can reflect damage information of the pipeline based on the previous work carried out by the authors. However, these plots may not be good choices for accurate detection of damage information since the model is 3D and has different flexural and torsional effects. Therefore, by extracting MMS information in the circumferential distribution plots, a novel deep neural network is employed to train and test these images, which reflect the important and key information of modal variance in the pipe system. Results show that the proposed Deep Learning based approach is a promising way to inherently identify damage types, location of the excitation load and support locations, especially when the structural types are complicated and the ambient environment is changing.

Composite gas pipelines: prospects of energy conservation

This article is devoted to the issue of assessing the feasibility of using alternative materials for the construction of gas mains. In this perspective, one of the most promising areas of the industry development is now the use of composite PE-RT polymer-based metal-plastic pipes. Such materials come with high durability, low unit weight and comparable cost to the traditional ones. The main operational advantage of composite pipelines is absolute stability in relation to corrosion.This makes it possible to exclude from a project of a gas transportation system the main facilities and auxiliary equipment of the electrochemical protection of pipelines.That substantially reduces the costs of CAPEX (for construction) and OPEX (electricity costs for the operation of the linear part of the main gas pipelines in terms of providing protection against corrosion). As a result, the guaranteed lifetime of composite gas pipeline systems reaches 80-100 years. In addition, composite pipes have minimum internal roughness. This beneficial characteristic allows gas to be pumped at a lower pressure and consequently reduce the consumption of fuel gas for gas-compressor units. The rationale for the work was the results of multiple joint meetings between the management of gas industry and the country’s power-generation system. During these meetings, long-term plans for the development of nanotechnologies and the introduction of composite pipes into the structure of the gas transportation system were adopted. A comparison of energy efficiency of steel pipes, steel pipes with an internal smooth coating and composite pipes was performed for a gas transportation system. The economic advantage of composite gas pipelines is established at the level of 7 times over the steel analogies.

Analytical behavior of carbon steel-concrete-stainless steel double-skin tube (DST) used in submarine pipeline structure

One type of submarine composite pipeline structure, with carbon steel-concrete-stainless steel (CCS) double-skin tube (DST), was introduced in this paper. This composite pipeline was expected to make optimal use of the three types of the materials, and provide significant structural and internal corrosion resistance. This study investigated the compressive and flexural behavior of the composite pipeline under internal content pressure and external hydrostatic pressure through finite element analysis (FEA). Finite element models were developed, where non-linear material properties of stainless steel and composite actions between constituent parts were considered. The models were verified through the comparisons between the numerically and experimentally determined results, in terms of load-deformation histories, failure modes and ultimate strength. Structural behaviors of the composite pipeline under pressures were compared with those without content and hydrostatic pressure. Parametric studies were carried out to investigate the effects of the outer carbon steel strength, inner stainless steel strength, concrete strength and hollow ratio on the compressive and flexural behaviors of the composite pipelines subjected to pressures.

Fatigue damage identification for composite pipeline systems using electrical capacitance sensors

This research investigates a damage identification framework for carbon fiber reinforced polymer composite pipeline systems using electrical capacitance sensors. First, a finite element pipeline model is established under the structural-thermal-electrostatic coupled field. Based on this model, an accumulative damage model is introduced to model the pipeline damage subjected to fatigue effect, and ten damage cases are considered. Both static and transient external excitations are loaded into the pipeline by installing distributed electrical capacitance sensors. A system transfer function is proposed and applied to the ‘open loop’ pipeline system. Results show these approaches perform great promises when damage evolves covering electrode pairs, the signal will change sensitively and abruptly with an order of magnitude.

On the Estimation of Seismic Resistance of Modern Composite Oil Pipeline Elements

The initiation of seismic activity on the continental shelf and its destructive effect on composite oil pipelines laid on the seabed is modeled numerically. The dynamic behavior of the medium is described by determining systems of elasticity and acoustic equations with an explicit separation of all layers. The composite is described as an orthotropic material. An algorithm is proposed that estimates the amount and type of oil pipeline destruction at a given level of seismic activity and given strength characteristics of the composite. A distinctive feature of the developed approach is that the problem is split into two stages calculated on different scales: the full-wave computation of seismic wave propagation from the earthquake source to the day surface and the computation of a composite pipeline element as an anisotropic object of complex shape. A grid-characteristic method on hexahedral and tetrahedral grids is used for the numerical computation.

Advanced high-density polyethylene used in pipelines networks

This paper presents the most important results obtained during tensile tests carried out on high-density polyethylene (HDPE) for pipelines used for water supply networks. Various specimens have been cut from HDPE 20 x 2 mm, 63 x 4 mm and 90 x 6 mm pipelines and subjected to tensile and four-point bending loads to determine their mechanical properties including stiffness and Young’s modulus. Load-extension distributions have also been determined. Two special cases of composite pipelines have been taken into consideration in theoretical approach: the cross-ply composite pipeline and the balanced angle-ply composite one, both subjected to internal pressure. In tensile tests, the stiffness evaluation of high-density polyethylene pipelines used for water supply networks put into evidence that the Young’s modulus and stiffness increase with the increase of pipelines’ diameter.

Numerical Analysis of Crack Failure of Reinforced Thermoplastic Pipe (RTP)

Composite pipeline can drastically reduce losses caused by corrosion that occurs in carbon steel pipes in the industry. Multiple numerical testing has been conducted to determine maximum stress and strain a Reinforced Thermoplastic Pipe (RTP) can withstand before hitting failure. Not many studies were done to find the maximum stress intensity a defected RTP can resist before failing. Objectives are to validate the numerical model for Reinforced Thermoplastic Pipeline (RTP) to industry standard and to analyze the maximum stress intensity of Reinforced Thermoplastic Pipes (RTP) can withstand with various size of defects under constant pressure and incremental internal pressure with constant crack defect. Results were, under constant internal pressure of 6 MPa, the pipe will fail with a defect length of 2.05mm and at constant design pressure of 10 MPa, the pipe will fail with a defect length of 0.3mm. At constant crack depth and width, crack tip propagation (failure) is more dependent on internal pressure rather than crack length. However, when comparing the severity of crack depth to internal pressure, crack depth is the major cause of failure.

Development of Non-Invasive Ultrasonic Measuring System for Monitoring Multiphase Flow in Liquid Media within Composite Pipeline

<span>Process of conveying liquid substance via the pipeline is the most common practice of transferring the liquid from one point to another point. Composite pipeline is becoming an option for liquid conveying purposed (instead of PVC, acrylic or metal) for its durability, longer lifetime and non-corrosive material in comparison with current pipeline. In order to ensure, the conveying process has a smooth flow rate without particle or bubble disturbance that could hinder good process flow, non-invasive monitoring system is always required. The ultrasonic measuring system is one of the monitoring options that could be applied. With proper designed for transmitting and conditioning circuitry, 300 kHz ultrasonic frequencies are found as the optimal frequency needed to penetrate across the composite pipeline with full of liquid. The ultrasonic sensor response is being successfully differentiated between full flow (no material blockage) and with bulk material blockage (dry and wet sand).</span>

Multi objective optimization of the vibration analysis of composite natural gas pipelines in nonlinear thermal and humidity environment under non-uniform magnetic field

The fluid-conveying pipe is a fundamental dynamical problem in the field of fluid– structure interactions. In recent years considerable attention has been given to the lateral vibrations of pipes containing by a moving fluid. In this paper, the vibration analysis of composite natural gas pipeline in the thermal and humidity environment is studied. The effect of the non-uniform magnetic field is investigated. By applying the Hamilton’s principle, the equation of motion is derived for the pipe with the effects of both linear and non-linear stress temperature cases. The differential quadrature method (DQM) has been utilized in computing the results for the pipe conveying fluid. The Bees algorithm and Genetic algorithm NSGA II for multi-objective optimization of a pipe model are used. Sample results are presented for several cases with varying values of the system parameter. Results are demonstrated for the dependence of natural frequencies on the flow velocity as well as temperature change and humidity percent. The influence of temperature change on the critical flow velocity at which buckling instability occurs is investigated. It is concluded that the effect of temperature change on the instability of conveyed fluid pipe is significant.

Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

The recent advent of DNA sequencing technologies facilitates the use of genome sequencing data that provide means for more informative and precise classification and identification of members of the Bacteria and Archaea. Because the current species definition is based on the comparison of genome sequences between type and other strains in a given species, building a genome database with correct taxonomic information is of paramount need to enhance our efforts in exploring prokaryotic diversity and discovering novel species as well as for routine identifications. Here we introduce an integrated database, called EzBioCloud, that holds the taxonomic hierarchy of the Bacteria and Archaea, which is represented by quality-controlled 16S rRNA gene and genome sequences. Whole-genome assemblies in the NCBI Assembly Database were screened for low quality and subjected to a composite identification bioinformatics pipeline that employs gene-based searches followed by the calculation of average nucleotide identity. As a result, the database is made of 61 700 species/phylotypes, including 13 132 with validly published names, and 62 362 whole-genome assemblies that were identified taxonomically at the genus, species and subspecies levels. Genomic properties, such as genome size and DNA G+C content, and the occurrence in human microbiome data were calculated for each genus or higher taxa. This united database of taxonomy, 16S rRNA gene and genome sequences, with accompanying bioinformatics tools, should accelerate genome-based classification and identification of members of the Bacteria and Archaea. The database and related search tools are available at www.ezbiocloud.net/.