Single Pipeline Research Articles

Stress Analysis of Pipe-In-Pipe Systems under Free Span for Deep Water Pipeline Applications

This study examined the phenomena of free span for a pipe -in- pipe (PIP) system for pipeline application. Two different span length of 8 and 30 meters are modelled and simulated using nonlinear stress analysis. The effect of pressure, temperature and gravity on the PIP system are determined and compared with conventional single pipeline. From the results obtained, it is clear that the finite element analysis (FEA) results correlated very well with those calculated using analytical methods. Percentage differences were generally less than 10%, with some discrepancies which were due to assumption of thin-walled theory which assumes a radial stress equals to zero, whereas the FEA calculates a non- zero radial stress. The key finding in this study demonstrated the strong potentials of PIP system in terms of structural reliability for deepwater pipeline application. Specifically, the 30m single pipe in free span (with pressure and temperature) deflected 205.1mm, more than double the corresponding PIP. This knowledge can be beneficial to selection and design considerations for pipeline system responses to both the gravity, thermal and pressure loading as well as the potential failure modes that may results in a typical scenario. Various theoretical calculations of stresses are used to validate the finding in this study of the single pipe and PIP models for flat seabed and free span.

Connecting genomic islands across prokaryotic and phage genomes via protein families

Prokaryotic genomes evolve via horizontal gene transfer (HGT), mutations, and rearrangements. A noteworthy part of the HGT process is facilitated by genomic islands (GIs). While previous computational biology research has focused on developing tools to detect GIs in prokaryotic genomes, there has been little research investigating GI patterns and biological connections across species. We have pursued the novel idea of connecting GIs across prokaryotic and phage genomes via patterns of protein families. Such patterns are sequences of protein families frequently present in the genomes of multiple species. We combined the large data set from the IslandViewer4 database with protein families from Pfam while implementing a comprehensive strategy to identify patterns making use of HMMER, BLAST, and MUSCLE. we also implemented Python programs that link the analysis into a single pipeline. Research results demonstrated that related GIs often exist in species that are evolutionarily unrelated and in multiple bacterial phyla. Analysis of the discovered patterns led to the identification of biological connections among prokaryotes and phages. These connections suggest broad HGT connections across the bacterial kingdom and its associated phages. The discovered patterns and connections could provide the basis for additional analysis on HGT breadth and the patterns in pathogenic GIs.

AdmixPipe v3: facilitating population structure delimitation from SNP data.

Quantifying genetic clusters (=populations) from genotypic data is a fundamental, but non-trivial task for population geneticists that is compounded by: hierarchical population structure, diverse analytical methods, and complex software dependencies. AdmixPipe v3 ameliorates many of these issues in a single bioinformatic pipeline that facilitates all facets of population structure analysis by integrating outputs generated by several popular packages (i.e. CLUMPAK, EvalAdmix). The pipeline interfaces disparate software packages to parse Admixture outputs and conduct EvalAdmix analyses in the context of multimodal population structure results identified by CLUMPAK. We further streamline these tasks by packaging AdmixPipe v3 within a Docker container to create a standardized analytical environment that allows for complex analyses to be replicated by different researchers. This also grants operating system flexibility and mitigates complex software dependencies. Source code, documentation, example files, and usage examples are freely available at https://github.com/stevemussmann/admixturePipeline. Installation is facilitated via Docker container available from https://hub.docker.com/r/mussmann/admixpipe. Usage under Windows operating systems requires the Windows Subsystem for Linux.

A cloud-based pipeline for analysis of FHIR and long-read data.

As genome sequencing becomes cheaper and more accurate, it is becoming increasingly viable to merge this data with electronic health information to inform clinical decisions. In this work, we demonstrate a full pipeline for working with both PacBio sequencing data and clinical FHIR® data, from initial data to tertiary analysis. The electronic health records are stored in FHIR® (Fast Healthcare Interoperability Resource) format, the current leading standard for healthcare data exchange. For the genomic data, we perform variant calling on long-read PacBio HiFi data using Cromwell on Azure. Both data formats are parsed, processed and merged in a single scalable pipeline which securely performs tertiary analyses using cloud-based Jupyter notebooks. We include three example applications: exporting patient information to a database, clustering patients and performing a simple pharmacogenomic study. https://github.com/microsoft/genomicsnotebook/tree/main/fhirgenomics. Supplementary data are available at Bioinformatics Advances online.

Automated identification of blastocyst regions at different development stages

The selection of the best single blastocyst for transfer is typically based on the assessment of the morphological characteristics of the zona pellucida (ZP), trophectoderm (TE), blastocoel (BC), and inner cell-mass (ICM), using subjective and observer-dependent grading protocols. We propose the first automatic method for segmenting all morphological structures during the different developmental stages of the blastocyst (i.e., expansion, hatching, and hatched). Our database contains 592 original raw images that were augmented to 2132 for training and 55 for validation. The mean Dice similarity coefficient (DSC) was 0.87 for all pixels, and for the BC, BG (background), ICM, TE, and ZP was 0.85, 0.96, 0.54, 0.63, and 0.71, respectively. Additionally, we tested our method against a public repository of 249 images resulting in accuracies of 0.96 and 0.93 and DSC of 0.67 and 0.67 for ICM and TE, respectively. A sensitivity analysis demonstrated that our method is robust, especially for the BC, BG, TE, and ZP. It is concluded that our approach can automatically segment blastocysts from different laboratory settings and developmental phases of the blastocysts, all within a single pipeline. This approach could increase the knowledge base for embryo selection.

Causes and treatment of adhesive damage in polymer flooding injection pipeline

The viscosity of polymer liquid is an important parameter used in oilfield. Understanding the loss rule and regularity of polymer liquid will help to improve the distribution and water injection quality of polymer liquid and ensure the effective distribution of polymer liquid. According to the oil-water viscosity data of the previous polymer flooding fluid, it is found that the oil-water viscosity is within the range of 5%-20%, with an average of 9.8%. The reasons of single well pipeline viscosity are complex and varied, which are closely related to reducing substances, types and quantities of bacteria, fouling oil suspensions on the inner wall of pipeline, pipeline length and running time. Therefore, from the aspects of Fe2+, pipeline running time and so on, the influence factors and prevention methods of single well pipeline viscosity loss were studied, and the corresponding treatment measures were worked out, and good results were obtained.

Numerical Investigations on Scour and Flow around Two Crossing Pipelines on a Sandy Seabed

When a pipeline is laid on the seabed, local scour often occurs below it due to sea currents. In practical engineering, there are some cases that two pipelines laid on the seabed need to cross with each other. The complex flow structures around two crossing pipelines make the scour characteristics different from that of an isolated single pipeline. In this study, scour below two crossing pipelines was simulated numerically using the CFD software Flow-3D. The study is focused on the effect of the intersecting angle on the equilibrium depth and time scale of scour below the crossing position. Five intersecting angles, i.e., α = 0°, 15°, 30°, 45° and 90°, are considered, where α = 0° and 90° represent two pipelines parallel and perpendicular to each other, respectively. The results show that the equilibrium depth and the time scale of scour below the two crossing pipelines are greater than those of an isolated single pipeline. The equilibrium depth and time scale of scour have the largest values at α = 0° and decrease with the increase of the intersecting angle. Finally, the flow structures around the crossing pipelines are presented to explain the scour process.

Flow characteristics and pattern transition of different pipe diameters in pneumatic conveying for gasifier

The scale of dry pulverized coal gasifier is restricted by the conveying capacity of single pipeline. In this paper, the flow characteristics of pulverized coal at different pipe diameters and operation parameters under high pressure are simulated to indicate flow stability and ultimate pipe diameter. Firstly, the numerical model is established and verified by the industrial data. The influences of conveying velocities and densities on the particle behavior are investigated to explore the flow regime and conveying stability. The flow characteristics and pattern transition regulation are discussed at different pipe diameters. The evolution mechanism of pressure drops in different straight pipes are analyzed. Also, the ultimate pipe diameter of gasifier is revealed at industrial operating parameters.

Segmentation and classification of ovarian cancer based on conditional adversarial image to image translation approach

AbstractMedical image analysis and disease diagnosis have significantly improved with the use of AI and Machine Learning algorithms. Automated systems for medical image analysis will help the doctors and radiologists understand the anomaly in a short span of time and with better visualization. Such automated systems will help to reduce the time taken for diagnosis by experts. Recently, Computer Vision is industrialized with the advancements in algorithms and hardware. The proposed study aims to develop a computer vision solution for automatic segmentation and classification of ovarian tumours in discriminating between benign and malignant tumours by image‐to‐image translation approach using Conditional Generative Adversarial Network (cGAN). Our method uses a novel algorithm which segments and classifies the images in a single pipeline which makes the algorithm unique and useful. This research also aims to compare its diagnostic accuracy with that of an expert radiologist. The dataset used by in the present study is formulated with images obtained from a hospital and annotated by doctors from the hospital. The obtained results show the proposed study is promising for ovarian cancer segmentation and classification with an average segmentation score of 0.825 for benign and 0.765 for malignant and classification accuracy of 83% for benign and 79% for malignant, precision score of 85% for benign and 80% for malignant and F1 score of 81% for benign and 80.1% for malignant images. The proposed methodology is evaluated on the existing MRI images to perform segmentation and classification. The results obtained shows that the proposed methodology can perform well on other MRI images. In this study, proposed methodology is convenient as separate segmentation need not be done and is giving good result. The same MRI images are segmented using UNet and classified using RESNET 101 and results are compared with the proposed methodology.

Unified Legal Party Based Sentiment Analysis Pipeline

The rapid growth of text corpora across various domains has emerged a need and an opportunity to leverage Nat- ural Language Processing to automate and efficiently streamline tedious manual tasks. Legal domain is one such text rich domain which suffers a rapid growth of text corpora and requirement for natural language processing applications. In the pursuit of automating the prediction of the winning party of a court case among other usages, analysing sentiment in a party wise manner is beneficial for legal professionals. The two main sub-tasks in this process is to identify parties in a court case and afterwards analysing the respective sentiment towards each party. In this study we discuss the unification of two such models capable of doing the two task into a single pipeline to perform party based sentiment analysis efficiently

Extensive Recombination-driven Coronavirus Diversification Expands the Pool of Potential Pandemic Pathogens.

The ongoing SARS-CoV-2 pandemic is the third zoonotic coronavirus identified in the last 20 years. Enzootic and epizootic coronaviruses of diverse lineages also pose a significant threat to livestock, as most recently observed for virulent strains of porcine epidemic diarrhea virus (PEDV) and swine acute diarrhea-associated coronavirus (SADS-CoV). Unique to RNA viruses, coronaviruses encode a proofreading exonuclease (ExoN) that lowers point mutation rates to increase the viability of large RNA virus genomes, which comes with the cost of limiting virus adaptation via point mutation. This limitation can be overcome by high rates of recombination that facilitate rapid increases in genetic diversification. To compare the dynamics of recombination between related sequences, we developed an open-source computational workflow (IDPlot) that bundles nucleotide identity, recombination, and phylogenetic analysis into a single pipeline. We analyzed recombination dynamics among three groups of coronaviruses with noteworthy impacts on human health and agriculture: SARSr-CoV, Betacoronavirus-1, and SADSr-CoV. We found that all three groups undergo recombination with highly diverged viruses from undersampled or unsampled lineages, including in typically highly conserved regions of the genome. In several cases, no parental origin of recombinant regions could be found in genetic databases, demonstrating our shallow characterization of coronavirus diversity and expanding the genetic pool that may contribute to future zoonotic events. Our results also illustrate the limitations of current sampling approaches for anticipating zoonotic threats to human and animal health.

Efficient Pipe Burst Detection in Tree‐Shape Water Distribution Networks Using Forward‐Backward Transient Analysis

AbstractTransient‐based leak/burst detection has received more and more attentions in the operation and management of water distribution networks. However, with the increase in pipe network complexity, it is hard to detect and locate the potential pipe defects and water losses efficiently. Recently, we proposed an efficient leak/burst localization strategy in single pipelines based on the forward and backward transient analysis, and in this work, this effective approach is customized for the more realistic branched (tree‐shaped) pipe networks. Unlike traditional transient‐based methods which rely on tedious optimization procedures, the proposed method uses a mismatch property between forward and backward analyses of transient signals for the pipe burst detection during the water supply process. Compared with other developed methods, this method can directly calculate the defect location, so it is expected to have high efficiency and wide applicability. To fulfill this goal, a framework for burst detection in a tree‐shaped pipe network is developed in this paper. Using the mass conservation and energy relations at the branched junctions, the forward and backward transient analysis is extended from one pipe to another until the burst is found and then located in the network. Both experimental and numerical tests show the effectiveness of the proposed method, and further analysis has shown that the method is also valid for leak detection in both transient and steady conditions, confirming the robustness and practicality of this proposed method. At last, this paper discusses the influence of transient sources and the potential combination of the method with other methods.

An Implicit Formulation for Calculating Final Conditions in Drainage Maneuvers in Pressurized Water Installations

Emptying processes are typical maneuvers that should be performed by water distribution companies for operation purposes. These processes involve a complex numerical analysis, since a set of algebraic and ordinary differential equations needs to be solved for the intricacy of hydraulic and thermodynamic formulations for two analyzed phases (liquid and gas). This research provides an implicit equation to compute exactly the final conditions in water emptying operations in single pipelines without an air valve (or admitted air). The implicit expression was developed by considering that for all final conditions, the water velocity is null, and thus, the water column length and air pocket pressure can be computed. The friction factor, internal pipe diameter, and opening maneuvers of drain valves do not disturb the final conditions in draining processes. The developed implicit formulation was validated using experimental measurements in a pipeline with a total length of 4.36 m. The equation is of utmost importance, since it can be utilized for engineers to easily plan for future conditions in water distribution networks.

Lessons learned from automated screening of COVID-19 preprints

Abstract Preprints occupied the spotlight early in the pandemic, as scientists, the media and the public sought information on the evolving pandemic. While some in the scientific community embraced this shift, others were concerned about the quality of these papers, which had not yet undergone peer review. Furthermore, the flood of COVID-19 preprints quickly overwhelmed the scientific community's ability to monitor and assess new preprints. Automated screening tools that detect beneficial practices, or common problems, in preprints are one potential solution to this problem. These tools could potentially provide individualized feedback, allowing authors to improve their manuscripts prior to publication in a peer-reviewed journal. We have combined many tools into a single pipeline, called ScreenIT. ScreenIT assess factors such as open data and open code, blinding, randomization, power calculations, limitations sections, and data visualization problems. Since June 2020, we have used ScreenIT to screen and post daily reports on more than 23,000 new COVID-19 preprints deposited on bioRxiv and medRxiv. Results show that practices such as sharing data and code are relatively uncommon. Sample size calculations, blinding and randomization are rarely reported and most papers do not report the sex of participants, animals or samples. This work demonstrates the feasibility of using automated tools to rapidly screen many preprints in real time, and provide authors and readers with rapid feedback. However, this approach has important limitations. Automated screening tools can make mistakes. Tools can't always determine whether an item is relevant to a particular manuscript. Further studies are needed to determine whether feedback from automated tools is effective in encouraging authors to improve reporting.

An adaptive space-step simulation approach for steam heating network considering condensate loss

Steam heating plays an irreplaceable role in industrial productions and occupies a specific proportion of the total heating load. High-precision and efficient simulation is of substantial significance to the economical operation, safety and reliability and energy utilization efficiency of the steam heating network. Widely applicable and adequately accurate simulation approach for the steam heating network is in necessity. A novel adaptive space-step simulation approach for steam heating network considering the condensate loss is developed in this paper. The model equations are precisely derived from the primitive differential equations based on the trapezoidal formula and reorganized into the matrix form for computation acceleration. Meanwhile, a quasi-linear fitting method is proposed to simplify the calculation of steam enthalpy. To solve the model, the computation process is decoupled as hydraulic calculation and thermal calculation, and the converge is achieved through alternating iterative algorithm. The condensate check is introduced after the thermal calculation, in which the condensate loss can be calculated. To acquire the expected simulation precision, an adaptive space-step determination method is developed, in which minimum number of nodes are automatically added to divide long pipes into shorter segments. Finally, case study is conducted on single pipeline cases and a 20-node network. Results show that the proposed approach is applicable to networks containing superheated and saturated steam simultaneously. The error can be controlled to the initially set precision of 0.1 kPa and 0.1 °C through space-step adaption, and nodes are mostly added near the transition point from superheated steam to saturated steam for precision need.

Numerical analysis of seabed liquefaction in the vicinity of two tandem pipelines in a trench

In engineering practice, pipeline trenching has been adopted as one of effective protection options. Most previous studies mainly focused on the prediction of the seabed response around a single pipeline, although two tandem pipelines have been used in engineering practice for transporting hydrocarbons. This study aimed to investigate the wave–current induced liquefaction around two tandem pipes in a trench. A series of simulations were performed to explore the effect of the horizontal gap ratio of dual pipes in a shared trench on the seabed response, and the results were compared with a single trenched pipe. In the numerical model, we used an integrated two-dimensional model that was developed based on the Finite Volume Method (FVM) in OpenFOAM®. In terms of the flow field, VARANS (Volume-Averaged Reynolds Averaged Navier–Stokes) was applied to simulate the fluid motion, while Biot’s consolidation equation was used to govern the seabed model. The numerical examples indicate that twin pipelines semi-buried in close proximity within the same trench significantly impact the flow patterns and seabed response around them. Furthermore, the self-weight of dual pipes, ocean currents and trench configuration have a considerable influence on the evaluation of the liquefaction distribution around two tandem pipelines in a trench.

A Comparative Study of RNA-Seq Aligners Reveals Novoalign’s Default Setting as an Optimal Setting for the Alignment of HeLa RNA-Seq Reads

The introduction of RNA-sequencing (RNA-Seq) technology into biological research has encouraged bioinformatics developers to build various analysis pipelines. The chosen bioinformatics pipeline mostly depends on the research goals and organisms of interest because a single pipeline may not be optimal for all cases. As the first step in most pipelines, alignment has become a crucial step that will affect the downstream analysis. Each alignment tool has its default and parameter settings to maximise the output. However, this poses great challenges for the researchers as they need to determine the alignment tool most compatible with the correct settings to analyse their samples accurately and efficiently. Therefore, in this study, the duplication of real data of the HeLa RNA-seq was used to evaluate the effects of data qualities on four commonly used RNA-Seq tools: HISAT2, Novoalign, TopHat and Subread. Furthermore, these data were also used to evaluate the optimal settings of each aligner for our sample. These tools’ performances, precision, recall, F-measure, false discovery rate, error tolerance, parameter stability, runtime and memory requirements were measured. Our results showed significant differences between the settings of each alignment tool tested. Subread and TopHat exhibited the best performance when using optimised parameters setting. In contrast, the most reliable performance was observed for HISAT2 and Novoalign when the default setting was used. Although HISAT2 was the fastest alignment tool, the highest accuracy was achieved using Novoalign with the default setting.

Hybrid graph convolution neural network and branch-and-bound optimization for traffic flow forecasting

In this study, we combine graph optimization and prediction in a single pipeline to investigate an innovative convolutional graph-based neural network for urban traffic flow prediction in an edge IoT environment. Pre-processing of the linked graph is first performed to remove noise from the set of original road networks of urban traffic data. Outlier detection strategy is used to efficiently explore the road network and remove irrelevant patterns and noise. The resulting graph is then implemented to train an extended graph convolutional neural network to estimate the traffic flow in the city. To accurately tune the hyperparameter values of the proposed framework, a new optimization technique is developed based on branch and bound. For comparison, an intensive evaluation is conducted with multiple datasets and baseline methods. The results show that the proposed framework outperforms the baseline solutions, especially when the number of nodes in the graph is large.

Dynamic modeling and characteristic analysis of natural gas network with hydrogen injections

With the transformation of energy structure, the proportion of renewable energy in the power grid continues to increase. However, the power grid's capacity to absorb renewable is limited. In view of this, converting the excess renewable energy into hydrogen and injecting it into natural gas network for transportation can not only increase the absorption capacity of renewable energy but also reduce the transportation cost of hydrogen. While this can lead to the problem that hydrogen injection will make the dynamic characteristics of the pipeline more complicated, and hydrogen embrittlement of pipeline may occur. It is of great significance to simulate the dynamic characteristics of gas pipeline with hydrogen injection, especially the hydrogen mixture ratio. In this paper, the cell segmentation method is used to solve each natural gas pipeline model, the gas components are recalculated in each cell and the parameters of partial differential equation are updated. Additionally, the dynamic simulation model of natural gas network with hydrogen injections is established. Simulation results show that for a single pipeline, when the inlet hydrogen ratio changes, whether or not hydrogen injection has little influence on the pressure and flow. The propagation speed of hydrogen concentration is far less than that of the pressure and flow rate, and it takes about 1.2 × 105 s for the 100 km pipeline hydrogen ratio to reach the steady state again.

Numerical modeling of combined wave and current-induced residual liquefaction around twin pipelines

With the operation of offshore oil & gas fields, offshore pipeline has been widely used in offshore engineering. So far, most studies have focused on exploring the seabed responses around a single pipeline, and ignored the effect of multiple pipelines on the physical process of the surrounding seabed. In this study, to investigate the residual seabed dynamic response around twin pipelines, a two-dimensional numerical model, combining the Shear-Stress Transport (SST) turbulence model with the porous seabed model, is developed. Unlike previous studies, this study focuses on three aspects: (1) the physical process of seabed around twin pipelines; (2) the wave and current-induced residual soil response; and (3) the effect of upstream pipeline on the liquefaction of downstream pipeline. Numerical results demonstrate the significant effect of current and twin pipelines’ arrangement on the residual pore pressure and liquefaction zone around the twin pipelines. Results show that the pressure fluctuation caused by the vortex between the twin pipelines deepens the residual liquefaction depth of the seabed.