• Title/Summary/Keyword: Pipelines

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An Experimental Study of Pressure Variation in Pipe Flow according to Residual Air Condition (잔류공기조건에 따른 관 내 유동의 압력변화에 관한 실험적 연구)

  • Park, Jaegon;Lee, Kyungsu;Ko, Joo Suk;Lyu, Siwan
    • Journal of the Korean Society of Safety
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    • v.37 no.4
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    • pp.113-119
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    • 2022
  • Sudden intrusion of a large amount of surface water into a flood defensive tunnel or pipeline system can compress the residual air. The compressed air may explode along with water through the inlet or air vent, resulting in hydraulic capacity degradation or safety hazards. This study aims to investigate the behavior of compressed air body in pipelines according to the residual air condition with a series of laboratory experiments measuring pressure variation. It has been found that flow characteristics and residual air conditions have a dominant influence on the magnitude and periodicity of the pressure variation. A proper measure to effectively control the residual air is required for securing the design capacity of flood defensive pipeline systems, since the peak pressure is predominantly affected by residual air conditions.

Application of nanoparticles in extending the life of oil and gas transmission pipeline

  • Yunye, Liu;Hai, Zhu;Jianfeng, Niu
    • Structural Engineering and Mechanics
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    • v.84 no.6
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    • pp.733-741
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    • 2022
  • The amount of natural gas that is used on a worldwide scale is continuously going up. Natural gas and acidic components, such as hydrogen sulfide and carbon dioxide, cause significant corrosion damage to transmission lines and equipment in various quantities. One of the fundamental processes in natural gas processing is the separation of acid gases, among which the safety and environmental needs due to the high toxicity of hydrogen sulfide and also to prevent wear and corrosion of pipelines and gas transmission and distribution equipment, the necessity of sulfide separation Hydrogen is more essential than carbon dioxide and other compounds. Given this problem's significance, this endeavor aims to extend the lifespan of the transmission lines' pipes for gas and oil. Zinc oxide nanoparticles made from the environmentally friendly source of Allium scabriscapum have been employed to accomplish this crucial purpose. This is a simple, safe and cheap synthesis method compared to other methods, especially chemical methods. The formation of zinc oxide nanoparticles was shown by forming an absorption peak at a wavelength of about 355 nm using a spectrophotometric device and an X-ray diffraction pattern. The size and morphology of synthesized nanoparticles were determined by scanning and transmission electron microscope, and the range of size changes of nanoparticles was determined by dynamic light scattering device.

SIMULATED ANNEALING FOR LINEAR SCHEDULING PROJECTS WITH MULTIPLE RESOURCE CONSTRAINTS

  • C.I. Yen
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.530-539
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    • 2007
  • Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.

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Current status of whole-genome sequences of Korean angiosperms

  • Jongsun PARK;Yunho YUN;Hong XI;Woochan KWON;Janghyuk SON
    • Korean Journal of Plant Taxonomy
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    • v.53 no.3
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    • pp.181-200
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    • 2023
  • Owing to the rapid development of sequencing technologies, more than 1,000 plant genomes have been sequenced and released. Among them, 69 Korean plant taxa (85 genome sequences) contain at least one whole-genome sequence despite the fact that some samples were not collected in Korea. The sequencing-by-synthesis method (next-generation sequencing) and the PacBio (third-generation sequencing) method were the most commonly used in studies appearing in 65 publications. Several scaffolding methods, such as the Hi-C and 10x types, have also been used for pseudo-chromosomal assembly. The most abundant families among the 69 taxa are Rosaceae (10 taxa), Brassicaceae (7 taxa), Fabaceae (7 taxa), and Poaceae (7 taxa). Due to the rapid release of plant genomes, it is necessary to assemble the current understanding of Korean plant species not only to understand their whole genomes as our own plant resources but also to establish new tools for utilizing plant resources efficiently with various analysis pipelines, including AI-based engines.

Distributed In-Memory Caching Method for ML Workload in Kubernetes (쿠버네티스에서 ML 워크로드를 위한 분산 인-메모리 캐싱 방법)

  • Dong-Hyeon Youn;Seokil Song
    • Journal of Platform Technology
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    • v.11 no.4
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    • pp.71-79
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    • 2023
  • In this paper, we analyze the characteristics of machine learning workloads and, based on them, propose a distributed in-memory caching technique to improve the performance of machine learning workloads. The core of machine learning workload is model training, and model training is a computationally intensive task. Performing machine learning workloads in a Kubernetes-based cloud environment in which the computing framework and storage are separated can effectively allocate resources, but delays can occur because IO must be performed through network communication. In this paper, we propose a distributed in-memory caching technique to improve the performance of machine learning workloads performed in such an environment. In particular, we propose a new method of precaching data required for machine learning workloads into the distributed in-memory cache by considering Kubflow pipelines, a Kubernetes-based machine learning pipeline management tool.

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A Branch Prediction Mechanism With Adaptive Branch History Length for FAFF Information Processing (농림수산식품분야 정보처리를 위한 적응하는 분기히스토리 길이를 갖는 분기예측 메커니즘)

  • Ko, K.H.;Cho, Y.I.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.13 no.1
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    • pp.3-17
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    • 2011
  • Pipelines of processor have been growing deeper and issue widths wider over the years. If this trend continues, branch misprediction penalty will become very high. Branch misprediction is the single most significant performance limiter for improving processor performance using deeper pipelining. Therefore, more accurate branch predictor becomes an essential part of modem processors for FAFF(Food, Agriculture, Forestry, Fisheries)Information Processing. In this paper, we propose a branch prediction mechanism, using variable length history, which predicts using a bank having higher prediction accuracy among predictions from five banks. Bank 0 is a bimodal predictor which is indexed with the 12 least significant bits of the branch PC. Banks 1,2,3 and 4 are predictors which are indexed with different global history bits and the branch PC. In simulation results, the proposed mechanism outperforms gshare predictors using fixed history length of 12 and 13, up to 6.34% in prediction accuracy. Furthermore, the proposed mechanism outperforms gshare predictors using best history lengths for benchmarks, up to 2.3% in prediction accuracy.

Thermal-hydraulic 0D/3D coupling in OpenFOAM: Validation and application in nuclear installations

  • Santiago F. Corzo ;Dario M. Godino ;Alirio J. Sarache Pina;Norberto M. Nigro ;Damian E. Ramajo
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1911-1923
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    • 2023
  • The nuclear safety assessment involving large transient simulations is forcing the community to develop methods for coupling thermal-hydraulics and neutronic codes and three-dimensional (3D) Computational Fluid Dynamics (CFD) codes. In this paper a set of dynamic boundary conditions are implemented in OpenFOAM in order to apply zero-dimensional (0D) approaches coupling with 3D thermal-hydraulic simulation in a single framework. This boundary conditions are applied to model pipelines, tanks, pumps, and heat exchangers. On a first stage, four tests are perform in order to assess the implementations. The results are compared with experimental data, full 3D CFD, and system code simulations, finding a general good agreement. The semi-implicit implementation nature of these boundary conditions has shown robustness and accuracy for large time steps. Finally, an application case, consisting of a simplified open pool with a cooling external circuit is solved to remark the capability of the tool to simulate thermal hydraulic systems commonly found in nuclear installations.

'Mind the Mocking and don't Keep on Walking': Galaxy Mock Challenges for the Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey

  • Moon, Jeongin;Choi, Peter D.;Rossi, Graziano
    • The Bulletin of The Korean Astronomical Society
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    • v.45 no.1
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    • pp.68.3-69
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    • 2020
  • We develop a series of N-body data challenges, functional to the final analysis of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) galaxy sample, primarily based on high-fidelity catalogs constructed from the Outer Rim simulation. We generate synthetic galaxy mocks by populating Outer Rim halos with a variety of halo occupation distribution (HOD) schemes of increasing complexity, spanning different redshift intervals. We then assess the performance of three complementary redshift space distortion (RSD) models in configuration and Fourier space, adopted for the analysis of the complete DR16 eBOSS sample of Luminous Red Galaxies (LRGs). We find that all the methods are mutually consistent, with comparable systematic errors on the Alcock-Paczynski parameters and the growth of structure, and robust to different HOD prescriptions - thus validating the robustness of the models and the pipelines used for the baryon acoustic oscillation (BAO) and full shape clustering analysis. Our study is relevant for the final eBOSS DR16 'consensus cosmology', as the systematic error budget is informed by testing the results of analyses against these high-resolution mocks. In addition, it is also useful for future large-volume surveys, since similar mock-making techniques and systematic corrections can be readily extended to model for instance the DESI galaxy sample.

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Health monitoring of pressurized pipelines by finite element method using meta-heuristic algorithms along with error sensitivity assessment

  • Amirmohammad Jahan;Mahdi Mollazadeh;Abolfazl Akbarpour;Mohsen Khatibinia
    • Structural Engineering and Mechanics
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    • v.87 no.3
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    • pp.211-219
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    • 2023
  • The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

SUSTAINABILITY SOLUTIONS USING TRENCHLESS TECHNOLOGIES IN URBAN UNDERGROUND INFRASTRUCTURE DEVELOPMENT

  • Dae-Hyun (Dan) Koo;Samuel Ariaratnam
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.367-374
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    • 2013
  • Underground infrastructure systems provide essential public services and goods through buried structures including water and sewer, gas and petroleum, power and communication pipelines. The majority of existing underground infrastructure systems was installed in green field areas prior to development of complex urban built environments. Currently, there is a global trend to escalate major demand for underground infrastructure system renewal and new installation while minimizing disruption and maintaining functions of existing superstructures. Therefore, Engineers and utility owners are rigorously seeking technologies that minimize environmental, social, and economic impact during the renewal and installation process. Trenchless technologies have proven to be socially less disruptive, more environmentally friendly, energy conservative and economically viable alternative methods. All of those benefits are adequate to enhance overall sustainability. This paper describes effective sustainable solutions using trenchless technologies. Sustainability is assessed by a comparison between conventional open cut and trenchless technology methods. Sustainability analysis is based on a broad perspective combining the three main aspects of sustainability: economic; environmental; and social. Economic includes construction cost, benefit, and social cost analysis. Environmental includes emission estimation and environmental quality impact study. Social includes various social impacts on an urban area. This paper summarizes sustainable trenchless technology solutions and presents a sustainable construction method selection process in a proposed framework to be used in urban underground infrastructure capital improvement projects.

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