Research Article
Research on Influencing Factors and Prediction of Drag Reducing Agent Effectiveness in Oil Pipeline Transportation
Issue:
Volume 10, Issue 2, April 2025
Pages:
17-30
Received:
27 February 2025
Accepted:
13 March 2025
Published:
21 March 2025
Abstract: This study is a comprehensive and in-depth investigation of the performance of drag-reducing agents (DRA) for pipeline oil products. Systematic experiments were conducted using a specially constructed indoor loop experimental device, using drag reduction rate as a metric. During the experimental process, variables such as DRA concentration and Reynolds number were precisely regulated to analyze the mechanism and influence law of these factors on the drag reduction rate. Based on a large amount of experimental data, a drag reduction rate prediction fitting formula is proposed that integrally considers relevant parameters such as drag-reducing agent concentration, Reynolds number, temperature, pipe diameter, and oil properties. The structure of the formula is designed to incorporate the mechanism and influencing factors of the DRA, and specific coefficients are introduced to express the relationship between the drag reduction rate and various aspects. Subsequently, the formula is fitted and validated using indoor experimental data and field data from actual crude oil pipeline transportation. The results show that the proposed fitting formula has high accuracy and reliability under different operating conditions. This formula and the accompanying validation method are expected to be effective tools for predicting drag reduction rates. This study provides a solid theoretical basis and strong technical support for the optimization of the additive amount of DRA in the crude oil pipeline transportation process and the precise regulation of transportation parameters, which is expected to be widely used and deeply promoted in the pipeline transportation link in the field of petroleum industry, and provides a reference example for the subsequent related research and technical improvement.
Abstract: This study is a comprehensive and in-depth investigation of the performance of drag-reducing agents (DRA) for pipeline oil products. Systematic experiments were conducted using a specially constructed indoor loop experimental device, using drag reduction rate as a metric. During the experimental process, variables such as DRA concentration and Reyn...
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Research Article
Analysis of Green Total Factor Energy Efficiency in OECD Countries Based on a Super-efficiency SBM-DEA Model
Chenyang Lee
,
Seiichi Ogata*
Issue:
Volume 10, Issue 2, April 2025
Pages:
31-45
Received:
6 December 2024
Accepted:
20 December 2024
Published:
14 April 2025
DOI:
10.11648/j.ijeee.20251002.12
Downloads:
Views:
Abstract: In the context of intensifying climate change and increasing resource constraints, addressing the dual challenges of economic growth and environmental sustainability has emerged as a critical global priority. Green Total Factor Energy Efficiency (GTFEE), an essential metric for evaluating the coordination between economic development, energy efficiency, and environmental protection, plays a pivotal role in optimizing resource allocation, fostering technological innovation, and supporting the pursuit of sustainable development. However, existing research has yet to provide a comprehensive and systematic analysis of GTFEE’s long-term trends and its underlying driving mechanisms. This study addresses this gap by focusing on OECD (Organization for Economic Co-operation and Development) countries, employing the super-efficient SBM-DEA model with non-expected outputs to evaluate GTFEE from 1995 to 2021 systematically. The analysis delves into the spatial and temporal characteristics of GTFEE and its dynamic evolution patterns. The findings reveal a sustained upward trajectory in GTFEE across OECD countries, with the average score rising from 0.7814 in 1995 to 0.8894 in 2021. Nonetheless, substantial heterogeneity persists in GTFEE levels among regions and countries. Further, using quantile random forest regression analysis, the study identifies critical determinants of GTFEE, including economic development levels, energy intensity, technological innovation capacity, industrial structure optimization, fiscal revenue, and urbanization. These results not only elucidate the driving mechanisms of GTFEE but also offer a robust theoretical foundation and actionable policy insights for advancing green energy transitions and achieving sustainable development goals. A comprehensive and integrated assessment of Green Total Factor Energy Efficiency (GTFEE) in OECD countries is crucial for advancing sustainable development. This study systematically measures GTFEE in OECD countries over the period 1995-2021, utilizing the super-efficient SBM-DEA model with an undesired output. It further analyzes the spatial and temporal distribution characteristics and dynamic evolution of GTFEE. The results indicate that, overall, GTFEE in OECD countries exhibits an upward trend throughout the study period, with the average value increasing from 0.7814 in 1995 to 0.8894 in 2021, reflecting improvements in green total factor energy efficiency. However, substantial disparities in GTFEE levels are observed across countries, suggesting varied rates of progress and effectiveness in promoting green transitions and enhancing energy efficiency. Through quantile random forest regression analysis, the study identifies key determinants influencing GTFEE, including the level of economic development (as measured by GNI per capita), energy intensity (primary energy consumption), technological innovation capacity, industrial structure optimization, fiscal revenue, and urbanization.
Abstract: In the context of intensifying climate change and increasing resource constraints, addressing the dual challenges of economic growth and environmental sustainability has emerged as a critical global priority. Green Total Factor Energy Efficiency (GTFEE), an essential metric for evaluating the coordination between economic development, energy effici...
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