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Article
Geosciences, Multidisciplinary
Tathiana Rodrigues Caetano et al.
Summary: This study demonstrates the effectiveness of Ground Penetrating Radar (GPR) and Electrical Resistivity (ERT) methods in detecting water leakage from a specific large unpressurized pipeline. These methods can indicate soil zones related to water losses and their accuracy depends on environmental factors and the time of the leaking opening. The application of geophysical technologies in water resource management can help address losses in the water supply system.
JOURNAL OF APPLIED GEOPHYSICS
(2023)
Article
Energy & Fuels
Mahmood Farzaneh-Gord et al.
Summary: This study presents a thermodynamic evaluation of using a Reciprocating Expansion Engine (REE) to recover pressure exergy in the Natural Gas (NG) distribution network. The GERG-2008 equation of state (EOS) and the Try & Error method, as well as an Artificial Neural Network (ANN) method, are used to simulate the REE and evaluate its performance. The results show that the NG composition has a significant impact on the REE performance.
PETROLEUM SCIENCE AND TECHNOLOGY
(2023)
Article
Energy & Fuels
Bingyuan Hong et al.
Summary: Failure and leakage of natural gas pipelines can lead to serious ecological losses and casualties. This paper proposes a dynamic risk probability analysis method based on Dynamic Bayesian network (DBN), which is validated by a third-party damage case under uncertainty.
Article
Energy & Fuels
Kangyin Dong et al.
Summary: Liquefied natural gas (LNG) point supply is a flexible and convenient method advocated by China for distributing energy to towns and villages where gas pipelines are difficult or uneconomical to construct. This study designs an optimization model for LNG point supply in China using mixed-integer linear programming, aiming to minimize economic and environmental costs in construction and operation stages. By considering parameters such as location-allocation, gas storage and vaporization capacity, equipment selection, and pipeline distribution, the model successfully meets the fluctuating seasonal demand for natural gas. Sensitivity analysis shows that construction cost is highly sensitive.
Review
Engineering, Environmental
Ting-Wei Wu et al.
Summary: This review examines the applications of convolutional neural networks (CNNs) in intelligent waste identification and recycling (IWIR). It provides an introduction to CNNs, outlines the use of open-source datasets and advanced CNN models in IWIR, and summarizes the applications in recyclable material identification, trash pollution detection, and solid waste classification. The challenges and limitations of current applications are discussed, along with the future prospects of CNNs in this field.
RESOURCES CONSERVATION AND RECYCLING
(2023)
Article
Energy & Fuels
Huaxing Lin et al.
Summary: This study explores the carbon peak statuses and trends of cities in less-developed western China, finding that these cities can be divided into different types and discussing the unbalanced and asynchronous characteristics in achieving carbon peaks.
Article
Geography
Amber Marshall et al.
Summary: This cross-disciplinary study examines how rural individuals and organizations in Australia can effectively prepare for, respond to, and recover from natural disasters using telecommunications. The study highlights the social factors of disaster resilience facilitated by digital technologies, in contrast to the dominant focus on technical infrastructure and capability in the literature. The research findings are particularly important as rural Australia and other parts of the world experience more frequent and severe natural disasters.
JOURNAL OF RURAL STUDIES
(2023)
Review
Computer Science, Interdisciplinary Applications
Zhuochao Li et al.
Summary: The pipeline is an important carrier in the petroleum industry, but its development is hindered by low efficiency, high cost, and high decision risk. However, with the help of machine learning and advanced sensors, new technological breakthroughs are being made to develop intelligent pipeline systems. This paper focuses on the full life cycle of a pipeline and reviews the theoretical research and key technologies in each stage, emphasizing the importance of full digital construction and operation, as well as the critical role of the Internet of Things, big data, and multiobjective optimization. Future directions are also proposed to promote pipeline intelligence.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Zheng Cai et al.
Summary: The effects of sulfate-reducing bacteria on the corrosion behaviors of different pipeline steels were evaluated, showing variations in the corrosion rates and pitting depths.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2022)
Article
Geosciences, Multidisciplinary
Soumi Chaki et al.
Summary: This paper proposes a framework based on Probabilistic Neural Network (PNN) for lithology classification using seismic attributes. The framework is compared with existing supervised classifiers in terms of performance measures such as classification accuracy, sensitivity, and specificity. The study also investigates the selection of appropriate parameters for the classifiers and the importance of individual seismic predictors. The framework is shown to be helpful in estimating the probability of hydrocarbon presence in a large study area.
JOURNAL OF APPLIED GEOPHYSICS
(2022)
Article
Engineering, Multidisciplinary
Jong-hyun Baek et al.
Summary: This study evaluates the failure probability of pipelines in structural reliability assessment by considering the resistance of pipe material to external load or stress. It discusses the various stress factors acting on natural gas pipelines and evaluates the failure probabilities using the Von-Mises stress criterion. Approximate analytical methods, such as the first-order reliability method, are applied in the failure probability analysis.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2022)
Article
Geosciences, Multidisciplinary
Eujeong Choi et al.
Summary: This study proposes a community disaster resilience clustering method that evaluates the disaster resilience of communities by integrating physical vulnerability and socioeconomic recoverability. The results indicate that the method successfully categorizes communities in terms of disaster resilience and provides useful insights for resilience planning.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Engineering, Industrial
Nikola Blagojevic et al.
Summary: Communities and their supporting civil infrastructure systems consist of multiple interacting and interdependent components. A proposed method based on Sobol' indices and a heuristic search is able to measure the importance of vulnerability and recoverability of components for community disaster resilience, without prior knowledge of the components. The method has been demonstrated in two case studies, confirming its ability to identify important components and reduce redundant modeling and data gathering efforts.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Thermodynamics
Bingyuan Hong et al.
Summary: This paper proposes a comprehensive method that considers the various costs of modular equipment and the impact of utilization time on equipment value in unconventional gas field development, aiming to achieve the best economic performance. A real case study is conducted to demonstrate the practicality and advantages of the proposed model.
Article
Economics
Slawomir Raszewski
Summary: This paper examines the failure of the Turkey-Austria natural gas pipeline project (NGPP) and analyzes the EU's external policy. It argues that the drawbacks of the NGPP, attributed to political factors, have actually led to the recovery and improvement of successor projects, as well as the engagement of key stakeholders.
Article
Energy & Fuels
Jianheng Chen et al.
Summary: Bypass pigging technology is a promising strategy to reduce the velocity of pipeline inspection gauge (PIG) and mitigate pigging-induced slug volume. This study proposes an intelligent self-regulated bypass pig prototype with an internal bypass regulating module to enhance the anti-blocking capability for pigging operations. Experimental and numerical investigations were conducted to analyze the force variation characteristics of bypass valve in blocked bypass pigs, providing insights for the optimal design of the bypass regulating module.
JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING
(2022)
Article
Energy & Fuels
Yunhong Che et al.
Summary: This paper proposes a novel framework to improve the accuracy and reliability of battery health prognostic. By introducing sequential information-ensembled health indicators, lifetime clustering, and model migration, the proposed framework achieves high accuracy and reliability in battery health prediction.
Article
Computer Science, Artificial Intelligence
Maciej Kusy et al.
Summary: This paper presents a method for reducing the architecture of the probabilistic neural network (PNN) by clustering data and selecting nearest neighbors. Experimental results show that the reduced PNN achieves higher accuracy than the original network and existing methods in most classification tasks.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Romenia Gurgel Vieira et al.
Summary: This work presents the development of a fault detection method for photovoltaic systems using artificial neural networks. The method is capable of identifying short-circuited modules and disconnected strings. What sets this research apart is its adaptability, as it uses long-term datasets and considers datasets contaminated with random noise, making it suitable for any photovoltaic power plant and eliminating the need for pre-existing system data or new sensor installation. The proposed method consists of two unique algorithms, namely the Multilayer Perceptron and the Probabilistic Neural Network. The research utilized modeling, simulation, and experimental data, with both algorithms trained on simulated datasets and tested on data from two different photovoltaic systems. Despite the inclusion of noisy situations in the training dataset, the results demonstrate superior accuracy for the Multilayer Perceptron neural network. The findings show a maximum accuracy of 99.1% for detecting short-circuited modules and 100% for detecting disconnected strings.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Geosciences, Multidisciplinary
Sefa Mizrak et al.
Summary: The effects of natural and technological disasters can be prevented through scientific and technological developments. This study aimed to investigate the factors affecting the disaster resilience of countries. By analyzing data from 181 countries, the study identified variables that contributed to the rate of population affected by disasters. The findings of the study have implications for disaster risk reduction efforts and can guide future research in this area.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Energy & Fuels
Abigail Andrews et al.
Summary: This study proposes a four-step method for including grid interactivity and demand flexibility in building benchmarking models. It effectively clusters buildings and reveals patterns in building operations and demand flexibility issues.
Article
Engineering, Aerospace
Yanfang Liu et al.
Summary: The study introduces a probabilistic ensemble neural network (PENN) for predicting the long-term behavior of free-floating space manipulators (FFSMs), which effectively addresses the uncertainties in dynamic system estimation by combining a probabilistic deep network dynamics model with the ensemble method and using sampling-based uncertainty propagation for long-term prediction.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Energy & Fuels
Xiaolong Sun et al.
Summary: This study introduces a novel source-to-sink assessment methodology to identify suitable regions for CCS deployment in Spain, selecting potential CO2 sources and storage structures. The research demonstrates that CCS deployment in Spain could help reduce around 21% of carbon emissions and be a significant contributor to achieving the mid-century net-zero target of the Paris Agreement.
Article
Engineering, Marine
Yin Zhang et al.
Summary: This paper proposes an indirect damage identification method based on Probabilistic Neural Network, utilizing natural frequency changes to indirectly identify damage and improve the identification accuracy and efficiency through optimization algorithms. Results show that Genetic Algorithm has higher iterative efficiency and the optimized PNN has higher damage identification accuracy.
Review
Green & Sustainable Science & Technology
B. Li et al.
Summary: This review systematically studies the application of Artificial Neural Network (ANN) and hybridized ANN models for PV fault detection and diagnosis, extracting and analyzing the targeted PV faults, detectable faults, data types and amounts, model configurations, and FDD performance for each application. The main trends, challenges, and prospects for the application of ANN for PV FDD are identified and presented.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Geosciences, Multidisciplinary
Si-Cong Liu et al.
Summary: Urban underground space (UUS) is a crucial part of cities that contributes to urban sustainability through disaster prevention benefits. By analyzing the concept of urban resilience, the relationships between underground facilities and disaster prevention services can be better understood and evaluated. The study shows that UUS has a close connection with infrastructure resilience and plays an important role in disaster response.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Computer Science, Hardware & Architecture
Maedeh Mahzarnia et al.
Summary: This paper introduces a three-stage resilience improvement scheme to enhance the operational power system resilience against a hurricane event, which includes vulnerability assessment, optimal transmission line switching, and preventive islanding techniques. The proposed methodology is evaluated in the IEEE 24-bus test system to examine its applicability.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Engineering, Chemical
Min-Cheng Teng et al.
Summary: This study evaluated earthquake damage to underground pipelines in urban areas and discussed pipeline disaster management procedures and improvement measures, such as establishing a geographic information platform. These measures aim to enhance pipeline safety and reduce the likelihood of secondary disasters.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2021)
Article
Engineering, Industrial
Weichao Yu et al.
Summary: This study proposes an integrated method based on demand-side analysis to assess the supply reliability of large-scale and complex natural gas pipeline networks. By analyzing market demand and user importance, the feasibility of the method is confirmed and suggestions for improving supply reliability are provided.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Weichao Yu et al.
Summary: A subset simulation-based methodology is developed to evaluate the time-dependent reliability of corroding pipelines with multiple correlated corrosion defects and competing failure modes. The accuracy and efficiency of the methodology are demonstrated through a numerical example, and sensitivity analysis reveals significant impact of corrosion defect correlation on system reliability.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Geosciences, Multidisciplinary
Melissa Parsons et al.
Summary: This study presents a national-scale assessment of disaster resilience in Australia, revealing a distribution where metropolitan and inner regional areas have higher capacity for disaster resilience compared to outer regional, remote, and very remote areas. The assessment also highlights various themes of disaster resilience that impact different communities, such as community capital and social cohesion. Understand the spatial distribution of disaster resilience can help in developing policies and programs to address systemic influences on disaster resilience.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Engineering, Environmental
Yan Cui et al.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2020)
Article
Energy & Fuels
Wenbin Yu et al.
Article
Energy & Fuels
Weichao Yu et al.
JOURNAL OF ENERGY STORAGE
(2020)
Article
Engineering, Mechanical
Mahmood Farzaneh-Gord et al.
FLOW MEASUREMENT AND INSTRUMENTATION
(2020)
Article
Computer Science, Artificial Intelligence
Hoda Zamani et al.
APPLIED SOFT COMPUTING
(2019)
Article
Development Studies
Bernard Manyena et al.
Proceedings Paper
Engineering, Mechanical
S. A. Tikhonova et al.
1ST INTERNATIONAL CONFERENCE ON INTEGRITY AND LIFETIME IN EXTREME ENVIRONMENT (ILEE-2019)
(2019)
Article
Engineering, Mechanical
Taolong Xu et al.
ENGINEERING FAILURE ANALYSIS
(2018)
Article
Energy & Fuels
Mahmood Farzaneh-Gord et al.
JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING
(2018)
Article
Energy & Fuels
Masoud Ahmadipour et al.
Review
Geosciences, Multidisciplinary
Crystal Kwan et al.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2017)
Article
Geosciences, Multidisciplinary
Yang Kai et al.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2017)
Article
Energy & Fuels
Shuai Li et al.
Article
Engineering, Mechanical
Jie Zhang et al.
ENGINEERING FAILURE ANALYSIS
(2016)
Article
Engineering, Industrial
Xerandy et al.
Article
Computer Science, Information Systems
Bo-Hao Chen et al.
INFORMATION SCIENCES
(2015)
Article
Computer Science, Artificial Intelligence
Hamse Y. Mussa et al.
PATTERN RECOGNITION LETTERS
(2015)
Article
Energy & Fuels
Joshua D. Rhodes et al.
Article
Optics
Changjun Zhou et al.
Article
Business
Nuno Camacho et al.
INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING
(2014)
