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2025 International Petroleum technology Conference, IPTC 2025

作者： Wu, Zangyuan Feng, Qihong Lian, Liming Meng, Xiangjuan Xu, YanLong Wang, Sen Wu, Kuankuan Zhou, Wei Luo, Min Li, Yang Fan, Jin Cheng, ronghong Wu, Mimi Huang, Xingning School of Petroleum Engineering China University of Petroleum East China China Tarim Oilfield Company PetroChina Korla China R&D Center for Ultra-Deep Complex Reservoir Exploration and Development CNPC Korla China Research Institute of Petroleum E&D Petrochina CNPC Beijing China Chengdu CK Energy Technology Co. Ltd. Chengdu China

ISBN: (纸本)9781959025436

This paper addresses the difficulty in calculating CO2 storage volume due to the complexity of CO2 occurrence states in the CCUS process. A method for calculating CO2 storage volume is proposed, designing well networks throughout the entire lifecycle of CCUS to meet the demands of both CO2 EOr and storage stages. This extends the implementation time of CO2 EOr to enhance oil recovery and ensures effective CO2 storage while maximizing oil production, aligning with the global strategy of green and low-carbon development. Initially assuming that the pore volume of produced hydrocarbons is completely occupied by CO2 and considering dissolution retention and mineral reaction retention, the theoretical carbon storage volume of the target reservoir is predicted to determine the upper limit of storage volume. Building on flash calculation, utilizing equations of state-activity models, equations of state-equations of state models, and chemical reaction kinetics models, model parameters were fitted and corrected through experiments on CO2 multiphase non-isothermal flow, dissolution, solid-phase deposition, and mineral reactions to develop a CO2 storage volume prediction model and proprietary software. Finally, reliability verification was conducted using analogous block comparison methods. The technology proposed in this paper has been applied in the integrated CO2 EOr and storage scheme for the L reservoir, predicting saturation fields, solubility fields, and various storage mechanisms during the CO2 flooding and storage process and providing three-dimensional field changes. results indicate that the theoretical carbon storage upper limit for the L reservoir is 9.88 million tons;under current reservoir temperature and pressure conditions, CO2 dissolution loss in formation connate water is 0.05 t/m3, and in residual oil it is 0.32 t/t, resulting in an effective storage volume of 7.47 million tons (with analogous block comparison results at 7.78 million tons, verifying the rel

关键词： Oil well flooding

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Low Power Consumption using dynamic Cell Area Integration in 6G Mobile Networks

Low Power Consumption using Dynamic Cell Area Integration in...

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OptoElectronics and Communications Conference, OECC

作者： Hiroyuki Saito Yoshihiro Nakahira Masayuki Kashima Masahiro Sarashina Photonics R&D Department Research & Development Center Technology Division Oki Electric Industry Co. Ltd Warabi-shi Saitama Japan

Both increasing network capacity and low power consumption are required for 6G mobile networks. We propose a dynamic area integration method at the user side to reduce the power consumption. Using proposed method, 28.... 详细信息

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

关键词： 6G mobile communication Power demand System dynamics

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Fabrication of a Hydrophobic Hierarchical Surface on Shale Using Modified Nano-SiO_(2)for Strengthening the Wellbore Wall in drilling Engineering

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Engineering 2022年第4期8卷 101-110页

作者： Xianbin Huang Jinsheng Sun He Li ren Wang Kaihe Lv Haichao Li Key Laboratory of Unconventional Oil and Gas Development(China University of Petroleum(East China)) Ministry of EducationQingdao 266580China School of Petroleum Engineering China University of Petroleum(East China)Qingdao 266580China CNPC Engineering Technology R&D Co. Ltd.Beijing 102206China

Wellbore stability is essential for safe and efficient drilling during oil and gas exploration and *** paper introduces a hydrophobic nano-silica(HNS)for use in strengthening the wellbore wall when using a water-based drilling fluid(WBF).The wellbore-strengthening performance was studied using the linear swelling test,hot-rolling recovery test,and compressive strength *** mechanism of strengthening the wellbore wall was studied by means of experiments on the zeta potential,particle size,contact angle,and surface tension,and with the use of a scanning electron microscope(SEM).The surface free energy changes of the shale before and after HNS treatment were also calculated using the contact angle *** experimental results showed that HNS exhibited a good performance in inhibiting shale swelling and *** with the use of water,the use of HNS resulted in a 20%smaller linear swelling height of the bentonite pellets and an 11.53 times higher recovery of water-sensitive shale—a performance that exceeds those of the commonly used shale inhibitors KCl and *** importantly,the addition of HNS was effective in preventing a decrease in shale *** to the mechanism study,the good wellbore-strengthening performance of HNS can be attributed to three ***,the positively charged HNS balances parts of the negative charges of clay by means of electrostatic adsorption,thus inhibiting osmotic ***,HNS fabricates a lotus-leaf-like surface with a micro-nano hierarchical structure on shale after adsorption,which significantly increases the water contact angle of the shale surface and considerably reduces the surface free energy,thereby inhibiting surface ***,the decrease in capillary action and the effective plugging of the shale pores reduce the invasion of water and promote wellbore *** approach described herein may provide an avenue for inhibiting both the surface hydration and the os

关键词： Hydrophobic Nanoparticle Shale inhibitor drilling fluid Wellbore stability

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Performance and wear mechanisms of TiAlN-NbN coated cemented carbide in milling Ti6Al4V with different cooling and lubrication approaches

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Wear 2025年

作者： Lindvall, rebecka Casas Gayubo, Josu Gutnichenko, Oleksandr Auzenat, François M'Saoubi, rachid Bushlya, Volodymyr Division of Production and Materials Engineering Lund University Ole Römers Väg 1 Lund221 00 Sweden R&D Milling and Process Seco Tools France 22 Avenue de La Prospective Bourges18 000 France R&D Materials and Technology Development Seco Tools AB Fagersta737 82 Sweden

Titanium alloys are difficult-to-machine materials given their high strength, the high temperatures generated, and the naturally short contact length that combined result in rapid tool wear. different machining strategies can be employed to cope with the low machinability. This study investigates the machining performance using different cooling and lubrication methods during down face milling of the most employed Ti alloy Ti6Al4V. The conditions include a dry environment, flood coolant, and sustainable vegetable oil applied at minimum quantity lubrication (MQL) condition. The tool life at dry conditions and with MQL applied vegetable oil are similar but MQL shows promising potential in prolonging tool life. Flood coolant provided no beneficial effect and tool life was about 50 % shorter as to dry and MQL conditions. The tool wear evolution on as-worn tools and their cross-sections is studied in scanning electron microscope using X-ray energy-dispersive spectroscopy. The PVd applied TiAlN-NbN coated WC-12%Co tools are worn by mechanical fracturing which is additionally accelerated by the outward diffusion of C from WC and Co binder that facilitate WC grain pull-out. Oxidation of Co binder further weakens the tool material mechanically. © 2025 The Authors

关键词： Titanium alloys

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Hypergraph-Based Session Modeling: A Multi-Collaborative Self-Supervised Approach for Enhanced recommender Systems 30

Hypergraph-Based Session Modeling: A Multi-Collaborative Sel...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language resources and Evaluation, LrEC-COLING 2024

作者： Zheng, Xiangping Wu, Bo Zhang, Alex X. Li, Wei College of Computer Science and Technology Harbin Engineering University China R&D and External Relations Department Xiangjiang Laboratory China Modeling and Emulation in E-Government National Engineering Laboratory China Harvest Fund Management Co. Ltd. China Qingdao Innovation and Development Base of Harbin Engineering University China

ISBN: (纸本)9782493814104

Session-based recommendation (SBr) is a challenging task that involves predicting a user's next item click based on their recent session history. Presently, many state-of-the-art methodologies employ graph neural networks to model item transitions. Notwithstanding their impressive performance, graph-based models encounter significant challenges when confronted with intricate session dependencies and data sparsity in real-world scenarios, ultimately constraining their capacity to enhance recommendation accuracy. In recognition of these challenges, we introduce an innovative methodology known as'Mssen,' which stands for Multi-collaborative self-supervised learning in hypergraph neural networks. Mssen is meticulously crafted to adeptly discern user intent. Our approach initiates by representing session-based data as a hypergraph, adeptly capturing intricate, high-order relationships. Subsequently, we employ self-supervised learning on item-session hypergraphs to mitigate the challenges of data sparsity, all without necessitating manual fine-tuning, extensive search, or domain-specific expertise in augmentation selection. Comprehensive experimental analyses conducted across multiple datasets consistently underscore the superior performance of our approach when compared to existing methodologies. © 2024 ELrA Language resource Association: CC BY-NC 4.0.

关键词： Graph neural networks

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Improving robustness of GNN-based Anomaly detection by Graph Adversarial Training 30

Improving Robustness of GNN-based Anomaly Detection by Graph...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language resources and Evaluation, LrEC-COLING 2024

ISBN: (纸本)9782493814104

Graph neural networks (GNNs) play a fundamental role in anomaly detection, excelling at the identification of node anomalies by aggregating information from neighboring nodes. Nonetheless, they exhibit vulnerability to attacks, with even minor alterations in the graph structure or node attributes resulting in substantial performance degradation. To address this critical challenge, we introduce an innovative mechanism for graph adversarial training, meticulously designed to bolster GNN-based anomaly detection systems against potential poisoning attacks. This novel approach follows a two-step framework. (1) In the initial phase, we employ a Multiple-Objective Generative Adversarial Attack (MO-GAA), which focuses on generating feature modifications and inducing structural disruptions within the graph. Its primary objective is to mimic the adversarial behavior of potential attackers on the anomaly detection graph, with the explicit intention of confounding the anomaly detector. (2) In the subsequent stage, we introduce Purification-Based Adversarial Attack defense (PB-AAd), a method specifically designed to rectify any contamination and restore the integrity of the graph. The central aim of PB-AAd is to counteract the destructive actions carried out by potential attackers. Our empirical findings, derived from extensive experiments conducted on four real-world anomaly detection datasets, serve to demonstrate how MO-GAA systematically disrupts the graph, compromising the effectiveness of GNN-based detectors, while PB-AAd effectively mitigates these adversarial actions, thereby enhancing the overall robustness of GNN-based anomaly detectors. © 2024 ELrA Language resource Association: CC BY-NC 4.0.

关键词： Anomaly detection

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Sub-surface sinking effect of reinforcement particle in laser assisted machining of metal matrix composites

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CIrP Annals 2025年

作者： Mypati, Omkar Liao, Zhirong Zan, Shusong M'Saoubi, rachid Axinte, dragos Machining and Condition Monitoring Group Faculty of Engineering University of Nottingham United Kingdom R&D Materials and Technology Development Fagersta Sweden Division of Production and Materials Engineering Lund University Lund Sweden

Aluminium-based SiC particle-reinforced metal matrix composites are widely used in engineering applications due to their exceptional mechanical properties. However, their machining remains challenging due to the mismatch of material properties between the brittle SiC particles and the ductile aluminium matrix, causing tool wear and surface damage. To mitigate these issues, laser inverse problem scanning is utilised to strategically melt the top layer aluminium matrix, allowing the SiC particles to sink and promoting more ductile Al-matrix. The strategic hybrid laser milling approach optimises particle sinking, reduces tool wear and enhances surface integrity by minimising particle fracture, pullout and refining microstructure. © 2025 The Author(s)

关键词： Milling (machining)

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Measurement and analysis of acoustic characteristics of panel type sensor arrays in an open water tank 24

Measurement and analysis of acoustic characteristics of pane...

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24th International Congress on Acoustics, ICA 2022

作者： Kim, Kyungseop Pyo, Seonghun Kwon, Byung-Jin Chang, Woosuk Lee, Jeong-Min Agency for Defense Development Maritime Technology Research Institute Korea Republic of LIG Nex1 Co. Ltd. Maritime R&D Lab. Korea Republic of

A new method is presented for acoustic measurement of a panel type sensor module in open water tank. The method utilizes the data from the hydrophones, which have in-plane three different positions, of the sensor module. It provides an estimation of the edge-diffracted pressure field as well as the sensor receiving field (incident/reflected pressure) for the finite-sized module. The method is applied on the synthetic and experimental data to confirm the validity. diffraction effects on the measurement of the acoustic characteristics are examined, and distribution characteristics of scattering sound field around panels according to sample size and composition of the panel materials are also analyzed. © ICA *** rights reserved

关键词： Acoustic measurement diffraction Panel

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Hybrid Complex Proportional Assessment-Multi-objective Grey Wolf Optimizer for Biodiesel Process Optimization 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Shanmugasundar, G. Chohan, Jasgurpreet Singh Kalita, Kanak Department of Mechanical Engineering Sri Sairam Institute of Technology Chennai600044 India Department of Mechanical Engineering and University Centre for Research & Development Chandigarh University Mohali140413 India Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Jadara University Research Center Jadara University Irbid Jordan

ISBN: (数字)9783031733215

ISBN: (纸本)9783031733208

In this study, a hybrid COPrAS-MOGWO (Complex Proportional Assessment-Multi-Objective Grey Wolf Optimizer) optimization approach is proposed for optimizing biodiesel production. The performance of the MOGWO is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II). Optimization of biodiesel production from waste frying soybean oil through transesterification is considered as the case study to test the proposed algorithm. The research aims to minimize energy consumption and maximize reaction conversion and green chemistry balance simultaneously. results indicate that MOGWO outperforms NSGA-II in terms of computational time and solution quality. Furthermore, the same best compromise solution (BCS) is identified by COPrAS across different weight-based scenarios. By comparing the relative performance of NSGA-II and MOGWO, this study contributes valuable insights into multi-objective optimization in biodiesel production and provides guidance for researchers and practitioners in selecting appropriate optimization algorithms to improve the efficiency and sustainability of biodiesel production processes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Cleaner production

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MErEC-MABAC Based-Parametric Optimization of Chemical Vapour deposition Process for diamond-Like Carbon Coatings 6th

MEREC-MABAC Based-Parametric Optimization of Chemical Vapour...

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6th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Prabhukumar, Sellamuthu Chohan, Jasgurpeet Singh Kalita, Kanak Department of Mechanical Engineering Presidency University Bangalore India Department of Mechanical Engineering University Centre for Research and Development Chandigarh University Mohali India Department of Mechanical Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi India

ISBN: (纸本)9783031501579

This research paper presents an application of the Multi-attributive Border Approximation Area Comparison (MABAC) method combined with the Method based on the removal Effects of Criteria (MErEC) for the parametric optimization of the Chemical Vapor deposition (CVd) process in diamond-like Carbon (dLC) coatings. A decision matrix is formulated using a case study from the literature. Four response parameters namely, Hardness (H), Young’s modulus (E), Coefficient of Friction (COF), and Wear rate (Wr) are considered. The weight allocation for these response parameters is calculated using five different methods, namely MErEC, mean weight (Mean), Standard deviation (Stdev), Entropy, and Criteria Importance Through Intercriteria Correlation (CrITIC) method. The MABAC method was employed to obtain the optimal parametric combination for the dLC coatings. results showed a clear superior combination of the CVd process parameters can be achieved using the MErEC-MABAC methodology. Thus, the study successfully demonstrates the effectiveness of the MErEC-MABAC-based approach for the simultaneous optimization of multiple responses in the CVd process for dLC coatings. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Coatings

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