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Flexible refractory castables based on the Al2O3-MgO-TiO2 system

Ceramics International 2025年第15期51卷 20822-20829页

作者： Reitmann, B. Borges, O.H. Falsetti, L.O.Z. Pagliosa Neto, C. Pandolfelli, V.C. Federal University of São Carlos Graduate Program in Materials Science and Engineering São Carlos Brazil São Carlos Brazil RHI Magnesita Research and Development Center Contagem Brazil

Toughening by in-situ phase formation is highly desired for high-performance refractories, as it enhances their thermomechanical properties (e.g. thermal shock damage resistance). For this purpose, pseudobrookite and intermediary spinels are promising phases due to their thermal expansion mismatch, resulting in self-microcracking. Aiming to develop highly flexible refractory castables, compositions based on the Al2O3-MgO-TiO2 system were formulated with the aid of computational thermodynamics. Of the most promising compositions, five of them were experimentally produced and had their thermomechanical and physical properties assessed by X-ray diffraction, in-situ elastic modulus, thermal shock damage analysis (ΔT = 1000 °C) and scanning electron microscopy. Results pointed out that small titania contents led to a positive effect on microstructure densification, improving the mechanical performance of the refractories and generation of phases that induce microcracking upon cooling, enhancing the thermal shock damage resistance. Nevertheless, an excess of TiO2 led to extensive cracking and cohesion loss in the refractory matrix. © 2025

关键词： Microcracking

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Microstructural Evolution during Tensile Deformation in TRC-ZA21 Magnesium Alloy with Different Loading Directions and Strain Rates

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Acta Metallurgica Sinica(English Letters) 2023年第2期36卷 192-214页

作者： Yun Zhang Chen Jiang Shaoheng Sun Wei Xu Quan Yang Yongjun Zhang Shiwei Tian Xiaoge Duan Zhe Xu Haitao Jiang Institute of Engineering Technology University of Science and Technology BeijingBeijing100083China China Electric Power Research Institute Beijing100055China Shunde Graduate School of University of Science and Technology Beijing Foshan528399China China Ship Research and Development Academy Beijing100081China

The variation of texture characteristics and activation of deformation mechanism in magnesium alloys can be achieved by addition of RE and Ca elements and subsequently affect the microstructure evolution during deformation *** this manuscript,the effects of loading direction and strain rate on mechanical properties,microstructural characteristics,texture evolution and deformation mechanism in TRC-ZA21 magnesium alloy sheet were ***,orientation dependence and strain rate sensitivity of deformation mechanism were also *** results showed that evident difference in mechanical properties in TRC-ZA21 alloy exhibited by the changes in loading direction and strain *** variations in grain orientation and basal texture characteristic were attributed to the grain rotation behavior during the plastic deformation,dominated by deformation *** slip,extension twinning and prismatic slip played different contributions to plastic deformation behavior and presented orientation dependence and strain rate *** activities of prismatic slip and extension twinning both enhance with increasing strain *** phenomenon of weakened effect of twinning and promoted role of prismatic slip was presented to coordinate strain compatibility during plastic deformation.

关键词： Magnesium alloys Mechanical property Orientation behavior Deformation mechanism Microstructural evolution

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Adaptive spatio-temporal attention neural network for cross-database micro-expression recognition

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Virtual Reality & Intelligent Hardware 2023年第2期5卷 142-156页

作者： Yuhan RAN Key Laboratory of Child Development and Learning Science of Ministry of Education Research Center for Learning ScienceSoutheast UniversityNanjing 210096China School of Cyber Science and Engineering Southeast UniversityNanjing 210096China

Background The use of micro-expression recognition to recognize human emotions is one of the most critical challenges in human-computer interaction applications. In recent years, cross-database micro-expression recognition(CDMER) has emerged as a significant challenge in micro-expression recognition and analysis. Because the training and testing data in CDMER come from different micro-expression databases, CDMER is more challenging than conventional micro-expression recognition. Methods In this paper, an adaptive spatio-temporal attention neural network(ASTANN) using an attention mechanism is presented to address this challenge. To this end, the micro-expression databases SMIC and CASME II are first preprocessed using an optical flow approach,which extracts motion information among video frames that represent discriminative features of *** preprocessing, a novel adaptive framework with a spatiotemporal attention module was designed to assign spatial and temporal weights to enhance the most discriminative features. The deep neural network then extracts the cross-domain feature, in which the second-order statistics of the sample features in the source domain are aligned with those in the target domain by minimizing the correlation alignment(CORAL) loss such that the source and target databases share similar distributions. Results To evaluate the performance of ASTANN, experiments were conducted based on the SMIC and CASME II databases under the standard experimental evaluation protocol of CDMER. The experimental results demonstrate that ASTANN outperformed other methods in relevant crossdatabase tasks. Conclusions Extensive experiments were conducted on benchmark tasks, and the results show that ASTANN has superior performance compared with other approaches. This demonstrates the superiority of our method in solving the CDMER problem.

关键词： Cross-database micro-expression recognition Deep learning Attention mechanism Domain adaption

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Data-driven diagnosis of high temperature PEM fuel cells based on the electrochemical impedance spectroscopy: Robustness improvement and evaluation

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Journal of Energy Chemistry 2024年第9期96卷 544-558页

作者： Dan Yu Xingjun Li Samuel Simon Araya Simon Lennart Sahlin Vincenzo Liso Department of Energy Aalborg UniversityAalborg 9220Denmark Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA Materials Research and Technology Development Luxembourg Institute of Science and Technology(LIST)4422 BelvauxLuxembourg

Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a critical and challenging task in real application. To enhance the robustness of diagnosis and achieve a more thorough evaluation of diagnostic performance, a robust diagnostic procedure based on electrochemical impedance spectroscopy (EIS) and a new method for evaluation of the diagnosis robustness was proposed and investigated in this work. To improve the diagnosis robustness: (1) the degradation mechanism of different faults in the high temperature PEM fuel cell was first analyzed via the distribution of relaxation time of EIS to determine the equivalent circuit model (ECM) with better interpretability, simplicity and accuracy;(2) the feature extraction was implemented on the identified parameters of the ECM and extra attention was paid to distinguishing between the long-term normal degradation and other faults;(3) a Siamese Network was adopted to get features with higher robustness in a new embedding. The diagnosis was conducted using 6 classic classification algorithms—support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and Naive Bayes employing a dataset comprising a total of 1935 collected EIS. To evaluate the robustness of trained models: (1) different levels of errors were added to the features for performance evaluation;(2) a robustness coefficient (Roubust_C) was defined for a quantified and explicit evaluation of the diagnosis robustness. The diagnostic models employing the proposed feature extraction method can not only achieve the higher performance of around 100% but also higher robustness for diagnosis models. Despite the initial performance being similar, the KNN demonstrated a superior robustness after feature selection and re-embedding by triplet-loss method, which sug

关键词： PEM fuel cell Data-driven diagnosis Robustness improvement and evaluation Electrochemical impedance spectroscopy

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Hospital laundry practices and nosocomial infection risk in a Moroccan public hospital: critical views and suggestions for improvement

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International Journal of Environmental Studies 2025年第1期82卷 633-656页

作者： Mourabit, Nadira Elwardi, Khadija Bouhoudan, Assia Ouakourou, Hajar Nafai, Manal Bakkali, Mohamed Laboratory of Research and Development in Engineering Sciences Faculty of Sciences and Techniques of Al-Hoceima Abdelmalek Essaadi University Tetouan Morocco Faculty of Science and Technology of Tangier Abdelmalek Essaâdi University Tetouan Morocco

This study investigates the role of linen from laundry washing and Intensive Care Units in spreading infections at a Public Hospital in North Morocco. Microbiological analyses revealed 100% contamination of linens with a concerning presence of bacteria like Enterobacterales (30%), Pseudomonas aeruginosa (21.11%), and Acinetobacter baumannii (13.3%). Most isolated bacteria show significant resistance. For all Gram-negative bacteria, ceftazidime resistance exceeded 48%, and Enterobacterales exhibited the lowest carbapenem resistance rate (14.8%). No methicillin-resistant Staphylococcus aureus was isolated. Interestingly, germ prevalence showed no significant difference between laundry and ICU settings (p = 0.68), and a solid positive correlation suggests potential cross-contamination. The FMECA analysis revealed critical deficiencies in the laundry process, including staff training and segregation of dirty from clean laundry. The PESTEL analysis highlighted the need for laundry equipment and stringent hospital linen management to ensure patient safety. This study reveals linens as potential pathogen reservoirs and highlights laundry process deficiencies. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Linen

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GO/HTPB composite liner for anti-migration of small molecules

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Defence Technology（防务技术） 2023年第4期22卷 156-165页

作者： Hao Li Jie Wei Ya-nan Zhang Yu-bing Hu Wei Jiang Teng-yue Zhang College of Materials Science and Engineering Nanjing Tech UniversityNanjing211816China National Special Superfine Powder Engineering Research Center of China Nanjing University of Science and TechnologyNanjing210014China Key Laboratory of Special Energy Materials Nanjing University of Science and TechnologyMinistry of EducationNanjing210094China China Research and Development Academy of Machinery Equipment Beijing100089China

Hydroxyl-terminated polybutadiene/toluene diisocyanate(HTPB/TDI)system is widely used in composite solid *** migrations of plasticizers and water molecules from solid propellants and surrounding environment to the inhibitor have always been the important *** study focuses on the preparation,characterization and anti-migration behavior of graphene oxide(GO)/HTPB nanocomposite *** GO/HTPB(GH)composite liners affect the migration of small molecules through a tighter cross-linked structure and weakening function of small molecule *** anti-migration performance of the liner at different temperatures was analyzed,and the influence of the added amount of GO on the anti-migration performance and adhesion performance was also systematically *** overall performance of the liner is optimized when the amount of GO filler is 0.3 wt%.After adding 0.3 wt%GO,the concentration of dioctyl sebacate(DOS)migrated into the liner is decreased by 23.28%,and the concentration of water molecules is decreased by 51.89%,indicating that the introduction of GO can significantly improve the anti-migration performance of the *** addition,the bond strength is greatly increased from 0.25 MPa to 0.95 MPa,which meets the application requirements of the current propellant *** research provides an important way for the preparation of structure-function synergistic anti-migration composite liners.

关键词： Graphene oxide Liner Structure-function Anti-migration Bonding

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Developing an Edge based predictive maintenance system for transformer using low-cost sensors 2

Developing an Edge based predictive maintenance system for t...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Baji, Pratiksha Pradeep Gavankar, Nitin L. Mahambrey, Mayur Rokade, Sonali S. Walchand College of Engineering Computer Science and Engineering Maharashtra Sangli416 416 India Siemens Verna Research & Development Goa 403722 India

ISBN: (纸本)9798331528713

Transformers are essential for ensuring the reliable distribution and transmission of electrical power. Traditional maintenance procedures, which are generally reactive and schedule-driven, can result in costly breakdowns and unanticipated expenses. This research offers an edge-based predictive maintenance system for transformers that uses powerful machine learning techniques and five temperature sensors strategically distributed throughout the transformer in non-invasive manner. The system uses edge computing to handle real-time temperature data locally, allowing for more precise and accurate anomaly detection and predictive analytics. This strategy enables proactive maintenance, timely interventions, and less operational disturbances. The proposed methodology optimises maintenance schedules, lowers downtime, and increases grid reliability, providing a viable method for managing essential infrastructure and improving overall grid dependability. © 2024 IEEE.

关键词： Predictive maintenance

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Unveiling R&D Project Timelines with AI 3

Unveiling R&D Project Timelines with AI

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Chopra, Raghav Goswami, Sumit Guru Nanak Dev Engineering College Department of Computer Science & Engineering Ludhiana India Defence Research & Development Organisation New Delhi India

ISBN: (纸本)9798331518592

Predictive analytics in project management has the power to reshape the way we forecast and manage project timelines, paving the way for enhanced efficiency and favourable project results. This research evaluates machine learning models for predicting time required for projects based on project titles and ancillary features. Utilizing feature selection techniques, including Chi-Squared and scikit-learn, we refined our dataset by removing redundant and noisy features to enhance model performance and generalizability. The preprocessing sequence incorporated categorical encoding, and feature scaling to standardize inputs to the model. We implemented and benchmarked predictive models-Random Forest Regressor, Neural Network, Support Vector Regressor, and Gradient Boosting Regressor. Model efficacy was quantified using Mean Squared Error (MSE), Mean Absolute Error (MAE), and R2 Score. Our results indicate that ensemble methods, particularly Random Forest and Gradient Boosting, exhibit good accuracy in capturing complex nonlinear dependencies within project data. This study demonstrates the significance of meticulous feature engineering and selection in machine learning-driven project management, providing a detailed comparative analysis of model performances for delay prediction. We achieved an MSE of 0.09 through our research, underscoring the effectiveness of our approach in accurately predicting project timelines. © 2024 IEEE.

关键词： Predictive analytics

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Structural Variation between the Western and Eastern Kuqa Fold-and-thrust Belt,China:Insights from Seismic Interpretation and Analog Modeling

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Acta Geologica Sinica(English Edition) 2023年第4期97卷 1078-1093页

作者： WANG Wei XIE Huiwen YIN Hongwei JIA Dong XU Zhenping LUO Haoyu HE Wanhui YUAN Rui DUAN Yunjiang School of Earth Science and Engineering Nanjing UniversityNanjing 210046China Research Institute of Petroleum Exploration and Development Tarim Oilfield CompanyPetroChinaKorlaXinjiang 841000China

The Kuqa fold-and-thrust belt exhibits apparent structural variation in the western and eastern *** salt layer act as effective decollements and influence the varied *** this study,detailed seismic interpretations and analog modeling are presented to construct the suprasalt and subsalt structures in the transfer zone of the middle Kuqa and investigate the influence of the two salt *** results reveal that the relationship of the two salt layers changes from separated to connected,and then overlapped toward the foreland in the transfer *** structural models are formed in the suprasalt and subsalt units due to the interaction of the two salt *** imbricate thrust faults form two broom-like fault systems in the subsalt *** suprasalt units develop detached folds terminating toward the east in the region near the orogenic ***,two offset anticlines with different trends develop at the frontal edge of the lower salt layer and the trailing edge of the upper salt layer,*** to exploration results in this region,the relationship between suprasalt and subsalt structures has an influence on hydrocarbon *** believe that the connected deformation contains high-risk plays while the decoupled deformation contains well-preserved plays.

关键词： along-strike variation analog modeling 3D geometric model salt-related structure Kuqa fold-and-thrust belt

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Adaptive Leader-Follower Consensus Control of Multiple Flexible Manipulators With Actuator Failures and Parameter Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 1020-1031页

作者： Yu Liu Lin Li School of Automation Science and Engineering South China University of TechnologyGuangzhou 510640 Research and Development Center of Precision Electronic Manufacturing Technology Guangzhou Institute of Modern Industrial TechnologyGuangzhou 511458China

In this paper,the leader-follower consensus problem for a multiple flexible manipulator network with actuator failures,parameter uncertainties,and unknown time-varying boundary disturbances is *** purpose of this study is to develop distributed controllers utilizing local interactive protocols that not only suppress the vibration of each flexible manipulator but also achieve consensus on joint angle position between actual followers and the virtual *** the accomplishment of the reconstruction of the fault terms and parameter uncertainties,the adaptive neural network method and parameter estimation technique are employed to compensate for unknown items and bounded ***,the Lyapunov stability theory is used to demonstrate that followers’angle consensus errors and vibration deflections in closed-loop systems are uniformly ultimately ***,the numerical simulation results confirm the efficacy of the proposed controllers.

关键词： Actuator failures leader-follower consensus multiple flexible manipulators neural network parameter uncertainties

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