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Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Journal of Magnesium and Alloys 2024年第2期12卷 750-766页

作者： Xiaoxi Mi Lili Dai Xuerui Jing Jia She Bjørn Holmedal Aitao Tang Fusheng Pan College of Materials science and Engineering Chongqing UniversityChongqing 400044China Southwest technology and Engineering Research Institute Chongqing 400039China National Engineering Research Center for Magnesium Alloys Chongqing UniversityChongqing 400044China Department of Materials science and Engineering Norwegian University of Science and Technology(NTNU)Trondheim 7051Norway

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various *** development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial *** the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg *** paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought *** employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy *** model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design *** RBOALM,several new high-performance alloys have been successfully designed and ***,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture ***,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

关键词： Mg-Mn-based alloys High-performance Alloy design Machine learning Bayesian optimization

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Well-Posedness of Stochastic Continuity Equations on Riemannian Manifolds

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Chinese Annals of Mathematics,Series B 2024年第1期45卷 81-122页

作者： Luca GALIMBERTI Kenneth H.KARLSEN Department of Mathematical sciences NTNU Norwegian University of Science and TechnologyN-7491 TrondheimNorway Department of mathematics University of OsloP.O.Box 1053BlindernN-0316 OsloNorway

The authors analyze continuity equations with Stratonovich stochasticity,■ρ+divh[ρo(u(t,x)+∑_(i=1)^(N)a_(i)(x)w_(i)(t))]=0defined on a smooth closed Riemannian manifold M with metric *** velocity field u is perturbed by Gaussian noise terms Wi(t),:WN(t)driven by smooth spatially dependent vector fields a1(x),...,aN(x)on *** velocity u belongs to L_(t)^(1)W_(x)^(1,2)with divh u bounded in Lf,for p>d+2,where d is the dimension of M(they do not assume div_(h) u∈L_(t,x)^(∞)).For carefully chosen noise vector fields ai(and the number N of them),they show that the initial-value problem is well-posed in the class of weak L^(2) solutions,although the problem can be ill-posed in the deterministic case because of concentration *** proof of this“regularization by noise”result is based on a L^(2) estimate,which is obtained by a duality method,and a weak compactness argument.

关键词： Stochastic continuity equation Riemannian manifold Hyperbolic equa-tion Non-smooth velocity field Weak solution Existence Uniqueness

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A Comparative Study on the Post-Buckling Behavior of Reinforced Thermoplastic Pipes(RTPs)Under External Pressure Considering Progressive Failure

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China Ocean Engineering 2024年第2期38卷 233-246页

作者： DING Xin-dong WANG Shu-qing LIU Wen-cheng YE Xiao-han College of Engineering Ocean University of ChinaQingdao 266100China Shandong Provincial Key Laboratory of Ocean Engineering Ocean University of ChinaQingdao 266100China Department of Marine technology Norwegian University of Science and Technology(NTNU)Trondheim NO-7491Norway

The collapse pressure is a key parameter when RTPs are applied in harsh deep-water *** investigate the collapse of RTPs,numerical simulations and hydrostatic pressure tests are *** the numerical simulations,the eigenvalue analysis and Riks analysis are combined,in which the Hashin failure criterion and fracture energy stiffness degradation model are used to simulate the progressive failure of composites,and the“infinite”boundary conditions are applied to eliminate the boundary *** for the hydrostatic pressure tests,RTP specimens were placed in a hydrostatic chamber after filled with *** has been observed that the cross-section of the middle part collapses when it reaches the maximum *** collapse pressure obtained from the numerical simulations agrees well with that in the ***,the applicability of NASA SP-8007 formula on the collapse pressure prediction was also *** has a relatively greater difference because of the ignorance of the progressive failure of *** the parametric study,it is found that RTPs have much higher first-ply-failure pressure when the winding angles are between 50°and 70°.Besides,the effect of debonding and initial ovality,and the contribution of the liner and coating are also discussed.

关键词： reinforced thermoplastic pipes post-buckling behavior progressive failure of composites debonding initial ovality

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Distributed Hybrid Model Predictive Secondary Control of DC Microgrids with Random Communication Disorders

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 925-935页

作者： Meysam Yaribeygi Zeinab Karami Qobad Shafiee Hassan Bevrani the Department of Electrical Engineering K.N.Toosi University of TechnologyTehranIranand he is now with the Sportradar CompanyTrondheimNorway the Department of Engineering Cybernetics(ITK) Norwegian University of Science and Technology(NTNU)TrondheimNorway the Smart/Micro Grids Research Center Department of Electrical EngineeringUniversity of KurdistanSanandajIran

A reliable and robust communication network is essential to exchange information between distributed generators(DGs)and accurately calculate their control actions in microgrids(MGs).However,the integration of the communication network and MGs poses challenges related to the flexibility,availability,and reliability of the ***,random communication disorders such as time delays and packet loss can negatively impact the system ***,it is essential to design a suitable secondary controller(SC)with a fast dynamic response to restore voltage and appropriate powersharing,while ensuring that the effects of random communication disorders are *** this regard,an optimal distributed hybrid model predictive secondary control method is presented in this *** simulations are carried out in a mixed simulation environment based on MATLAB and OMNET++,by considering IEEE 802.11(Wi Fi)using the recently developed Internet networking(INET)*** the implemented application layer,the recovery Unit is responsible for reducing the impact of random communication *** effectiveness and performance of the proposed method in comparison with a conventional model predictive control are verified by simulation results.

关键词： Microgrid model predictive control random communication disorder secondary control

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Vision based intelligent traffic light management system using Faster R‐CNN

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CAAI Transactions on Intelligence technology 2024年第4期9卷 932-947页

作者： Syed Konain Abbas Muhammad Usman Ghani Khan Jia Zhu Raheem Sarwar Naif RAljohani Ibrahim AHameed Muhammad Umair Hassan Department of Computer science and Engineering University of Engineering and TechnologyLahorePakistan Zhejiang Key Laboratory of Intelligent Education technology and Application Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Faculty of Computing and Information technology King Abdulaziz UniversityJeddahSaudi Arabia Department of ICT and Natural sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

关键词： access control artificial intelligence computer vision intelligent control

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揭示鱼鳞降低冰黏附力的奥秘

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science China Materials 2024年第6期67卷 2016-2022页

作者：王锋刘思琪肖森波 Bjørn Skallerud 张志良何健英 Department of Structural Engineering Norwegian University of Science and Technology(NTNU)Trondheim 7491Norway Suzhou Laboratory Suzhou 215000China

近几十年来,大量的研究文献表明,研究人员一直在探究静态表面特性(包括自由能、韧性和弹性)对疏冰性的影响.然而,对于动态表面特性在辅助除冰方面的理解非常有限.在本工作中,我们重点研究了北三文鱼表皮的冰黏附强度,并且观察到了有趣... 详细信息

近几十年来,大量的研究文献表明,研究人员一直在探究静态表面特性(包括自由能、韧性和弹性)对疏冰性的影响.然而,对于动态表面特性在辅助除冰方面的理解非常有限.在本工作中,我们重点研究了北三文鱼表皮的冰黏附强度,并且观察到了有趣的各向异性的冰黏附行为.与顺着鱼鳞生长方向的冰黏附强度(353±95 kPa)相比,逆着鱼鳞生长方向的冰黏附强度(141±47 kPa)降低了60%.我们发现,鱼鳞在受到剪切力的过程中,会发生独特的结构演变,从而导致界面连续断裂,有利于降低冰的黏附性.研究发现,鱼鳞的张开和剥离能力(描述了鳞片在外力下与其下部鳞片和黏结物分离的趋势)可以调控冰的脱落.通过提高鱼鳞的张开和剥离能力,可以在鱼鳞上实现更低的冰黏附强度(66±15 kPa)和更为容易的除冰过程.由于鱼鳞具有出色的机械鲁棒性,这一发现为设计坚硬耐用的防覆冰表面提供了新的视角.

关键词： fish scale ice adhesion dynamic behaviors sequential rupture anti-icing

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Bayesian partial pooling to reduce uncertainty in overcoring rock stress estimation

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第4期16卷 1192-1201页

作者： Yu Feng Ke Gao Suzanne Lacasse norwegian Geotechnical Institute OsloNorway Department of Earth and Space sciences Southern University of Science and TechnologyShenzhenChina

The state of in situ stress is a crucial parameter in subsurface engineering,especially for critical projects like nuclear waste *** one of the two ISRM suggested methods,the overcoring(OC)method is widely used to estimate the full stress tensors in rocks by independent regression analysis of the data from each OC ***,such customary independent analysis of individual OC tests,known as no pooling,is liable to yield unreliable test-specific stress estimates due to various uncertainty sources involved in the OC *** address this problem,a practical and no-cost solution is considered by incorporating into OC data analysis additional information implied within adjacent OC tests,which are usually available in OC measurement ***,this paper presents a Bayesian partial pooling(hierarchical)model for combined analysis of adjacent OC *** performed five case studies using OC test data made at a nuclear waste repository research site of *** results demonstrate that partial pooling of adjacent OC tests indeed allows borrowing of information across adjacent tests,and yields improved stress tensor estimates with reduced uncertainties simultaneously for all individual tests than they are independently analysed as no pooling,particularly for those unreliable no pooling stress estimates.A further model comparison shows that the partial pooling model also gives better predictive performance,and thus confirms that the information borrowed across adjacent OC tests is relevant and effective.

关键词： Overcoring stress measurement Uncertainty reduction Partial pooling Bayesian hierarchical model Nuclear waste repository

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Development of bismuth-based solutions for well plugging and abandonment:A review

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Petroleum Research 2024年第2期9卷 250-264页

作者： Lewaa Hmadeh Marcelo Anunciação Jaculli Behzad Elahifar Sigbjørn Sangesland norwegian university of science and technology PTSValgrindaS.P.Andersens veg 15 ANorway

Plugging and abandonment(P&A)is a crucial step of the well life *** of how long one stretches the productive life of a well,P&A operations will have to be carried out *** current panorama of our industry includes many wells to be plugged and abandoned,with steep requirements to abide by both regulations and societal *** this context,we must guarantee that no leakage occurs with an eternal perspective in *** has been the prime material for this task,but recent studies have indicated the potential of degradation over time-especially in corrosive environments-and the creation of leaking paths due to its *** has opened up a path toward the usage of alternative *** of the emerging candidates is bismuth,a metal with the unique characteristic of expanding when *** a trait could improve the overall sealability of wellbores and especially during P&*** article discusses the current status of bismuth sealing technologies,introducing the basics of bismuth,the ongoing efforts to qualify it as a barrier material,its potential applications,and the challenges that still need to be *** latest research indicates promising results in terms of its usage as a barrier element.

关键词： Bismuth plugs Bismuth-tin alloys Well plugging and abandonment Well integrity

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Elasto-inertial focusing and particle migration in high aspect ratio microchannels for highthroughput separation

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Microsystems & Nanoengineering 2024年第3期10卷 381-394页

作者： Selim Tanriverdi Javier Cruz Shahriar Habibi Kasra Amini Martim Costa Fredrik Lundell Gustaf Mårtensson Luca Brandt Outi Tammisola Aman Russom Division of Nanobiotechnology Department of Protein ScienceScience for Life LaboratoryKTH Royal Institute of TechnologySolna 17165Sweden Division of Microsystems technology Department of Materials Science and EngineeringUppsala UniversityUppsala 75237Sweden FLOW and SeRC(Swedish e-science Research Centre) Department of Engineering MechanicsRoyal Institute of TechnologyStockholm SE 10044Sweden FLOW and Fluid Physics Laboratory Department of Engineering MechanicsRoyal Institute of TechnologyStockholmSweden Wallenberg Wood science Center Royal Institute of TechnologyStockholm SE 10044Sweden Department of Energy and Process Engineering Norwegian University of Science and Technology(NTNU)TrondheimNorway AIMES Center for the Advancement of Integrated Medical and Engineering sciences at Karolinska Institutet and KTH Royal Institute of technology StockholmSweden

The combination of flow elasticity and inertia has emerged as a viable tool for focusing and manipulating particles using *** there is considerable interest in the field of elasto-inertial microfluidics owing to its potential applications,research on particle focusing has been mostly limited to low Reynolds numbers(Re<1),and particle migration toward equilibrium positions has not been extensively *** this work,we thoroughly studied particle focusing on the dynamic range of flow rates and particle migration using straight microchannels with a single inlet high aspect *** initially explored several parameters that had an impact on particle focusing,such as the particle size,channel dimensions,concentration of viscoelastic fluid,and flow *** experimental work covered a wide range of dimensionless numbers(0.05

关键词： particle separation straight

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Flood Velocity Prediction Using Deep Learning Approach

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Journal of Geodesy and Geoinformation science 2024年第1期7卷 59-73页

作者： LUO Shaohua DING Linfang TEKLE Gebretsadik Mulubirhan BRULAND Oddbjørn FAN Hongchao Department of Civil and Environmental Engineering Norwegian University of Science and TechnologyTrondheim 7034Norway

Floods are one of the most serious natural disasters that can cause huge societal and economic *** research has been conducted on topics like flood monitoring,prediction,and loss *** these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the *** methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long *** learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional *** study explores the potential of deep learning models in predicting flood *** specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain *** data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP *** experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing ***,we discuss the limitations for the improvement in future work.

关键词： flood velocity prediction geographic data MLP deep learning

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