清江学术论坛
报告题目：激光粉末床融熔过程中熔池动力学模拟仿真研究
报告人：周宗彦教授
时 间：2025年10月23日(周四)14:30
地 点：南昌校区综合实验楼A308报告厅
报告人简介：
周宗彦，江西理工大学国际创新研究院特聘教授，博士生导师。曾任新南威尔士大学讲师、蒙纳士大学高级讲师和兼职教授以及澳大利亚科研理事会颗粒计算中心副主任。江西省双千计划创新领军人才、颗粒技术江西省重点实验室主任，中国科协海智计划特聘专家。长期从事于对散料体系统、多相流以及传热传质的基础研究，和工业过程(矿冶、化工和增材制造等)的应用研究；在阐明多相流动体系模拟理论和建立数值实验优化方法等科学问题上取得显著学术突破。以第一/通讯作者发表SCl论文160余篇，主持/参与了10余项国家级基金项目，指导毕业博士生20余名；受邀国内外会议特邀报告20余次；任学术期刊PowderTechnology编委，担任多种国际权威学术刊物评阅专家。
摘 要：
粉末床熔融已成为航空航天、生物医学和汽车工业中成功的工业化生产技术之一。在此工艺中，使用涂布器将薄层细金属粉末均匀铺粉，每一层粉末都由激光束熔融，然后凝固形成固态金属零件。粉末床熔融工艺仍面临许多重大挑战，其中之一是如何控制制造零件中产生的缺陷，例如孔隙、未熔合孔、裂纹等。在本研究中，我们采用数值模拟手段研究了粉末床熔合过程，采用离散元法用于研究粉末铺展，旨在探究粉末特性和操作参数如何影响粉末床的填充特性；计算流体力学用于研究金属粉末的熔化和随后的凝固过程。例如，气液界面附近的熔融液体发生离心流动，产生包括顺时针和逆时针旋涡在内的涡流，从而影响气泡流动特性以及匙孔生命周期。结果表明，粉末床熔融模拟可以有效揭示粉末床熔合中的多物理场规律及缺陷形成机制。
清江学术论坛
报告题目：Research on Entity Alignment Over the Cross-lingual Knowledge Graphs
报告人：Muhammad USman Akhta
时 间：2025年10月23日(周四)14:30
地 点：南昌校区综合实验楼A308报告厅
报告人简介：
Muhammad Usman Akhtar,自2024年7月起担任西北工业大学软件学院博士后研究员，此前于2024年7月在武汉大学获得软件工程博士学位。己发表学术论文10余篇，累计影响因子超过35.77。拥有十余年软件工程领域的学术与研究经验，长期致力于人工智能与非结构化数据相关研究。积极与学术界及工业界伙伴开展合作，并担任《Knowledge-Based Systems》、《Information Fusion》、《Engineering Applications of Artificial Intelligence》等高影响力期刊的独立审稿人，累计审稿逾440篇(ORCID记录https://orcid.org/O000-0002-5389-1156)。致力于通过前沿学术研究与国际合作，推动全球科技创新，助力构建面向未来的AI解决方案。
摘 要：
Entity alignment(EA)seeks to identify similar real-world objects in different mulilingualknowledge graphs(Kgs),also known as ontology alignment.EA assists in handling a wide range oflanguage semantics and in building integrated knowledge bases.However,most mainstream studieshave focused on structural information,paying little attention to insufficient contextual information andlimited handling of complex relationships.This paper aims to address these limitations and improveEA performance and efficiency.
Methods:
This paper investigates multilingual EA techniques and proposes a novel Abductive KnowledgeReasoning(AKR)model to address these issues.AKR can compute complex relationship semanticscontext by reasoning and enrich counterpart entity contextual information through centralitycalculation,which helps connect distant entities in multilingual Kgs.
Novelty:
The proposed AKR model introduces a new approach to EA by integrating centrality calculationand relational semantics reasoning.This method overcomes the limitations of existing EA techniques byeffectively handling insufficient contextual information and complex relationships in multilingual Kgs.
Findings:
AKR outperforms all state-of-the-art EA models across five datasets.AKR achieves Hit @1score of 79.4%,for entity alignment between Chinese-to-English knowledge graphs representing19.9%improvement over the best-performing translation-based model,Neighborhood-AwareAttentional Representation Entity Alignment,and a 5.0%improvement over the best-performinggraph neural network-based model,Relational Semantics Augmentation.
清江学术论坛
报告题目：Prognostic Maintenance of Wind Turbine Rotor-Bearing System
报告人：Khandaker Noman博士
时 间：2025年10月23日(周四)14:30
地 点：南昌校区综合实验楼A308报告厅
报告人简介：
Khandaker Noman博士，毕业于上海交通大学机械工程学院，现任西北工业大学民航学院副教授，硕士生导师。长期助力于复杂装备的故障预测与健康管理方向的研究。先后主持“国际青年科学家研究基金项目”、“国际优秀青年科学家研究资金”项目等国家级、省部级项目8项。共发表SCI论文50篇，英文专著1本。目前，他担任国际知名期刊《Journal of Intelligent Manufacturing》(中科院二区，IF=7.4)、《Non-destructive Testing and Evaluation》(中科院二区，IF=4.2)的"副主编”,和《Measurement》(中科院二区，IF=5.6)“顾问委员会成员”。以“主旨发言人”、“副主席”、“特邀发言人”和“会议主席”等身份参加过10余次著名国际会议。曾获得中国江苏省“企业家和创新人才”称号以及《Machines Young Investigator Award》(全球唯一)。
摘 要：
In order to address the need of achieving UN carbon neutrality plan laid out by the Paris climateagreement in 2016,signing countries are focusing more and more on the renewable energygeneration.As a result,wind energy industry has become a center of attractions for researchers.Continuous and uninterruptable generation of wind energy can not only reduce our dependence onfossil fuel energy but also can ensure the energy security of the countries.Hence,propermaintenance of wind turbine components can facilitate the reduction of wind energy production cost,ensure the high yield and prevent accidents happening in the wind farms.In this context,wind turbinerotor-bearing system maintenance is of utmost importance due to its role in generating the highestamount of wind turbine failure.To this end,in compare to tradition condition based maintenance ofwind turbine rotor-bearing system,prognostic maintenance can bring the essence of predictivemaintenance in the analysis domain.A successful prognostic maintenance not only ensures thedetection of defect at the earliest point of inception but also ensures the tracking of fault in consistentmanner.Furthermore,it also facilitates the prediction of remaining useful life of the faulty wind turbinerotor-bearing system.Considering all the aforementioned aspects,this lecture will focus on theresearch on prognostic maintenance of wind turbine rotor-bearing system.
清江学术论坛
报告题目：Mechanical Integrity Assessments Challenges forthe Additively Manufactured Gas Turbine Components
报告人：WENKE PAN博士
时 间：2025年10月23日(周四)14:30
地 点：南昌校区综合实验楼A308报告厅
报告人简介：
Professor Wenke Pan received his bachelor degree from DalianUniversity of Technology,Master degree from Beijing University of Aeronauticsand Astronautics and PhD degree in Computational Solid Mechanics fromInstitute of Mechanics,Chinese Academy of Science.After this,he worked aspost-doctoral researcher at several top Chinese and UK universities includingUniversity of Science and Technology of China,Cardiff University,NottinghamUniversity,Glasgow University and Strathclyde University.He was a lecturer atStrathclyde University(UK)for about four years before he joined SiemensIndustrial Turbomachinery Ltd (UK)as a Principal Analytical Engineer in 2012.Hewas later promoted to Lead Analytical Engineer and responsible for MechanicalIntegrity Assessments for the key components of Siemens gas turbines.
Some important projects he worked for Siemen include:(1)SGT-600 pilotburner thermal mechanical fatigue design and optimization using additivemanufacture technology;(2)SGT-40013MW first stage additive manufacturedcompressor turbine blade(CTB)mechanical integrity assessments and (3)dynamic strain gauge testing and assessments of the SGT-300 twin shaftengine 1st and 2nd stage CTBs,etc.These works either shorten the product'stime to market dramatically or reduce the product's cost significantly.
Specializing in high temperature gas turbine material constitutive modelling,he has pioneered a novel ideawith introducing a parameter transformation method for creep theta-projection model,which allows efficientimplicit finite element implementation and enhances both accuracy and computational performance.
摘 要：
Additively manufactured components have been widely used for the key components in aero engines andindustrial gas turbines.The successful examples include the Iron-man like personal fly jet suits,gas turbinenozzle cooling passage design and the repairing of the compressor blades,etc.The technology is used not onlyto improve the engine performance,but also to reduce the manufacturing time and cost.However,as theadditive manufacturing process is similar to the welding process,the material behavior of the additivelymanufactured components is different from the conventional casting material,especially the creep deformationproperties,it is necessary to perform the detailed mechanical integrity assessments for these types ofcomponents.
In this presentation,it first introduces some examples of the additively manufactured mini jet engines,thenlists the gas turbine main components which could potentially be manufactured or repaired using the AMtechnology.The next section focuses on the reasons why the AM technology is important.This is then followedby the detailed application of AM technology used to manufacture some of the Siemens/Siemens Energy andGE industrial gas turbine components.For any gas turbine key components manufactured using AMtechnology,the mechanical integrity assessments have to be performed.The presentation highlights the mainchallenges where the eleven key aspects are itemized with some of them have been discussed.Finally,theconclusions are given.
