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Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

Nuclear Science and Techniques 2017年第3期28卷 59-67页

作者： Yue Zhao francesco di maio Enrico Zio Qin Zhang Chun-Ling Dong Jin-Ying Zhang Institute of Nuclear and New Energy Technology of Tsinghua University Beijing 100084 China Energy Department Politecnico di Milano 20156 MilanItaly Chair System Science and the Energy Challenge Fondation Electricite′ de France (EDF) CentraleSupe′lec Universite Paris Saclay 92290 Chatenay-Malabry France Department of Computer Science and Technology Tsinghua University Beijing 100084 China Department of Economic and Management North China Electric Power University Beijing 102206 China

Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neurofuzzy approaches, support vector machine, K-nearest neighbor classifiers and inference methodologies. Among these methods, dynamic uncertain causality graph(DUCG)has been proved effective in many practical cases. However, the causal graph construction behind the DUCG is complicate and, in many cases, results redundant on the symptoms needed to correctly classify the fault. In this paper, we propose a method to simplify causal graph construction in an automatic way. The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree(FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT. Genetic algorithm(GA) is, then, used for the optimization of the FDT, by performing a wrapper search around the FDT: the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system. The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation. The results show that the FDT, with GA-optimized symptoms and diagnosis strategy, can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.

关键词： Dynamic uncertain causality graph Fault diagnosis Classification Fuzzy decision tree Genetic algorithm Nuclear power plant

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Release behavior of soluble salts in MSWI bottom ash used as road basement materials under continuous rainfall conditions

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Waste disposal and Sustainable Energy 2023年第4期5卷 525-534页

作者： Lingqin Zhao Dongming Zhang Yanjun Hu Qianqian Guo Long Jiao Nan Zhou francesco di maio Institute of Thermal and Power Engineering Zhejiang University of TechnologyLiuhe Road 28#310023HangzhouChina Zhejiang Zheneng Xingyuan Energy Saving Technology Co.Ltd Gongshu District310011HangzhouChina Delft University of Technology P.O.Box 50482628DelftThe Netherlands

The bottom ash is increasingly used as a substitute aggregate material in road construction in China,and road salting is the major salt source in *** rainfall releases soluble salts from the bottom ash subgrade into the surrounding soil and groundwater,resulting in potential *** methods were employed to simulate and collect runoff water during rainfall events,including batch leaching test,dynamic leaching test and constant head test,to assess environmental impact of bottom ash as road basement materials under continuous rainfall *** study simulated the seepage of bottom ash backfill roads under different rainfall intensities,rainfall times,and rainfall pH values.A comprehensive sampling and laboratory testing program was undertaken to characterize the environmental impact of soluble salts from bottom *** obtained results reveal that the leaching concentrations of Cl^(−)and SO_(4)^(2−)exceed the limit specified in the class V standard of surface water,which are 2.06–2.17 times and 1.08–1.25 times,*** examining the long-term environmental influence under the condition of continuous rainfall,the leaching of Cl^(−)mainly occurs in the early leaching stage,and the maximum leaching concentration reaches 19,700 mg/*** release concentration of Cl^(−)begins to be lower than the class V standard of surface water when continuous rainfall approaches the total rainfall for 13 *** cumulative release of Cl^(−)in the bottom ash is 2.8–5.4 mg/*** rainfall intensity and rain pH affect the release of Cl^(−).The obtained results derived from the constant head tests indicate that stagnant water caused by rainfall deteriorates the release of soluble salt into the groundwater in only 1 day,especially at the early stage of 12 *** work provides some basic information about how to minimize damage to the surrounding environment caused by the leaching of salt in bottom ash.

关键词： Municipal solid waste Incineration bottom ash Salts Leaching Continuous rainfall

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城市固体废弃物焚烧底灰理化特性研究

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太阳能学报 2008年第10期29卷 1187-1191页

作者：胡艳军陈冠益 francesco di maio 天津大学环境学院 Delft University of Technology Faculty of Civil Enginnering and GeosciencesStevinweg 1 2628 CN DelftThe Netherlands Delft University of Technology Faculty of Civil Enginnering and GeosciencesStevinweg 12628 CN DelftThe Netherlands

通过对天津市某垃圾焚烧发电厂的底灰按照粗颗粒(颗粒粒径>4.75mm)、细颗粒(颗粒粒径<4.75mm)分类,系统地研究了其化学成分、粒径分布、物理组成、吸水性、压实性、砂当量、表干密度、表面密度、饱和密度、颗粒矿物形态等物理化学特性... 详细信息

通过对天津市某垃圾焚烧发电厂的底灰按照粗颗粒(颗粒粒径>4.75mm)、细颗粒(颗粒粒径<4.75mm)分类,系统地研究了其化学成分、粒径分布、物理组成、吸水性、压实性、砂当量、表干密度、表面密度、饱和密度、颗粒矿物形态等物理化学特性以及不同液固比条件下重金属浸出毒性的环境质量评价。结果表明,底灰的物化特性主要受硅和钙等几种主要成分质量分数的影响,属于具有高多孔率、与天然矿物质有相似成分、吸水性较高的轻质材料,同时满足建筑材料的大多数工程特性要求,但应用时仍需注意环境影响。文章旨在为今后的底灰的资源化利用和批量处理以及环境保护提供理论依据。

关键词：城市生活垃圾焚烧底灰重金属理化特性资源利用

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A Robust Indicator for Promoting Circular Economy through Recycling

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Journal of Environmental Protection 2015年第10期6卷 1095-1104页

作者： francesco di maio Peter Carlo Rem Delft University of Technology Delft The Netherlands

In order to move towards a more sustainable development, it is necessary not only to minimize the use of materials in the design stage and to find new materials as alternatives to nonrenewable ones (e.g. optical fiber instead of copper, biopolymers instead of polymers from oil) but also to reclaim as much as possible material value through effective recycling. To this extent, recycling can play a key role in multiple dimensions, while providing new business opportunities for innovative companies, having positive impacts on the society and the environment and fostering an effective circular economy as well. Because of the advanced waste management infrastructures available in developed countries, it is possible to achieve an almost complete collection of solid wastes into a variety of controlled bulk material flows. However, the picture for the follow-up step, the recycling of raw materials such as steel, non-ferrous metals, polymers and glass from these flows, is less positive. Materials value recovered from waste represents a very small fraction of European GDP. The fundamental issue is that policymakers still lack an effective key performance indicator for stimulating the recycling industry. Therefore although recycling plays an important role in the circular economy perspective, it is necessary to radically change the metric used so far to compute the recycling rate. Nowadays, the recycling rate is computed measuring the amount of material entering the recycling facilities. This approach has brought about an inaccurate and somehow misleading indicator (the recycling rate) which contributed to wrong decision making and to poor innovation in the industry. The new approach proposed in this paper considers the use of a Circular Economy Index (CEI) as the ratio of the material value produced by the recycler (market value) by the intrinsic material value1 entering the recycling facility. It is argued that this index is related to strategic, economic and environmental a

关键词： Recycling Recycling Rate Innovation Policy Resource Efficiency Indicators

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Investigating epithelial-neuronal signaling contribution in visceral pain through colon organoid-dorsal root ganglion neuron co-cultures

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Neural Regeneration Research 2024年第6期19卷 1199-1200页

作者： francesco Margiotia Lorenzo di Cesare Mannelli Antonino Morabito Carla Ghelardini Elena Lucarini Department of Neuroscience Psychology Drug Research and Child Health-NEUROFARBA-Pharmacology and Toxicology Section University of Florence Department of Neuroscience Psychology Drug Research and Child Health-NEUROFARBA University of Florence 3. Meyer Children's Hospital IRCCS

Abdominal pain is a common symptom associated with irritable bowel syndrome and inflammatory bowel diseases(IBDs), affecting about 20% of the global population(Grundy et al., 2019). Current pain therapies are poorly effective on visceral pain of intestinal origin and present several side effects, hence the need to identify novel molecular and cellular targets for drug development. The pathophysiology of visceral-abdominal pain,

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Tribological behavior of shape-specific microplate-enriched synovial fluids on a linear two-axis tribometer

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Friction 2024年第3期12卷 539-553页

作者： Agnese FRAGASSI Antonietta GRECO Martina di francesco Luca CESERACCIU Aiman ABU AMMAR Israel DVIR Thomas Lee MOORE Haytam KASEM Paolo DECUZZI Laboratory of Nanotechnology for Precision Medicine Fondazione Istituto Italiano di TecnologiaGenova 16163Italy Department of Chemistry and Industrial Chemistry University of GenovaGenoa 16146Italy Materials Characterization Facility Istituto Italiano di TecnologiaGenova 16163Italy Department of Pharmaceutical Engineering Azrieli College of Engineering JerusalemJerusalem 9103501Israel Department of Mechanical Engineering Azrieli College of Engineering JerusalemJerusalem 9103501Israel

Nano-and micro-particles are being increasingly used to tune interfacial frictional properties in diverse applications,from friction modifiers in industrial lubrication to enhanced biological fluids in human osteoarthritic ***,we assessed the tribological properties of a simulated synovial fluid enriched with non-spherical,poly lactic-co-glycolic acid(PLGA)microparticles(μPL)that have been previously demonstrated for the pharmacological management of osteoarthritis(OA).Three different μPL configurations were fabricated presenting a 20μm×20μm square base and a thickness of 5μm(thin,5H μPL),10μm(10H μPL),and 20μm(cubical,20H μPL).After extensive morphological and physicochemical characterizations,the apparent Young’s modulus of the μPL was quantified under compressive loading returning an average value of~6 kPa,independently of the particle ***,using a linear two-axis tribometer,the static(μ_(s))and dynamic(μ_(d))friction coefficients of the μPL-enriched simulated synovial fluid were determined in terms of particle configuration and concentration,varying from 0(fluid only)to 6×10^(5) μPL/*** particle morphology had a modest influence on friction,possibly because the μPL were fully squeezed between two mating surfaces by a 5.8 N normal load realizing boundary-like lubrication ***,friction was observed to depend on the dimensionless parameterW,defined as the ratio between the total volume of the μPL enriching the simulated synovial fluid and the volume of the fluid *** coefficients of friction were documented to grow withWreaching a plateau of μ_(s)~0.4 and μ_(d)~0.15,already at Ω~2×10^(-3).Future investigations will have to systematically analyze the effect of sliding velocity,normal load,and rigidity of the mating surfaces to elucidate in full the tribological behavior of μPL in the context of osteoarthritis.

关键词： osteoarthritis microparticles tribology synovial fluid pin on plate

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人工智能面临的复杂性挑战

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自然辩证法研究 2024年第6期40卷 72-77页

作者：任然 francesco di Iorio 南开大学哲学院天津300350

随着近年来人工智能和复杂性科学的发展,复杂性挑战不仅延续到智能系统中,而且围绕着计算复杂性问题展开。生成式人工智能的兴起彻底颠覆了以往对复杂性问题的认知,不仅涉及智能系统的复杂性,而且涉及自然系统的复杂性,探讨了许多新的问... 详细信息

随着近年来人工智能和复杂性科学的发展,复杂性挑战不仅延续到智能系统中,而且围绕着计算复杂性问题展开。生成式人工智能的兴起彻底颠覆了以往对复杂性问题的认知,不仅涉及智能系统的复杂性,而且涉及自然系统的复杂性,探讨了许多新的问题,例如如何解决“生成难度”问题,提出了一些应对挑战的方法论原则,例如奥卡姆剃刀原则,深化了我们对有关认识论和方法论问题的思考。

关键词：人工智能计算复杂性生成式人工智能复杂性挑战

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Two big orifices in the second duodenal portion:A case of an atypical double papilla

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Hepatobiliary & Pancreatic diseases International 2024年第1期23卷 83-85页

作者： Salvatore francesco Vadalàdi Prampero Nikola Panic Marco Massidda Chiara Rocchi Pierluigi Maria Rinaldi Ana Malenkovic Milutin Bulajic Gastroenterology and GI Endoscopy Department Mater Olbia HospitalOlbia 07026Italy digestive Endoscopy Unit University Clinic"Dr Dragisa Misovic-Dedinje"Belgrade 11000Serbia Radiology Department Mater Olbia HospitalOlbia 07026Italy

With the advent of endoscopic retrograde cholangiopancreatography(ERCP)in the early 1970s,anatomic anomalies of the Vaterian system were described endoscopically[1].Although the occurrence is rare,the common bile duct(CBD)and the pancreatic duct may fail to coalesce during embryologic *** leads to double major papilla because both ducts open into the duodenum separately[1].In this way the cranial duct communicates with the CBD,while the caudal orifice communicates with the pancreatic duct[2].

关键词： orifice Vater atypical

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Autonomous Vehicle Platoons In Urban Road Networks:A Joint distributed Reinforcement Learning and Model Predictive Control Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 141-156页

作者： Luigi D’Alfonso francesco Giannini Giuseppe Franzè Giuseppe Fedele francesco Pupo Giancarlo Fortino IEEE the Department of Computer Engineering ModelingElectronics and SystemsUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy the Department of Mechanical Engineering Energy Engineering and ManagementUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy

In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the a

关键词： distributed model predictive control distributed reinforcement learning routing decisions urban road networks

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Impact characterization on thin structures using machine learning approaches

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Chinese Journal of Aeronautics 2024年第2期37卷 30-44页

作者： Flavio diPIETRANGELO francesco NICASSIO Gennaro SCARSELLI Department of Engineering for Innovation University of SalentoLecce 73100Italy

Machine learning algorithms are trained and compared to identify and to characterise the impact on typical aerospace panels of different *** activities are conducted to build a proper impacts’*** regression algorithm and artificial neural network are applied and optimised to panels without stringer to test their capability to identify the ***,the algorithms are applied to panels reinforced with stringers that represent a significant increase of complexity in terms of dynamic features of the system to test:the focus is not only on the impact position’s detection but also on the event’s *** the identification of the best algorithm,the corresponding machine learning model is deployed on an ARM processor minicomputer,implementing an impact detection system,able to be installed on board an aerial vehicle,making it a smart aircraft equipped with an artificial intelligence decision-making system.

关键词： Artificial neural network Impact localisation Machine learning Polynomial regression Structural health monitoring

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