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Temperature and structure measurements of heavy-ion-heated diamond using in situ X-ray diagnostics

Matter and radiation at Extremes 2024年第4期9卷 80-89页

作者： J.Lutgert P.Hesselbach M.Schorner V.Bagnoud r.belikov P.Drechsel B.Heuser O.SHumphries P.Katrik B.Lindqvist C.Qu r.redmer D.riley G.Schaumann S.Schumacher A.Tauschwitz D.Varentsov K.Weyrich X.Yu B.Zielbauer Zs.Major P.Neumayer D.Kraus Institut fur Physik Universitat RostockAlbert-Einstein-Str.2318059 RostockGermany GSI Helmholtzzentrum fur Schwerionenforschung Planckstr.164291 DarmstadtGermany Institut für Angewandte Physik Goethe-Universität Frankfurt am MainMax-von-Laue-Str.160438 Frankfurt am MainGermany Institut fur Geowissenschaften Goethe-Universitat Frankfurt am MainAltenhoferallee 160438 Frankfurt am MainGermany Helmholtz-Zentrum Dresden-rossendorf Bautzner Landstr.40001328 DresdenGermany European XFEL GmbH Holzkoppel 422869 SchenefeldGermany Centre for Plasma Physics School of Mathematics and PhysicsQueen’s University BelfastUniversity RoadBelfast BT71NNUnited Kingdom Institut für Kernphysik Technische Universität DarmstadtSchlossgartenstr.964289 DarmstadtGermany State Key Laboratory of Nuclear Physics and Technology Institute of Heavy Ion PhysicsPeking UniversityBeijing 100871China Helmholtz Institut Jena Frobelstieg 307743 JenaGermany

We present in situ measurements of spectrally resolved X-ray scattering and X-ray diffraction from monocrystalline diamond samples heatedwith an intense pulse of heavy *** this way,we determine the samples’heating dynamics and their microscopic and macroscopic structuralintegrity over a timespan of several *** the ratio of elastic to inelastic scattering with state-of-the-art density functionaltheory molecular dynamics simulations allows the inference of average temperatures around 1300 K,in agreement with predictions fromstopping power *** simultaneous diffraction measurements show no hints of any volumetric graphitization of the material,butdo indicate the onset of fracture in the diamond *** experiments pave the way for future studies at the Facility for Antiproton andIon research,where a substantially increased intensity of the heavy ion beam will be available.

关键词： heated intense structure

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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

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Energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun ram Machlev Qianchao Wang Juri belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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Explainable Artificial Intelligence (XAI) techniques for energy and powersystems: review, challenges and opportunities

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能源与人工智能(英文) 2022年第3期9卷 193-205页

作者： r.Machlev L.Heistrene M.Perl K.Y.Levy J.belikov S.Mannor Y.Levron The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion—Israel Institute of TechnologyHaifa 3200003Israel Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia School of Technology Pandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia

Despite widespread adoption and outstanding performance, machine learning models are considered as ‘‘blackboxes’’, since it is very difficult to understand how such models operate in practice. Therefore, in the powersystems field, which requires a high level of accountability, it is hard for experts to trust and justify decisionsand recommendations made by these models. Meanwhile, in the last couple of years, Explainable ArtificialIntelligence (XAI) techniques have been developed to improve the explainability of machine learning models,such that their output can be better understood. In this light, it is the purpose of this paper to highlight thepotential of using XAI for power system applications. We first present the common challenges of using XAI insuch applications and then review and analyze the recent works on this topic, and the on-going trends in theresearch community. We hope that this paper will trigger fruitful discussions and encourage further researchon this important emerging topic.

关键词： Power Energy Neural network Deep-learning Explainable artificial intelligence XAI

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Explainability-based Trust Algorithm for electricity price forecasting models

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Energy and AI 2023年第4期14卷 141-158页

作者： Leena Heistrene ram Machlev Michael Perl Juri belikov Dmitry Baimel Kfir Levy Shie Mannor Yoash Levron Electrical Engineering Department School of TechnologyPandit Deendayal Energy UniversityGandhinagarGujarat382007India The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa3200003Israel Department of Software Science Tallinn University of TechnologyAkadeemia tee 15ATallinn12618Estonia Electrical&Electronics Engineering Department Sami Shamoon College of EngineeringBeer-Sheva84100Israel

Advanced machine learning(ML)algorithms have outperformed traditional approaches in various forecasting applications,especially electricity price forecasting(EPF).However,the prediction accuracy of ML reduces substantially if the input data is not similar to the ones seen by the model during *** is often observed in EPF problems when market dynamics change owing to a rise in fuel prices,an increase in renewable penetration,a change in operational policies,*** the dip in model accuracy for unseen data is a cause for concern,what is more,challenging is not knowing when the ML model would respond in such a *** uncertainty makes the power market participants,like bidding agents and retailers,vulnerable to substantial financial loss caused by the prediction errors of EPF ***,it becomes essential to identify whether or not the model prediction at a given instance is *** this light,this paper proposes a trust algorithm for EPF users based on explainable artificial intelligence *** suggested algorithm generates trust scores that reflect the model’s prediction quality for each new *** scores are formulated in two stages:in the first stage,the coarse version of the score is formed using correlations of local and global explanations,and in the second stage,the score is fine-tuned further by the Shapley additive explanations values of different *** score-based explanations are more straightforward than feature-based visual explanations for EPF users like asset managers and traders.A dataset from Italy’s and ErCOT’s electricity market validates the efficacy of the proposed *** show that the algorithm has more than 85%accuracy in identifying good predictions when the data distribution is similar to the training *** the case of distribution shift,the algorithm shows the same accuracy level in identifying bad predictions.

关键词： Electricity price forecasting EPF Explainable AI model XAI SHAP Explainability

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NN-ANArX Structure for Control of Nonlinear SISO and MIMO Systems: Neural Networks Based Approach

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第二十六届中国控制会议

作者： Petlenkov Eduard belikov Juri Tallinn University of Technology Department of Computer control Institute of Cybernetics at Tallinn University of Technology

ISBN: (纸本)7900719229;9787900719225

An application of Neural Networks based Additive Nonlinear Autoregressive Exogenous （NN-ANArX） structure for modeling and control of nonlinear SISO and MIMO systems is presented in the paper.A novel neural network based ap- proach for calculation of control signals by using NN-ANArX based dynamic output linearization algorithm is proposed in the *** effectiveness of the approach proposed in the paper is demonstrated on example

关键词： nonlinear control systems nonlinear MIMO systems ANArX model dynamic output feedback linearization neural networks

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A Novel Taylor Series Based Approach for Control Computation in NN-ANArX Structure Based Control of Nonlinear Systems

A Novel Taylor Series Based Approach for Control Computation...

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第二十七届中国控制会议

作者： belikov J Vassiljeva K Petlenkov E Nomm S Institute of Cybernetics at Tallinn University of Technology Department of Computer Control Tallinn University of Technology

ISBN: (纸本)9787900719706

This paper presents an alternative approach for control computation in a closed loop of discrete-time nonlinear system and NN-ANArX based dynamic output *** technique is based on an application of Taylor series expansion for computation of control directly from neural network based *** modifications of the algorithm are proposed for both single-input single-output and multi-input multi-output nonlinear *** effectiveness of the proposed approach is demonstrated on numerical examples.

关键词： Nonlinear control systems Linearization Neural networks

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Microperforation of the human nail plate by radiation of erbium lasers

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Frontiers of Optoelectronics 2017年第3期10卷 299-307页

作者： Andrey V. belikov Andrey N. SErGEEV Sergey N. SMIrNOV Anastasia D. TAVALINSKAYA Department of Laser Technologies and Systems Saint-Petersburg National Research University of Information Technologies Mechanics and Optics (ITMO University) Saint Petersburg 197101 Russia

The nail plate forms a barrier that limits the effectiveness of drug delivery in the treatment of nail diseases and prevents the outflow of fluid in the case of subungual hematoma formation. Microperforation of the nail plate through laser radiation can increase the effectiveness of drug delivery and ensure the possibility of blood outflow. This study detected and identified the type and threshold of effects that arise from exposing the nail plate to Yb,Er： Glass （λ = 1.54 μm） and Er：YLF （λ= 2.81 μm） laser radiation. The rate and efficiency of nail plate ablation by the radiation of these lasers were studied. The effect of the storage time of a freshly extracted nail plate in open air on its ablation rate by Er：YLF （ λ=2.81 μm） laser radiation was also investigated. The impact of the Yb,Er：Glass and Er：YLF laser pulses on the nail plate caused bleaching, carbonization, ablation with microcrater formation, and microperforation. The laser energy densities WE （thresholds） required for these effects were determined. The maximum ablation rate for Yb,Er：Glass laser radiation was 8 μm/pulse at WE = 91 ±2 J/cm2, whereas that for Er：YLF laser radiation was 12 μm/ pulse at WE= 10.5＋0.5 J/cm2. The maximum ablation efficiency for Yb,Er：Glass laser radiation was 0.1 μm/mJ at Ws = 10.5±0.5 J/cm2, whereas that for Er：YLF laser radiation was 4.6 μm/mJ at WE = 5.3±0.3 J/cm2. The laser ablation rate depends on the storage time and conditions of the freshly extracted nail plate. For example, when exposed to Er：YLF laser radiation, the laser ablation rate decreased by half from the initial maximum value in 96 h of air storage and returned to the initial value after 1 h of storage in distilled water.

关键词： Yb Er:Glass laser Er:YLF laser nail plate microperforation ablation rate ablation efficiency dehydration

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Comparison of diode laser continuous wave and in soft tissue surgery using pulsed modes in vitro

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Frontiers of Optoelectronics 2015年第2期8卷 212-219页

作者： Andrey V. belikov Alexei V. SKrYPNIK Ksenia V. SHATILOVA Saint-Petersburg National research University of Information Technologies Mechanics and Optics (ITMO University) Saint-Petersburg 197101 Russia

In this study, the interaction between diode laser radiation and chicken soft tissue was studied in vitro by a high-speed digital video camera. We used a diode laser with a wavelength of （980 ±10）nm and average power of 10 W. The diode laser was operated in continuous wave （CW） and pulsed modes. In CW mode, the average laser radiation power was 10 W; in pulsed mode, the average laser radiation power was I0 W and the peak power was 20 W. Diode laser radiation was delivered to soft tissue （chicken meat） using a quartz optical fiber with either a clear distal end （clear tip） or a distal end containing an optothermal converter （hot tip）. Application of the diode laser in pulsed mode resulted in crater depths and areas of collateral damage in soft tissue about 1.6 times greater than those observed in CW mode at treatment with the clear tip. Significant differences in the crater depth and collateral damage width of chicken meat were not found after hot-tip treatment with the diode laser in CW and pulsed modes. Soft tissue treated with the hot tip showed crater depths about 3.4 times greater than those observed after treatment with the clear tip. Hot tip treatment further resulted in collateral damage widths about 2.7 times lower than those obtained after treatment with the clear tip.