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Modal Frequency prediction of Chladni patterns Using Machine Learning

Open Journal of Acoustics 2024年第1期12卷 1-16页

作者： Atul kumar k. p. Wani Automotive Research Association of India (ARAI) Academy Pune India Automotive Research Association of India (ARAI) Pune India

The introduction of machine learning (ML) in the research domain is a new era technique. The machine learning algorithm is developed for frequency predication of patterns that are formed on the Chladni plate and focused on the application of machine learning algorithms in image processing. In the Chladni plate, nodes and antinodes are demonstrated at various excited frequencies. Sand on the plate creates specific patterns when it is excited by vibrations from a mechanical oscillator. In the experimental setup, a rectangular aluminum plate of 16 cm x 16 cm and 0.61 mm thickness was placed over the mechanical oscillator, which was driven by a sine wave signal generator. 14 Chladni patterns are obtained on a Chladni plate and validation is done with modal analysis in Ansys. For machine learning, a large number of data sets are required, as captured around 200 photos of each modal frequency and around 3000 photos with a camera of all 14 Chladni patterns for supervised learning. The current model is written in python language and model has one convolution layer. The main modules used in this are Tensor Flow keras, Numpy, CV2 and Maxpooling. The fed reference data is taken for 14 frequencies between 330 Hz to 3910 Hz. In the model, all the images are converted to grayscale and canny edge detected. All patterns of frequencies have an almost 80% - 99% correlation with test sample experimental data. This approach is to form a directory of Chladni patterns for future reference purpose in real-life application. A machine learning algorithm can predict the resonant frequency based on the patterns formed on the Chladni plate.

关键词： Chaldni pattern Modal Analysis Machine Learning Resonant Frequency Image processing

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Direct scaling of residual displacements for bilinear and pinching oscillators

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 129-149页

作者： Mohammad Saifullah Vinay k.Gupta Department of Civil Engineering Indian Institute of Technology KanpurKanpur 208016India

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the *** attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model *** of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not *** statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model *** proposed scaling model is applicable to horizontal ground motions in the western *** earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

关键词： residual displacement spectrum bilinear hysteresis model pinching hysteresis model nonlinear analysis scaling model

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Analysis of the Oscillatory Flows of Multiple Shock Waves in a Constant Area Duct

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Journal of Thermal Science 2024年第3期33卷 794-806页

作者： k JAMES Jintu kIM Heuy Dong Department of Mechanical Engineering Andong National UniversityAndong36729Republic of Korea CAD-IT korea Co. Ltd.Seoul08591Republic of Korea

The oscillatory response of multiple shock waves to downstream perturbations in a supersonic flow is studied numerically in a rectangular *** shock waves are formed inside the duct at a shock Mach number of *** duct has an exit height of H,and the effect of duct resonance on multiple shock oscillations is investigated by attaching exit ducts of lengths 0H,50H,and *** downstream disturbance frequency varied from 10 Hz to 200 Hz to explore the oscillation characteristics of the multiple shock *** oscillatory response of shock waves under self-excited and forced oscillation conditions are analyzed in terms of wall static pressure,shock train leading-edge location,shock train length,and the size of the separation *** extent of the initial shock location increases with an increase in exit duct length for the self-excited oscillation *** analysis of the shock train leading edge and the spectral analysis of wall static pressure variations are *** variation in the shock train length is analyzed using the pressure ratio method for self-excited as well as forced *** RMS amplitude of the normalized shock train length(ζ_(ST))increases with an increase in the exit duct length for the self-excited oscillation *** the downstream perturbation frequency is increased,ζ_(ST)is decreased for exit duct *** all exit duct designs and downstream forcing frequencies,the size of the separation bubble grows and shrinks during the shock oscillations,demonstrating the dependence on duct resonance and forced oscillations.

关键词： shock train downstream disturbance supersonic flow shock wave boundary layer interaction duct resonance flow separation

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Impact of Fin Arrangement on Heat Transfer and Melting Characteristics of phase Change Material

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Journal of Thermal Science 2024年第2期33卷 435-456页

作者： Arun UNIYAL Yogesh k.pRAJApATI Department of Mechanical Engineering National Institute of Technology UttarakhandSrinagar(Garhwal)246174India Department of Mechanical Engineering BIT SindriDhanbadJharkhand828123India

present work investigates the heat transfer and melting behaviour of phase change material(pCM) in six enclosures(enclosure-1 to 6) filled with paraffin *** enclosures are equipped with distinct arrangements of the fins while keeping the fin's surface area equal in each *** analysis has been presented to recognize the suitable fin arrangements that facilitate improved heat transfer and melting rate of the *** wall of the enclosure is maintained isothermal for the temperature values 335 k,350 k and 365 *** length of the enclosure including fins is ranging between 0 and *** have been illustrated through the estimation of important performance parameters such as energy absorbing capacity,melting rate,enhancement ratio,and Nusselt *** has been found that melting time(to melt 100% of the pCM) is 60.5%less in enclosure-2(with two fins of equal length) as compared to the enclosure-1,having no *** the fin surface area equal,if the longer fin is placed below the shorter fin(enclosure-3),melting time is further decreased by 14.1% as compared to ***,among all the configurations,enclosure-6 with wire-mesh fin structure exhibits minimum melting time which is 68.4% less as compared to the *** on the findings,it may be concluded that fins are the main driving agent in the enclosure to transfer the heat from heated wall to the *** design and positioning of the fins improve the heat transfer rate followed by melting of the pCM in the entire area of the *** of the favourable vortices and natural convection current in the enclosure accelerate the melting phenomenon and help to reduce charging time.

关键词： phase change material enclosure fin melting fraction energy storage heat transfer

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An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

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China Communications 2024年第2期21卷 258-269页

作者： p pabitha Anusha Jayasimhan Department of Computer Technology Anna UniversityMadras Institute of Technology CampusChennai 600044India

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOps with a degradation of just 0.11% accuracy.

关键词： CNN deep learning image classification model compression

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On the functions of astrocyte-mediated neuronal slow inward currents

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Neural Regeneration Research 2024年第12期19卷 2602-2612页

作者： Balázs pál Department of physiology Faculty of MedicineUniversity of DebrecenDebrecenHungary

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of *** events are significantly slower than the excitatory postsynaptic *** of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto *** are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback *** as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological *** is a growing body of evidence on the roles of slow inward currents on a single neuron or local network *** events often occur in synchro ny on neurons located in the same astrocytic *** synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic *** addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory *** note,there might be important regionspecific differences in the roles and actions triggering slow inward *** greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological *** inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural *** inward currents are significant contributors to paroxysmal depolarizational shifts/interictal *** events are related to epilepsy,but also found in Alzheimer's disease,parkinson's disease,and stroke,leading to the decline of cognitive *** with features overlapping with slow inward currents(excitatory,N-methyl-Dasp

关键词： astrocyte cortical spreading depolarization gliotransmission glutamate neural synchronization NMDA receptor paroxysmal depolarizational shift slow inward current

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Wormhole solutions under the effect of dark matter in f(R,L_(m))gravity

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Communications in Theoretical physics 2024年第5期76卷 102-113页

作者： Lakhan V Jaybhaye Moreshwar Tayde pk Sahoo Department of Mathematics Birla Institute of Technology and Science-PilaniHyderabad CampusHyderabad-500078India

In the background of f(R,L_(m))gravity,this work investigates three distinct dark matter halo profiles to test the possibility of generalised wormhole geometry within the galactic halo *** current study aims to accomplish these goals by examining various dark matter profiles including universal rotation curves(URC),Navarro-Frenk-White(NFW)model-Ⅰ,and NFW model-Ⅱinside two distinct f(R,L_(m))gravity *** to the f(R,L_(m))=R/2+L^(a)_(m)model,the dark matter(DM)halo density profiles produce suitable shape functions that meet all the necessary requirements for exhibiting the wormhole geometries with appropriate choice of free *** addition,to examine DM profiles under the f(R,L_(m))=R/2+(1+λR)L_(m) model,we consider a specific shape ***,we observed that the derived solution from both two models violates the null energy constraints,confirming that the DM supports wormholes to maintain in the galactic halo.

关键词： f(R L_(m))gravity wormhole dark matter(Some figures may appear in colour only in the online journal)

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Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

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Applied Mathematics and Mechanics(English Edition) 2024年第9期45卷 1613-1632页

作者： k.CHANDAN k.kARTHIk k.V.NAGARAJA B.C.pRASANNAkUMARA R.S.VARUN kUMAR T.MUHAMMAD Amrita School of Artificial Intelligence Amrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of Studies in Mathematics Davangere UniversityDavangere 577002KarnatakaIndia Computational Science Lab Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of pure and Applied Mathematics School of Mathematical SciencesSunway UniversityPetaling Jaya 47500Malaysia Department of Mathematics College of ScienceKing Khalid UniversityAbha 61413Saudi Arabia

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium(LTNE)*** governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled,and then are nondimensionalized by suitable dimensionless ***,the obtained nondimensional equations are solved by the clique polynomial method(CpM).The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical ***,the current study implements deep neural structures to solve physics-governed coupled equations,and the best-suited hyperparameters are attained by comparison with various network *** results of the CpM and physicsinformed neural network(pINN)exhibit good agreement,signifying that both methods effectively solve the thermal modeling problem.

关键词： heat transfer fin porous fin local thermal non-equilibrium(LTNE)model physics-informed neural network(pINN)

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Direct-Seeded Rice: Genetic Improvement of Game-Changing Traits for Better Adaption

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Rice science 2024年第4期31卷 417-433页

作者： priyanka NEGI Jagadish RANE Rajendra Sadashiv WAGH Tukaram Jayaram BHOR Dipti Digambar GODSE priyanka JADHAV C.ANILkUMAR Dasari SREEkANTH k.SAMMI REDDY Sharad Ramrao GADAkH k.M.BORAIH C.B.HARISHA p.S.BASAVARAJ Indian Council of Agricultural Research(ICAR)-National Institute of Abiotic Stress Management Baramati 413115India Mahatma phule krishi Vidyapeeth Rahuri 413722India ICAR-Central Institute for Arid Horticulture Bikaner 334006India ICAR-National Rice Research Institute Cuttack 753006India ICAR-Directorate of Weed Research Jabalpur 482004India Dr.panjabrao Deshmukh krishi Vidyapeeth Akola 444104India

The sustainability of rice production continues to be a subject of uncertainty and inquiry attributed to shifts in climatic conditions. In light of the impending climate change crisis and the high labor and water costs accompanying it, direct-seeded rice(DSR) is unquestionably one of the most practical solutions. Despite its resource and climate-friendly advantages, early maturing rice faces weed competitiveness and seedling establishment challenges. Resolving these issues is crucial for promoting its wider adoption among farmers, presenting it as a more effective sustainable rice cultivation method globally. Diverse traditional and contemporary breeding methods are employed to mitigate the limitations of the DSR approach, leveraging advanced techniques such as speed breeding and genome editing. Focusing on key traits like mesocotyl length elongation, early seedling vigor, root system architecture, and weed competitiveness holds promise for transformative improvements in DSR adaptation at a broader scale within farming communities. This review aims to summarize how these features contribute to increased crop production in DSR conditions and explore the research efforts focusing on enhancing DSR adaptation through these traits. Emphasizing the pivotal role of these game-changing traits in DSR adaptation, our analysis sheds light on their potential transformative impact and offers valuable insights for advancing DSR practices.

关键词： climate change direct-seeded rice aerobic rice early vigor trait

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physico−mathematical model of the voltage−current characteristics of light-emitting diodes with quantum wells based on the Sah−Noyce−Shockley recombination mechanism

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Journal of Semiconductors 2024年第8期45卷 25-33页

作者： Fedor I.Manyakhin Dmitry O.Varlamov Vladimir p.krylov Lyudmila O.Morketsova Arkady A.Skvortsov Vladimir k.Nikolaev Dinamics Strength of Machines and Resisance of MaterialsMoscow Polytechnic UniversityRussia Biomedical and Electronic Means and Technologies Vladimir State UniversityRussia Computer-Aided Design and Engineering National University of Science and Technology"MISiS"Russia

Herein,a physical and mathematical model of the voltage−current characteristics of a p−n heterostructure with quantum wells(QWs)is prepared using the Sah−Noyce−Shockley(SNS)recombination mechanism to show the SNS recombination rate of the correction function of the distribution of QWs in the space charge region of diode configuration.A comparison of the model voltage−current characteristics(VCCs)with the experimental ones reveals their *** technological parameters of the structure of the VCC model are determined experimentally using a nondestructive capacitive approach for determining the impurity distribution profile in the active region of the diode structure with a profile depth resolution of up to 10Å.The correction function in the expression of the recombination rate shows the possibility of determining the derivative of the VCCs of structures with QWs with a nonideality factor of up to 4.

关键词： light-emitting diodes with quantum wells voltage−current relation nonideality factor recombination mechanism Sah−Noyce−Shockley model

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