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A data-assisted physics-informed neural network(DA-PINN)for fretting fatigue lifetime prediction

International Journal of Mechanical System Dynamics 2024年第3期4卷 361-373页

作者： Can Wang Qiqi Xiao Zhikun Zhou Yongyu Yang Gregor Kosec Lihua Wang Magd Abdel Wahab Soete Laboratory Department of Electrical EnergyMetalsMechanical Constructions and SystemsFaculty of Engineering and ArchitectureGhent UniversityGentBelgium Department of Engineering Mechanics School of Aerospace EngineeringHuazhong University of Science and TechnologyWuhanChina Key Laboratory for Mechanics Anhui Polytechnic UniversityWuhuChina Parallel and Distributed Systems Laboratory Jožef Stefan InstituteLjubljanaSlovenia School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghaiChina College of Engineering Yuan Ze UniversityTaiwanChina

In this study,we present for the first time the application of physics-informed neural network(PINN)to fretting fatigue *** PINN has recently been applied to pure fatigue lifetime prediction,it has not yet been explored in the case of fretting *** propose a data-assisted PINN(DA-PINN)for predicting fretting fatigue crack initiation *** traditional PINN that solves partial differential equations for specific problems,DA-PINN combines experimental or numerical data with physics equations as part of the loss function to enhance prediction *** DA-PINN method,employed in this study,consists of two main ***,damage parameters are obtained from the finite element method by using critical plane method,which generates a data set used to train an artificial neural network(ANN)for predicting damage parameters in other ***,the predicted damage parameters are combined with the experimental parameters to form the input data set for the DA-PINN models,which predict fretting fatigue *** results demonstrate that DA-PINN outperforms ANN in terms of prediction accuracy and eliminates the need for high computational costs once the damage parameter data set is ***,the choice of loss-function methods in DA-PINN models plays a crucial role in determining its performance.

关键词： crack initiation data-assisted fretting fatigue finite element method physics-informed neural network

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Simultaneous biomethane and hydrochar recovery from washed elephant dung:The effects of inoculum source,substrate to inoculum ratio,and hydrothermal temperature

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Carbon Resources Conversion 2025年第1期8卷 26-34页

作者： Chayanon Sawatdeenarunat Boonya Charnnok Rojapun Nirunsin Sumate Chaiprapat Chen-Yeon Chu Asian Development College for Community Economy and Technology Chiang Mai Rajabhat UniversityChiang Mai 50300Thailand Energy Technology Program Department of Interdisciplinary EngineeringFaculty of EngineeringPrince of Songkla UniversityHat Yai DistrictSongkhla Province 90110Thailand School of Renewable Energy Maejo UniversityChiang Mai 50290Thailand Department of Civil and Environment Engineering PSU Energy Systems Research Institute(PERIN)Faculty of EngineeringPrince of Songkla UniversitySongkla 90002Thailand Institute of Green Products Feng Chia UniversityTaichung 40724TaiwanChina

This research aims to develop the appropriate biorefinery process integrating anaerobic digestion(AD)and hydrothermal carbonization(HTC)to recover the highest energy from the pretreated elephant ***,the raw elephant dung was physically processed by washing with water to generate the liquid waste,i.e.,washing water(WW),and solid waste,i.e.,washed fiber(WF).The appropriate substrate-to-inoculum ratio(SIR)and the inoculum source of the AD of WW were determined and the HTC temperature of WF was also *** results indicated that the AD of WW with the SIR of 1:2 and anaerobically digested swine manure as the inoculum presented the highest methane and energy yields of 412.3±9.9 N mL/g VS added and 2,220.1±53.03 MJ/ton dry wt.,*** HTC of WF,the optimum condition was the hydrothermal temperature of 170℃ at the residence time of 60 *** highest hydrochar and energy yields were 76.8%±1.9%dry *** 12,067.0±452.1 MJ/ton dry wt.,***,this biorefinery process could simultaneously treat elephant campderived waste and produce clean energy.

关键词： Elephant dung Biorefinery Anaerobic digestion Hydrothermal carbonization Lignocellulosic biomass

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Design and Analysis of IOT-based Solar Dryer for Sustainable Farming

Design and Analysis of IOT-based Solar Dryer for Sustainable...

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2023 Innovations in Power and Advanced Computing Technologies, i-PACT 2023

作者： Balachandran, Selvaraj Bautista, Dewar Wilmer Rico Edward, Belwin Wilson, Vincent Herald Swaminathan, Jose School of Mechanical Engineering Vellore Institute of Technology Vellore India Systems and IT Department Faculty of Engineering Francisco de Paula Santander University Colombia School of Electrical Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350325188

In this work, an indirect type solar dryer was developed using an Evacuated tube-based compound parabolic concentrator incorporated with PCM based latent heat thermal energy storage system. Without a tracking system, the absorber can collect direct and diffused ration by concentrating the solar radiation by assembling the two parabolas with compound rotation. The charging loop was built to maintain the proper heat collection from the solar collector. The heat transfer fluid pumped into the solar collector gains the heat by convection heat transfer mode. The heat transfer fluid flow inside the shell and tube Latent heat thermal energy storage system from the top transfer into the punch of tubes assembled parallel. Paraffin wax, due to its higher melting temperature and the latent heat of fusion, increases with an elongated hydrogen and carbon chain and is also a cost-effective, reliable, non-reactive material with self-nucleating properties. By implementing tubular encapsulation, direct contact between the PCM and the HTF is prevented, minimizing chemical reactions and enhancing PCM handling. Integrating a Thermal energy storage system into the solar dryer eliminates the fluctuation of solar radiation during non-sun shine hours, which helps prevent microbial growth. A power-full hard drive was developed especially for the energy-efficient IoT application. It has many features like low power, being a cost-effective platform, being integrated into Wi-Fi, containing a dual-core processor and having many input/output pins called GPIO (General Purpose Input/Output) to connect the sensor and control units. This system presented in this work assists in monitoring the system and controlling various vital parameters. This system would help small-scale farmers dry grains and monitor the system at a relatively cheaper cost. © 2023 IEEE.

关键词： IOT latent heat thermal storage phase change material regression analysis Solar dryer ThingSpeak

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Novel Approach for Enhancing Mental Well-Being Through Machine Learning Techniques 5

Novel Approach for Enhancing Mental Well-Being Through Machi...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Roshani, O.V.D.E. Ayuwardhana, H.M.K.J.J. Rodrigo, P.H.M.S. Hewageegana, R.U. Fernando, Harinda De Silva, Dilshan I. Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Frequently, individuals undergo specific episodes of mental health challenges throughout their lifetime. But the COVID pandemic has triggered a surge in mental health disorders arising from isolation, monotonous routines, demanding workloads, financial disparities, and disruptions to daily schedules. Furthermore, the global pandemic has induced constant anxiety and stress. Beyond the pandemic, the competition and intense pressure of the modern world impact mental health. Access to advanced mental health solutions and the necessary familiarity remain limited for most of the population. Given the integration of technology into daily life, diverse remedies, including mobile and web applications, have emerged to tackle the escalating challenge of mental health disorders. This study proposes an accessible and cost-effective approach that employs machine learning to detect stress levels and discern user emotions from journal entries and facial expressions while integrating self-journaling, video recommendations, and visual content generation to stimulate positive emotions and relieve stress. © 2023 IEEE.

关键词： Cost effectiveness

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Gaussian Process Regression Surrogate Model for Seismic Vulnerability Assessment of Highway Bridge Structure System

Gaussian Process Regression Surrogate Model for Seismic Vuln...

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Experimental Vibration Analysis for Civil engineering Structures - EVACES 2023 - Volume 2

作者： Saida, Taisei Muhammad, Rashid Nishio, Mayuko Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan

ISBN: (纸本)9783031391163

System fragility is required especially for the vulnerability assessment of existing bridges that configure transportation network as a structural system. Here, it is essential to consider not only variation of input ground motions but also the uncertainties in physical properties due to deteriorations or other aging effects. In that case, the derivation of system fragility requires the Monte Carlo calculation with high-dimensional input uncertain parameters. This study shows the deep kernel learning (DKL) surrogate modeling for the seismic system fragility analysis. Here, it has also been shown that the multilayer perceptron can be used in the DKL to compress high-dimensional uncertainties into low-dimensional features. In addition, a multi-output Gaussian process was used and correlations between multiple outputs were considered. The target structure for verification was a multi-span curved highway bridge with seismic isolation bearings with high nonlinearities. The input-output data were created by the earthquake response analysis using the FE model, and the DKL surrogate models for demand outputs for limit states evaluations were constructed with considering parameter uncertainties in the properties of bearings and piers. In the results, the system fragilities could be derived with appropriate accuracies at a low computational cost by the DKL surrogate model. In addition, the surrogate model can identify which components' limit states cause the bridge system's limit states. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Uncertainty analysis

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Social Radars: Finding Targets in Cyberspace for Cybersecurity

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 279-282页

作者： Lili Fan Changxian Zeng Yutong Wang Jiaqi Ma Fei-Yue Wang School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Dalian Minzu UniversityDalian 116600China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Civil and Environmental Engineering University of CaliforniaLos AngelesCA 90024 USA IEEE State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors.

关键词： prompt summarized insight

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Scheduling Tool for Deterministic Communication in Distributed Real-Time systems 10

Scheduling Tool for Deterministic Communication in Distribut...

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10th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Mach, Jan Tašková, Valéria Kohútka, Lukáš Institute of Computer Engineering and Applied Informatics Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

A network with critical data streams, where the timing of incoming and outgoing data is a necessity, is called a deterministic network. These networks are mostly used in association with real-time systems that use periodic hard-real-time data which need to be scheduled. The algorithm proposed in this paper is focused on achieving the lowest possible latency within the specified network topology depending on the physical parameters of the network and the periodic requirements of the communicating nodes. The algorithm allows to add priorities to the data flow between nodes and also the option to specify if preemption is allowed within the network, since not all devices support it. The result is a schedule of hard-real-time data communication within a specified network topology where all requirements of communicating nodes are met if such a solution is possible. © 2023 Copyright for this paper by its authors.

关键词： deadline deterministic scheduling Ethernet scheduling algorithm time-sensitive networking

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Computational Investigation of Multiband EMNZ Metamaterial Absorber for Terahertz Applications

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Computers, Materials & Continua 2022年第5期71卷 3905-3920页

作者： Ismail Hossain Md Samsuzzaman Mohd Hafiz Baharuddin Norsuzlin Binti Mohd Sahar Mandeep Singh Jit Singh Mohammad Tariqul Islam Space Science Center Universiti Kebangsaan Malaysia43600UKM BangiSelangorMalaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityBangladesh Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaMalaysia

This study presents an Epsilon Mu near-zero(EMNZ)nanostructured metamaterial absorber(NMMA)for visible regime *** resonator and dielectric layers are made of tungsten(W)and quartz(fused),where the working band is expanded by changing the resonator layer’s *** to perfect impedance matching with plasmonic resonance characteristics,the proposed NMMA structure is achieved an excellent absorption of 99.99%at 571 THz,99.50%at 488.26 THz,and 99.32%at 598 THz *** absorption mechanism is demonstrated by the theory of impedance,electric field,and power loss density distributions,*** geometric parameters are explored and analyzed to show the structure’s performance,and a near-field pattern is used to explain the absorption mechanism at the resonance frequency *** numerical analysis method describes that the proposed structure exhibited more than 80%absorbability between 550 and 900 *** Computer Simulation technology(CST Microwave Studio 2019)software is used to design the proposed ***,CSTHFSS interference is validated by the simulation data with the help of the finite element method(FEM).The proposed NMMA structure is also exhibits glucose concentration sensing capability as *** the proposed broadband absorber may have a potential application in THz sensing,imaging(MRI,thermal,color),solar energy harvesting,light modulators,and optoelectronic devices.

关键词： Metamaterial absorber terahertz applications multiband EM near zero nanostructured visible regime applications

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Towards Evaluating the Security of Wearable Devices in the Internet of Medical Things 11

Towards Evaluating the Security of Wearable Devices in the I...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Vaseghi, Yas Behara, Behnaz Delrobaei, Mehdi K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Systems and Control Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Biomedical Engineering Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Mechatronics Tehran Iran

ISBN: (纸本)9798350308105

The Internet of Medical Things (IoMT) offers a promising solution to improve patient health and reduce human error. Wearable smart infusion pumps that accurately administer medication and integrate with electronic health records are an example of technology that can improve healthcare. They can even alert healthcare professionals or remote servers during operational failure, preventing distressing incidents. However, as the number of connected medical devices increases, the risk of cyber threats also increases. Wearable medication devices based on IoT attached to patients' bodies are prone to significant cyber threats. Being connected to the Internet exposes these devices to potential harm, which could disrupt or degrade device performance and harm patients. To ensure patient safety and well-being, it is crucial to establish secure data authentication for internet-connected medical devices. It is also important to note that the wearability option of such devices might downgrade the computational resources, making them more susceptible to security risks. This paper implements a security approach to a wearable infusion pump. We discuss practical challenges in implementing security-enabled devices and propose initial solutions to mitigate cyber threats. © 2023 IEEE.

关键词： Wearable technology

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Optimized Hybrid CNN-GRU Approach for Accurate Prediction of Cardiovascular Diseases: Integrating Medical Imaging and Clinical Data 3

Optimized Hybrid CNN-GRU Approach for Accurate Prediction of...

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3rd International Conference on Communication, Control, and Intelligent systems, CCIS 2024

作者： Prasanna, V. Suresh Kumar, N. Divyaprabha, P. Sundaram, R. Srm Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Data Science and Business Systems Chennai India Sri Ramakrishna Engineering College Department of Information Technology Coimbatore India Sri Ramakrishna Engineering College Department of Computer Science and Engineering Coimbatore India Ganesh College of Engineering Department of Computer Science and Engineering Salem India

ISBN: (纸本)9798331528201

As the primary cause of death globally, cardiovascular diseases (CVDs) demand precise and timely prediction to enhance patient outcomes. Other examples of conventional approaches for CVD prediction include statistical models as well as machine learning models such as a single model that often struggle to address complex and comprehensive data from clinical records and Medical Imaging. To address these issues, the concept proposed here is to integrate the medical imaging data with clinical data as new apart from utilizing the hybrid CNN-GRU model to predict cardiovascular diseases with higher accuracy and interpretability. While the GRU module deals with the time sequences of clinical data including past history and other test results, the CNN module is to extract the spatial features from the medical images. Thus, by integrating these modules, it is more accurate to predict the data of the patient as a synergy of spatial and temporal arrangements. Cross-validation techniques and performance indices are used for model training and testing on a diverse data set containing imaging and other clinical-related data. Experimental results depict that the suggested hybrid CNN-GRU model performs much better than the traditional approaches and has higher levels of predicted accuracy and robustness. It is also feasible to generalize this integrated strategy to other medical disorder where multi-modal data analysis is crucial, besides enhancing the capacity to estimate CVDs. The findings underline the importance of integrating doctors' information with radiological images and applying new patterns of neural networks to augmenting clinical judgment. The suggested work is implemented using python. © 2024 IEEE.

关键词： Recurrent neural networks

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