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Physics-constrained graph modeling for building thermal dynamics

Energy and AI 2024年第2期16卷 150-157页

作者： Ziyao Yang Amol D.Gaidhane Ján Drgoňa Vikas Chandan mahantesh m.halappanavar Frank Liu Yu Cao School of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZ 85287USA Pacific Northwest National Laboratory RichlandWA 99354USA Oak Ridge National Laboratory Oak RidgeTN 37830USA

In this paper,we propose a graph model embedded with compact physical equations for modeling the thermal dynamics of *** principles of heat flow across various components in the building,such as walls and doors,fit the message-passing strategy used by Graph Neural networks(GNNs).The proposed method is to represent the multi-zone building as a graph,in which only zones are considered as nodes,and any heat flow between zones is modeled as an edge based on prior knowledge of the building ***,the thermal dynamics of these components are described by compact models in the *** are further employed to train model parameters from collected *** model training,our proposed method enforces physical constraints(e.g.,zone sizes and connections)on model parameters and propagates the penalty in the loss function of *** constraints are essential to ensure model robustness and *** evaluate the effectiveness of the proposed modeling approach on a realistic dataset with multiple *** results demonstrate a satisfactory accuracy in the prediction of multi-zone ***,we illustrate that the new model can reliably learn hidden physical parameters with incomplete data.

关键词： Physics-constrained learning Graph Neural Networks Compact model Building thermal dynamics

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Experimental study and numerical simulation of the impact of under-sleeper pads on the dynamic and static mechanical behavior of heavy-haul railway ballast track

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Railway Engineering Science 2024年第3期32卷 384-400页

作者： Yihao Chi Hong Xiao Yang Wang Zhihai Zhang mahantesh m.Nadakatti School of Civil Engineering Beijing Jiaotong UniversityBeijing 100044China Beijing Key Laboratory of Track Engineering Beijing Jiaotong UniversityBeijing 100044China Department of mechanical Engg KLSGITBelgaumKarnataka 590008India

Laying the under-sleeper pad(USP)is one of the effective measures commonly used to delay ballast degradation and reduce maintenance *** explore the impact of application of the USP on the dynamic and static mechanical behavior of the ballast track in the heavy-haul railway system,numerical simulation models of the ballast bed with USP and without USP are presented in this paper by using the discrete element method(DEm)-multi-flexible body dynamic(mFBD)coupling analysis *** ballast bed support stiffness test and dynamic displacement tests were carried out on the actual operation of a heavy-haul railway line to verify the validity of the *** results show that using the USP results in a 43.01%reduction in the ballast bed support stiffness and achieves a more uniform distribution of track loads on the *** effectively reduces the load borne by the sleeper directly under the wheel load,with a 7.89%reduction in the pressure on the ***,the laying of the USP changes the lateral resistance sharing ratio of the ballast bed,significantly reducing the stress level of the ballast bed under train loads,with an average stress reduction of 42.19 *** also reduces the plastic displacement of ballast particles and lowers the peak value of rotational angular velocity by about 50%to 70%,which is conducive to slowing down ballast bed settlement deformation and reducing maintenance *** summary,laying the USP has a potential value in enhancing the stability and extending the lifespan of the ballast bed in heavy-haul railway systems.

关键词： Heavy-haul railway Under-sleeper pad Discrete element method multi-flexible body dynamic coupling analysis mechanical behavior Quality state

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Influence of span-to-depth ratio on dynamic response of vehicle-turnoutbridge system in high-speed railway

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High-Speed Railway 2024年第1期2卷 30-41页

作者： Chuanqing Dai Tao Xin Shenlu Qiao Yanan Zhang Pengsong Wang mahantesh m.Nadakatti School of Civil Engineering Beijing Jiaotong UniversityBeijing 100044China China Railway Engineering Design and Consulting Group Co. Ltd.Beijing 100070China Karnatak Law Society’s Gogte Institute of Technology Belagavi 590006India

For high-speed railways,the smoothness of the railway line significantly affects the operational speed of *** the train passes through the turnout on a long-span bridge,the wheel-rail impacts caused by the turnout structure irregularities,and the instability arising from the bridge's flexural deformation lead to a strong coupling effect in the vehicle-turnout-bridge *** significantly affects both ride comfort and operational *** addressing this issue,the present study considered a long-span continuous rigid-frame bridge as an example and established a train-turnout-bridge coupled dynamic model of high-speed *** a selfdeveloped dynamic simulation program,the study analysed the dynamic response characteristics when the train passes through the turnouts on the *** also investigated the influence of different span-to-depth ratios of the bridge on the vehicle dynamic response when the train passes through the main line and branch line of turnouts and then proposed a span-to-depth ratio limit value for a long-span continuous rigid-frame *** research findings suggest that the changes in the span-to-depth ratio have a relatively minor impact on the train’s operational performance but significantly affect the dynamic characteristics of the bridge *** on the findings and a comprehensive assessment of safety indicators,it is advisable to establish a span-to-depth ratio limit of 1/4500 for a long-span continuous rigid-frame bridge.

关键词： Turnout on bridge Span-to-depth ratio Dynamic response Vehicle-turnout-bridge system High-speed railway

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Two-Tier Clustering with Routing Protocol for IoT Assisted WSN

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Computers, materials & Continua 2022年第5期71卷 3375-3392页

作者： AArokiaraj Jovith mahantesh mathapati m.Sundarrajan N.Gnanasankaran Seifedine Kadry maytham N.meqdad Shabnam mohamed Aslam Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Rajarajeswari College of EngineeringBengaluru560074India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science Thiagarajar CollegeMadurai625019India Department of Applied Data Science Noroff University CollegeKristiansandNorway Al-mustaqbal University College HillahIraq Department of Information Technology College of Computing and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia

In recent times,Internet of Things(IoT)has become a hot research topic and it aims at interlinking several sensor-enabled devices mainly for data gathering and tracking *** Sensor Network(WSN)is an important component in IoT paradigm since its inception and has become the most preferred platform to deploy several smart city application areas like home automation,smart buildings,intelligent transportation,disaster management,and other such IoT-based *** methods are widely-employed energy efficient techniques with a primary purpose i.e.,to balance the energy among sensor *** and routing processes are considered as Non-Polynomial(NP)hard problems whereas bio-inspired techniques have been employed for a known time to resolve such *** current research paper designs an Energy Efficient Two-Tier Clustering with multi-hop Routing Protocol(EETTC-mRP)for IoT *** presented EETTC-mRP technique operates on different stages namely,tentative Cluster Head(CH)selection,final CH selection,and *** first stage of the proposed EETTC-mRP technique,a type II fuzzy logic-based tentative CH(T2FL-TCH)selection is ***,Quantum Group Teaching Optimization Algorithm-based Final CH selection(QGTOA-FCH)technique is deployed to derive an optimum group of CHs in the ***,Political Optimizer based multihop Routing(PO-mHR)technique is also employed to derive an optimal selection of routes between CHs in the *** order to validate the efficacy of EETTC-mRP method,a series of experiments was conducted and the outcomes were examined under distinct *** experimental analysis infers that the proposed EETTC-mRP technique is superior to other methods under different measures.

关键词： Wireless networks internet of things energy efficiency clustering multi-hop routing metaheuristics

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A comparative analysis of paddy crop biotic stress classification using pre-trained deep neural networks

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Artificial Intelligence in Agriculture 2022年第1期6卷 167-175页

作者： Naveen N.malvade Rajesh Yakkundimath Girish Saunshi mahantesh C.Elemmi Parashuram Baraki Department of Information Science and Engineering Smt.Kamala and Sri.Venkappa M.Agadi College of Engineering and TechnologyLakshmeshwar582116KarnatakaIndia Department of Computer Science and Engineering K.L.E.Institute of TechnologyHubballi580030KarnatakaIndia Department of Computer Science and Engineering Navkis College of EngineeringHassan573217KarnatakaIndia Department of Computer Science and Engineering Smt.Kamala and Sri.Venkappa M.Agadi College of Engineering and TechnologyLakshmeshwar582116KarnatakaIndia Visvesvaraya Technological University Belagavi 590018KarnatakaIndia

The agriculture sector is no exception to the widespread usage of deep learning tools and *** this paper,an automated detection method on the basis of pre-trained Convolutional Neural Network(CNN)models is proposed to identify and classify paddy crop biotic stresses from the field *** proposed work also provides the empirical comparison among the leading CNN models with transfer learning from the ImageNet weights namely,Inception-V3,VGG-16,ResNet-50,DenseNet-121 and *** spot,hispa,and leaf blast,three of the most common and destructive paddy crop biotic stresses that occur during the flowering and ripening growth stages are considered for the *** experimental results reveal that the ResNet-50 model achieves the highest average paddy crop stress classification accuracy of 92.61%outperforming the other considered CNN *** study explores the feasibility of CNN models for the paddy crop stress identification as well as the applicability of automated methods to non-experts.

关键词： Paddy crop Stress classification Biotic stress PlantVillage ImageNet Pre-trained CNN models

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