Subhamoy Sen

Indian Institute of Technology Mandi (iitmandi), Mahar, N., Indian Institute of Technology Mandi (iitmandi), Yadav, G., Indian Institute of Technology Mandi (iitmandi), Thakur, K., Indian Institute of Technology Mandi (iitmandi), Sen, S., Université Gustave Eiffel, & Mevel, L. (2026). Structural parameter identification with hybrid physics informed neural network. e-Journal of Nondestructive Testing, 31(8). https://doi.org/10.58286/33756

Indian Institute of Technology Mandi (iitmandi), Thakur, K., Indian Institute of Technology Mandi (iitmandi), Mahar, N., Indian Institute of Technology Mandi (iitmandi), Yadav, G., Indian Institute of Technology Mandi (iitmandi), & Sen, S. (2026). Cycle-Consistent Framework for Mooring Tension Prediction in Floating Offshore Wind Turbines. e-Journal of Nondestructive Testing, 31(8). https://doi.org/10.58286/33731

Kumar, R., Keprate, A., & Sen, S. (2026). Corrosion estimation in floating offshore wind turbine mooring with particle filter coupled with DeepONet predictor. Applied Ocean Research, 173, 105103. https://doi.org/10.1016/j.apor.2026.105103

Mahar, N., Sen, S., & Mevel, L. (2026). Implicit Runge Kutta physics informed neural network for parameter identification of structural systems. Computers & Structures, 323, 108157. https://doi.org/10.1016/j.compstruc.2026.108157

Deep, A., Sen, S., & Keprate, A. (2026). Structural Representation Learning for Thermal Turbulence Detection in Infrared Imagery using YOLO. PHM Society European Conference, 9(1), 1–12. https://doi.org/10.36001/phme.2026.v9i1.4891

Kumar, R., Keprate, A., & Sen, S. (2026). Uncertainty-Aware Surrogate for Fatigue Assessment of Moorings in Offshore Wind Turbines. PHM Society European Conference, 9(1), 1–7. https://doi.org/10.36001/phme.2026.v9i1.4872

Shraddha, K., Sen, S., Pathak, S., & Mukherjee, M. (2026). Bayesian inversion for parameter estimation of advanced soil constitutive model and associated uncertainty quantification: Transitional Markov Chain Monte Carlo versus Particle Filtering. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 1–25. https://doi.org/10.1080/17499518.2026.2623471

Singh, M. P., & Sen, S. (2026). Time-Dependent Reliability Assessment of Mass Concrete Structures: Leveraging an LSTM-Based Surrogate Model for Early-Age Thermal Cracking under Parametric Uncertainty. Journal of Materials in Civil Engineering, 38(9), 04026279. https://doi.org/10.1061/jmcee7.mteng-22584

Singh, M. P., & Sen, S. (2025). Time-dependent Reliability Estimation with Risk Mitigation Strategies for Early-age Thermal Cracking in Concrete Dam Structures. INCOLD Journal (A Half Yearly Technical Journal of Indian Committee on Large.

Kumar, R., Sen, S., & Keprate, A. (2025). Real-time fatigue assessment of Floating Offshore Wind Turbine Mooring employing sequence-to-sequence-based deep learning on indirect fatigue response. Ocean Engineering, 315, 119741. https://doi.org/10.1016/j.oceaneng.2024.119741

Shereena, O. A., Kuncham, E., Jain, P. C., Mevel, L., & Sen, S. (2025). Mitigating high dimensionality in damage identification for plate-like structures through substructuring with interacting filtering-based approaches. Engineering Structures, 323, 119190. https://doi.org/10.1016/j.engstruct.2024.119190

Mahar, N., Sen, S., & Mevel, L. (2025). An attention-augmented Long Short-Term Memory network for PINN-based structural health monitoring. Engineering Structures, 340, 120673. https://doi.org/10.1016/j.engstruct.2025.120673

Guo, P., Li, D., Qiao, H., Guo, X., Shang, Z., Sen, S., & Li, H. (2025). Damping identification using topological signal processing of ambient vibration measurements. Engineering Structures, 345, 121572. https://doi.org/10.1016/j.engstruct.2025.121572

Kumar, S., & Sen, S. (2025). Robust Genetic Algorithm-based deployment of a hollow-rope tensegrity utility bridge. Structures, 72, 108179. https://doi.org/10.1016/j.istruc.2024.108179

Mahar, N., Sen, S., & Mevel, L. (2025). A parallel framework of physics-informed neural networks for model identification of linear and nonlinear systems. Structures, 79, 109454. https://doi.org/10.1016/j.istruc.2025.109454

Sood, S., Kumar, S., & Sen, S. (2025). A novel hybrid optimization framework integrating genetic algorithm and modified differential evolution optimization towards efficient form-finding of tensegrity structures. Structures, 80, 109764. https://doi.org/10.1016/j.istruc.2025.109764

Thakur, A., Kumar, R., Shereena, O. A., Sharma, S., Li, D., & Sen, S. (2025). Integrating DL-based surrogate within an Interacting Particle Ensemble Kalman Filtering framework for computationally efficient condition monitoring of FOWT moorings. Ocean Engineering, 330, 121223. https://doi.org/10.1016/j.oceaneng.2025.121223

Kumar, R., Prasad, K. J., Keprate, A., & Sen, S. (2025). Addressing material uncertainty in reliability analysis of floating offshore mooring through probabilistic meta-model developed with Stochastic Kriging technique. Ocean Engineering, 335, 121697. https://doi.org/10.1016/j.oceaneng.2025.121697

Mahar, N., Sen, S., & Mevel, L. (2025). Physics informed Long Short-Term Memory neural network for dual state-parameter estimation of linear dynamical systems robust to input forces. Mechanical Systems and Signal Processing, 236, 113012. https://doi.org/10.1016/j.ymssp.2025.113012

Shereena, O. A., Sen, S., & Mevel, L. (2025). Monitoring of sparsely observed structures by time-lagged Bayesian smoothing. Mechanical Systems and Signal Processing, 241, 113493. https://doi.org/10.1016/j.ymssp.2025.113493

Arya, A., Kumar, R., Keprate, A., & Sen, S. (2025). Real-Time Monitoring of Clump Weight Integrity Loss in Floating Wind Turbines via Deep Learning. Journal of Dynamics, Monitoring and Diagnostics. https://doi.org/10.37965/jdmd.2025.792

Kumar, R., Thakur, A., O A, S., Keprate, A., & Sen, S. (2024). Characterizing Damage in Wind Turbine Mooring Using a Data-Driven Predictor Model within a Particle Filtering Estimation Framework. PHM Society European Conference, 8(1), 8. https://doi.org/10.36001/phme.2024.v8i1.4051

Indian Institute of Technology Mandi (iitmandi), O A, S., Indian Institute of Technology Mandi (iitmandi), Sen, S., Université Gustave Eiffel, & Mevel, L. (2024). Mitigating Ill-posedness in Parameter Estimation under Sparse measurement for Linear time-varying systems employing Virtual Sensor Responses. e-Journal of Nondestructive Testing, 29(7). https://doi.org/10.58286/29673

Singh, M. P., Sen, S., Pathak, H., & Dogra, A. B. (2024). Early age cracking relevant to mass concrete dam structures during the construction schedule. Construction and Building Materials, 411(1), 134739. https://doi.org/10.1016/j.conbuildmat.2023.134739

Yadav, N., Pattabiraman, B., Tummuru, N. R., Soundharajan, B. S., Kasiviswanathan, K. S., Adeloye, A. J., Sen, S., Maurya, M., & Vijayalakshmanan, S. (2024). Toward improving water-energy-food nexus through dynamic energy management of solar powered automated irrigation system. Heliyon, 10(4), E25359. https://doi.org/10.1016/j.heliyon.2024.e25359

Aswal, N., & Sen, S. (2024). Improved force density optimization-based form-finding algorithm mitigating the local instabilities. Structures, 61(1), 106046. https://doi.org/10.1016/j.istruc.2024.106046

Tandon, K., & Sen, S. (2024). A probabilistic integration of LSTM and Gaussian process regression for uncertainty-aware reservoir water level predictions. Hydrological Sciences Journal, 70(1), 144–161. https://doi.org/10.1080/02626667.2024.2428428

Kuncham, E., Hoda, M. A., & Sen, S. (2024). Force estimation in bridge substructure boundary under vehicle loading using interacting filtering approach. International Journal of Advances in Engineering Sciences and Applied Mathematics, 16(3), 249–255. https://doi.org/10.1007/s12572-023-00367-y

Hoda, M. A., Kuncham, E., & Sen, S. (2024). Enhanced high-resolution structural crack detection using hybrid interacting Particle-Kalman filter. Structures, 62, 106227. https://doi.org/10.1016/j.istruc.2024.106227

Kuncham, E., & Sen, S. (2024). Fatigue assessment of bridges using interacting filtering approach with sub-structured predictor model based on current health. Structural Health Monitoring, 24(5), 2857–2875. https://doi.org/10.1177/14759217241263838

Kuncham, E., Aswal, N., Sen, S., & Mevel, L. (2023). Bayesian monitoring of substructures under unknown interface assumption. Mechanical Systems and Signal Processing, 193, 110269. https://doi.org/10.1016/j.ymssp.2023.110269

Keprate, A., Bagalkot, N., Siddiqui, M. S., & Sen, S. (2023). Reliability analysis of 15MW horizontal axis wind turbine rotor blades using fluid-structure interaction simulation and adaptive kriging model. Ocean Engineering, 288(1), 116138. https://doi.org/10.1016/j.oceaneng.2023.116138

Kumar, S., Aswal, N., & Sen, S. (2023). A novel Genetic algorithm based form-finding approach towards the improved design of tensegrity utility bridge. Structures, 58(1), 105401. https://doi.org/10.1016/j.istruc.2023.105401

Aswal, N., Kuncham, E., Sen, S., & Mevel, L. (2023). Subdomain Fault Isolation for Linear Parameter Varying Systems through Coupled Marginalized Particle and Kitanidis Filters. IFAC-PapersOnLine, 56(2), 126–131. https://doi.org/10.1016/j.ifacol.2023.10.1557

Tandon, K., Sen, S., Kasiviswanathan, K. S., Soundharajan, B. S., Tummuru, N. R., & Das, A. (2022). Integration of machine learning and particle filter approaches for forecasting soil moisture. Stochastic Environmental Research and Risk Assessment, 36(12), 4235–4253. https://doi.org/10.1007/s00477-022-02258-3

Sharma, S., Dangi, S. K., Bairwa, S. K., & Sen, S. (2022). Comparative study on sensitivity of acceleration and strain responses for bridge health monitoring. Journal of Structural Integrity and Maintenance, 7(4), 238–251. https://doi.org/10.1080/24705314.2022.2088167

Hoda, M. A., Kuncham, E., & Sen, S. (2022). Response and input time history dataset and numerical models for a miniaturized 3D shear frame under damaged and undamaged conditions. Data in Brief, 45(2022), 108692. https://doi.org/10.1016/j.dib.2022.108692

Aswal, N., Sen, S., & Mevel, L. (2022). Switching Kalman filter for damage estimation in the presence of sensor faults. Mechanical Systems and Signal Processing, 175(1), 109116. https://doi.org/10.1016/j.ymssp.2022.109116

Sharma, S., & Sen, S. (2022). Real-time structural damage assessment using LSTM networks: regression and classification approaches. Neural Computing and Applications, 35(1), 557–572. https://doi.org/10.1007/s00521-022-07773-6

Aswal, N., Sen, S., & Mevel, L. (2022). Strain‐based joint damage estimation approach robust to unknown non‐stationary input force. Structural Control and Health Monitoring, 29(10), e2999. https://doi.org/10.1002/stc.2999

Kuncham, E., Sen, S., Kumar, P., & Pathak, H. (2021). An online model-based fatigue life prediction approach using extended Kalman filter. Theoretical and Applied Fracture Mechanics, 117, 103143. https://doi.org/10.1016/j.tafmec.2021.103143

Aswal, N., Sen, S., & Mevel, L. (2021). Estimation of local failure in tensegrity using Interacting Particle-Ensemble Kalman Filter. Mechanical Systems and Signal Processing, 160(1), 107824. https://doi.org/10.1016/j.ymssp.2021.107824

Vidrio-Sahagún, C. T., He, J., Kasiviswanathan, K. S., & Sen, S. (2021). Stationary hydrological frequency analysis coupled with uncertainty assessment under nonstationary scenarios. Journal of Hydrology, 598(1), 125725. https://doi.org/10.1016/j.jhydrol.2020.125725

Sharma, S., & Sen, S. (2021). Bridge Damage Detection in Presence of Varying Temperature Using Two-Step Neural Network Approach. Journal of Bridge Engineering, 26(6), 04021027. https://doi.org/10.1061/(asce)be.1943-5592.0001708

Sharma, S., & Sen, S. (2021). Structural damage detection in presence of temperature variability using 2D CNN integrated with EMD. Structural Monitoring and Maintenance, 80(4), 379–402. https://doi.org/10.12989/smm.2021.8.4.379

Sen, S., Aswal, N., Zhang, Q., & Mevel, L. (2021). Structural health monitoring with non-linear sensor measurements robust to unknown non-stationary input forcing. Mechanical Systems and Signal Processing, 152(1), 107472. https://doi.org/10.1016/j.ymssp.2020.107472

Sharma, S., & Sen, S. (2020). One-dimensional convolutional neural network-based damage detection in structural joints. Journal of Civil Structural Health Monitoring, 10(5), 1057–1072. https://doi.org/10.1007/s13349-020-00434-z

Sen, S., He, J., & Kasiviswanathan, K. S. (2020). Uncertainty quantification using the particle filter for non-stationary hydrological frequency analysis. Journal of Hydrology, 584(1), 124666. https://doi.org/10.1016/j.jhydrol.2020.124666

Sen, S., Crinière, A., Mevel, L., Cérou, F., & Dumoulin, J. (2018). Seismic-induced damage detection through parallel force and parameter estimation using an improved interacting Particle-Kalman filter. Mechanical Systems and Signal Processing, 110(1), 231–247. https://doi.org/10.1016/j.ymssp.2018.03.016

Sen, S., & Bhattacharya, B. (2018). Non-Gaussian parameter estimation using generalized polynomial chaos expansion with extended Kalman filtering. Structural Safety, 70(1), 104–114. https://doi.org/10.1016/j.strusafe.2017.10.009

Sen, S., Crinière, A., Mevel, L., Cérou, F., & Dumoulin, J. (2018). Correntropy based IPKF filter for parameter estimation in presence of non-stationary noise process. IFAC-PapersOnLine, 51(24), 420–427. https://doi.org/10.1016/j.ifacol.2018.09.611

Sen, S., & Bhattacharya, B. (2016). Online structural damage identification technique using constrained dual extended Kalman filter. Structural Control and Health Monitoring, 24(9), e1961. https://doi.org/10.1002/stc.1961

Sen, S., & Bhattacharya, B. (2016). A non-iterative structural damage identification methodology using state space eigenstructure assignment. Structure and Infrastructure Engineering, 13(2), 211–222. https://doi.org/10.1080/15732479.2016.1157825

Sen, S., & Bhattacharya, B. (2016). Progressive damage identification using dual extended Kalman filter. Acta Mechanica, 227(8), 2099–2109. https://doi.org/10.1007/s00707-016-1590-9

Sen, S., & Bhattacharya, B. (2015). Non-iterative eigenstructure assignment technique for finite element model updating. Journal of Civil Structural Health Monitoring, 5(4), 365–375. https://doi.org/10.1007/s13349-015-0107-x

Mahar, N., Sen, S., & Mevel, L. (2026). Bayesian Physics-Informed Neural. In Proceedings of 5th International Conference on Frontiers in Computing and.

Kumar, R., Keprate, A., & Sen, S. (2026). Bayesian Deep Learning for Probabilistic Fatigue Damage Assessment of Mooring Lines In Floating Offshore Wind Turbines. In Volume 7A: Ocean Renewable Energy (pp. V07AT09A035). https://doi.org/10.1115/omae2026-177090

Lehmann, L., Herrmann, D., Schaeffer, L., Mittnacht, K., Sen, S., & Böhm, V. (2026). Compliant Modular Tensegrity Manipulator Enabling Seahorse-Like Spiral Grasping. In 2026 IEEE 9th International Conference on Soft Robotics (RoboSoft) (pp. 755–760). https://doi.org/10.1109/robosoft67810.2026.11522928

Herrmann, D., Lehmann, L., Schaeffer, L., Pink, F., Sen, S., & Böhm, V. (2026). Compliant Modular Tensegrity Robotic System with Actuated X-shaped Members. In 2026 IEEE 9th International Conference on Soft Robotics (RoboSoft) (pp. 829–834). https://doi.org/10.1109/robosoft67810.2026.11522881

Kumar, R., Sen, S., & Keprate, A. (2025). Sequence-to-Sequence Based Indirect. In Proceedings of the UNIfied Conference of DAMAS, IncoME VIII and TEPEN.

Mahar, N., Yadav, N., Yadav, G., Sen, S., & Mevel, L. (2025). Physics-aware neural network integrated with stochastic subspace identification for quantification of physical changes. In 11th International Operational Modal Analysis Conference.

Thakur, A., Shereena, O. A., Sen, S., & Mevel, L. (2025). Compensating Low Instrumentation for Mode Shape Estimation in Bayesian Filtering with Time-Delayed Data Embedding. In 11th International Operational Modal Analysis Conference.

Bharti, N., Reddy, Y. P. K., & Sen, S. (2023). Mode Specific Damping Estimation—An Inverse Damping Modelling Technique. In Indian Structural Steel Conference (pp. 271–284). https://doi.org/10.1007/978-981-19-9394-7_22

Aswal, N., Sen, S., & Mevel, L. (2022). Damage detection in tensegrity under varying temperature using interacting Particle-Ensemble Kalman Filter. In International Symposium on Nondestructive Testing in Civil Engineering, Aug 2022. https://inria.hal.science/hal-03874406/

Pramod Kumar Reddy, Y., & Sen, S. (2022). Temperature Robust Health Bench-Marking and Monitoring of an Heritage Suspension Bridge Using Coupled IWCM and TBSI Method. In Recent Advances in Materials Processing and Characterization (pp. 363–370). https://doi.org/10.1007/978-981-19-5347-7_30

Hoda, M. A., Kuncham, E., & Sen, S. (2022). Detection of edge crack in beam like structure modeled as rotational spring by using Bayesian filtering. In 67th Congress of the Indian Society of Theoretical and Applied Mechanics (ISTAM). https://istam.iitkgp.ac.in/resources/2022/proceedings/Full_paper/PA0198.pdf

Tandon, K., & Sen, S. (2022). A decomposition based Long short term memory model (LSTM) for reservoir inflow forecasting. In 67th Congress of the Indian Society of Theoretical and Applied Mechanics (ISTAM). http://203.110.246.133/resources/2022/proceedings/Full_paper/PA0212.pdf

Aswal, N., Sen, S., & Mevel, L. (2021). Damage Detection in Tensegrity Using Interacting Particle-Ensemble Kalman Filter. In European Workshop on Structural Health Monitoring. (pp. 732–741). https://doi.org/10.1007/978-3-030-64908-1_68

Aswal, N., Kuncham, E., Sen, S., & Mevel, L. (2021). Robust interacting particle-Kalman filter based structural damage estimation using dynamic strain measurements under non-stationary excitation-an experimental study. In 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (pp. 1–8). https://inria.hal.science/hal-03277241/document

Sharma, S., & Sen, S. (2019). PLATE DAMAGE DETECTION UNDER VARYING TEMPERATURE USING DUAL NEURAL NETWORK. In Structural Engineering Congress 2019. https://scholar.google.com/scholar?oi=bibs&cluster=6842880568624863203&btnI=1&hl=en

Aswal, N., & Sen, S. (2019). Design and Health Monitoring of Tensegrity Structures: An Overview. In Reliability, Safety and Hazard Assessment for Risk-Based Technologies: Proceedings of ICRESH 2019 (pp. 523–533). https://doi.org/10.1007/978-981-13-9008-1_43

Sharma, S., & Sen, S. (2018). Damage detection in presence of varying temperature through residual error modelling approach with dual neural network. In EWSHM 2018. https://www.ndt.net/article/ewshm2018/papers/0201-Smriti.pdf

Sen, S., Crinière, A., Mevel, L., Cérou, F., & Dumoulin, J. (2017). Estimation of time varying system parameters from ambient response using improved Particle-Kalman filter with correlated noise. In EGU General Assembly Conference Abstracts (pp. 15527). https://ui.adsabs.harvard.edu/abs/2017EGUGA..1915527S/abstract

Sen, S., Crinière, A., Mevel, L., Cérou, F., & Dumoulin, J. (2017). Seismic induced damage detection through parallel estimation of force and parameter using improved interacting Particle-Kalman filter. In 11th International Workshop on Structural Health Monitoring. https://inria.hal.science/hal-01590713/

Sen, S., & Bhattacharya, B. (2015). Adaptive nonlinear Kalman filtering technique for parameter identification: an application to Bouc-Wen model. In ASCE EMI Conference on Mechanics for Civil Engineers Against Natural Hazards. https://www.researchgate.net/publication/272420729_Adaptive_nonlinear_Kalman_filtering_technique_for_parameter_identification_an_application_to_Bouc-Wen_model

Sen, S., & Bhattacharya, B. (2014). Non-iterative eigenstructure assignment based finite element model updating of a Mindlin–Reissner plate in Duncan form of state space using ambient vibration respnose. In International Conference on Theoretical, Applied, Computational and Experimental Mechanics. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=e89593c5b3b135b5dbd7d3fd29242c4754b41a24

Sen, S., Radhika, B., & Bhattacharya, B. (2014). Identification of Bouc-Wen model parameters using Extended Kalman filter with adaptive process and measurement covariance matrices. In International Conference on Theoretical, Applied, Computational and Experimental Mechanics. http://www.facweb.iitkgp.ac.in/~baidurya/publications/ictacem%202014%20397_Fullpaper.pdf

Sen, S., & Bhattacharya, B. (2013). Eigen structure assignment based finite element model updating. In International Conference on Computer Aided Engineering (CAE-2013). https://www.researchgate.net/profile/Subhamoy-Sen/publication/295646681_Eigen_structure_assignment_based_finite_element_model_updating/links/56cc31b808aee3cee543600a/Eigen-structure-assignment-based-finite-element-model-updating.pdf

Tandon, K., & Sen, S. (2026). A Temporal Decomposition-Based LSTM Model for Forecasting Reservoir Inflow Using Real-Time Data. In Mechanisms and Machine Science (pp. 423–434). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-95963-9_31

Kumar, S., Lehmann, L., Sen, S., Rhode-Barbarigos, L., & Böhm, V. (2026). Actuation-Driven Tensegrity Shape Morphing from Tetrahedron to Octahedron: Effects of Material, Geometry, and Prestress Uncertainties. In Mechanisms and Machine Science (pp. 20–29). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-30274-8_3

Deep, A., Ojha, A., Joshi, I., & Sen, S. (2026). Flapwise Movement and Motion Tracking of FOWT Blades Using YOLOv8 and BoT-SORT Algorithm. In Lecture Notes in Networks and Systems (pp. 385–395). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-0497-8_28

Shraddha, K., Sen, S., Pathak, S., & Mukherjee, M. (2026). A Comparative Study on Estimation of Soil Constitutive Model Parameter Employing Sequential Monte Carlo and Markov Chain Monte Carlo Techniques. In Proceedings of The 17th International Conference of the International Association for Computer Methods and Advances in Geomechanics (pp. 493–498). Springer Nature Singapore. https://doi.org/10.1007/978-981-95-5969-5_69

Mahar, N., Sen, S., & Mevel, L. (2026). Bayesian Physics-Informed Neural Network for Parameter Estimation of Mooring Line. In Lecture Notes in Networks and Systems (pp. 403–414). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-8309-3_28

Kuncham, E., Hoda, M. A., & Sen, S. (2025). Identifying the Cracks in Beam Structures Using a Simplified Substructure Technique. In Lecture Notes in Mechanical Engineering (pp. 43–51). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-6367-2_4

Shereena, O. A., Sen, S., Zhang, Q., & Mevel, L. (2024). A Novel Lagged Estimation Framework for Sparsely Observed Systems Supplemented with Virtual Measurements. In Lecture Notes in Civil Engineering (pp. 443–452). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-61425-5_43

Singh, M. P., Sen, S., Arora, G., Pathak, H., Dogra, A. B., & Singh, K. (2024). FFT-Homogenization of Elastic and Thermo-elastic Properties of Concrete. In Lecture Notes in Mechanical Engineering (pp. 247–259). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-0418-7_23

Kumar, R., Sen, S., & Keprate, A. (2024). Fatigue Damage Assessment of FOWT Mooring Lines Using Sequence-to-Sequence Based Indirect Sensing. In Mechanisms and Machine Science (pp. 47–57). https://doi.org/10.1007/978-3-031-95963-9_4

Kumar, R., Thakur, A., Sen, S., & Keprate, A. (2024). Temporal feature extraction based real time damage detection of floating offshore wind turbine mooring lines. In Mechanisms and Machine Science (pp. 59–68). https://doi.org/10.1007/978-3-031-95963-9_5

Aswal, N., Sen, S., & Mevel, L. (2023). Estimation of Local Failure in Large Tensegrity Structures via Substructuring Using Interacting Particle-Ensemble Kalman Filter. In Lecture Notes in Civil Engineering (pp. 943–951). Springer International Publishing. https://doi.org/10.1007/978-3-031-07322-9_95

Thakur, C., Aadhityaa, M., Vijayalakshmanan, S., Kasiviswanathan, K. S., Soundharajan, B., Sen, S., & Tummuru, N. R. (2023). Forecasting of Soil Moisture: An ANN Model Integrated with Empirical Mode Decomposition. In Advances in Science, Technology & Innovation (pp. 137–139). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43759-5_30

Aswal, N., Bhattacharya, B., & Sen, S. (2022). Joint and Dual Estimation of States and Parameters with Extended and Unscented Kalman Filters. In Recent Developments in Structural Health Monitoring and Assessment–Opportunities and Challenges: Bridges, Buildings and Other Infrastructures (pp. 223–252). WORLD SCIENTIFIC. https://doi.org/10.1142/9789811243011_0008

Sharma, S., & Sen, S. (2020). Damage Detection in Presence of Varying Temperature Using Mode Shape and a Two-Step Neural Network. In Recent Advances in Computational Mechanics and Simulations (pp. 285–299). Springer Singapore. https://doi.org/10.1007/978-981-15-8138-0_23