Merge pull request #7 from mentzelopoulos/main

Fall_2023_Deep_Learning_project_Submission_Mentzelopoulos

assets/bibliography/2023-12-12-VIVFormer.bib

@@ -124,4 +124,180 @@ @inproceedings{zhou2022fedformer
   pages={27268--27286},
   year={2022},
   organization={PMLR}
+}
+
+@article{navrose_mittal_2016, title={Lock-in in vortex-induced vibration}, volume={794}, DOI={10.1017/jfm.2016.157}, journal={Journal of Fluid Mechanics}, publisher={Cambridge University Press}, author={Navrose and Mittal, Sanjay}, year={2016}, pages={565–594}}
+
+
+@article{park2016suppression,
+  title={Suppression of vortex-induced vibrations of rigid circular cylinder on springs by localized surface roughness at 3 x 10^4 < Re < 1.2 x 10^5},
+  author={Park, Hongrae and Kumar, R Ajith and Bernitsas, Michael M},
+  journal={Ocean Engineering},
+  volume={111},
+  pages={218--233},
+  year={2016},
+  publisher={Elsevier}
+}
+
+@inproceedings{bernitsas2019eigen,
+  title={Eigen-Solution for Flow Induced Oscillations (VIV and Galloping) Revealed at the Fluid-Structure Interface},
+  author={Bernitsas, Michael M and Ofuegbe, James and Chen, Jau-Uei and Sun, Hai},
+  booktitle={ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering},
+  year={2019},
+  organization={American Society of Mechanical Engineers Digital Collection}
+}
+
+@article{WILLIAMSON1988355,
+title = {Vortex formation in the wake of an oscillating cylinder},
+journal = {Journal of Fluids and Structures},
+volume = {2},
+number = {4},
+pages = {355-381},
+year = {1988},
+issn = {0889-9746},
+doi = {https://doi.org/10.1016/S0889-9746(88)90058-8},
+url = {https://www.sciencedirect.com/science/article/pii/S0889974688900588},
+author = {C.H.K. Williamson and A. Roshko},
+abstract = {When a body oscillates laterally (cross-flow) in a free stream, it can synchronize the vortex formation frequency with the body motion frequency. This fundamental “lock-in” regions is but one in a whole series of synchronization regions, which have been found in the present paper, in an amplitude-wavelength plane (defining the body trajectory) up to amplitudes of five diameters. In the fundamental region, it is shown that the acceleration of the cylinder each half cycle induces the roll-up of the two shear layers close to the body, and thereby the formation of four regions of vorticity each cycle. Below a critical wavelength, each half cycle sees the coalescence of a pair of like-sign vortices and the development of a Karman-type wake. However, beyond this wavelength the like-sign vortices convect away from each other, and each of them pairs with an opposite-sign vortex. The resulting wake comprises a system of vortex pairs which can convect away from the wake centerline. The process of pairing causes the transition between these modes to be sudden, and this explains the sharp change in the character of the cylinder forces observed by Bishop and Hassan, and also the jump in the phase of the lift force relative to body displacement. At precisely the critical wavelength, only two regions of vorticity are formed, and the resulting shed vorticity is more concentrated than at other wavelengths. We interpret this particular case as a condition of “resonant synchronization”, and it corresponds with the peak in the body forces observed in Bishop and Hassan's work.}
+}
+
+@article{wang2021illuminating,
+  title={Illuminating the complex role of the added mass during vortex induced vibration},
+  author={Wang, Z. and Fan, D. and Triantafyllou, M. S.},
+  journal={Phys. Fluids},
+  volume={33},
+  number={8},
+  pages={085120},
+  year={2021},
+  publisher={AIP Publishing LLC}
+}
+
+@phdthesis{fan2019thesis,
+  title={Mapping the hydrodynamic properties of flexible and rigid bodies undergoing vortex-induced vibrations},
+  author={Fan, Dixia},
+  year={2019},
+  school={Massachusetts Institute of Technology}
+}
+
+@article{rao1995mechanical,
+  title={Mechanical vibrations},
+  author={Rao, Singiresu S},
+  year={1995},
+  journal={Addison Wesley Boston, MA}
+}
+
+@inproceedings{mentzelopoulos2023physics,
+  title={Physics-Based Unsupervised Learning of Vortex-Induced Vibrations from Riser Field Experimental Stain Data},
+  author={Mentzelopoulos, Andreas P and Fan, Dixia and Resvanis, Themistocles and Sapsis, Themistoklis and Triantafyllou, Michael S},
+  booktitle={ISOPE International Ocean and Polar Engineering Conference},
+  pages={ISOPE--I},
+  year={2023},
+  organization={ISOPE}
+}
+
+@article{mentzelopoulos2024reconstructing,
+  title={Reconstructing flexible body vortex-induced vibrations using machine-vision and predicting the motions using semi-empirical models informed with transfer learned hydrodynamic coefficients.},
+  author={Mentzelopoulos, Andreas P and Prele, Emile and Fan, Dixia and del Aguila Ferrandis, Jose and Sapsis, Themistoklis P. and Triantafyllou, Michael S.},
+  year={2024},
+  journal={Journal of Fluids and Structures}
+}
+
+@article{vaswani2017attention,
+  title={Attention is all you need},
+  author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
+  journal={Advances in neural information processing systems},
+  volume={30},
+  year={2017}
+}
+
+@article{zhong2023pi,
+  title={Pi-vae: Physics-informed variational auto-encoder for stochastic differential equations},
+  author={Zhong, Weiheng and Meidani, Hadi},
+  journal={Computer Methods in Applied Mechanics and Engineering},
+  volume={403},
+  pages={115664},
+  year={2023},
+  publisher={Elsevier}
+}
+
+@article{takeishi2021physics,
+  title={Physics-integrated variational autoencoders for robust and interpretable generative modeling},
+  author={Takeishi, Naoya and Kalousis, Alexandros},
+  journal={Advances in Neural Information Processing Systems},
+  volume={34},
+  pages={14809--14821},
+  year={2021}
+}
+
+@article{shu2023physics,
+  title={A physics-informed diffusion model for high-fidelity flow field reconstruction},
+  author={Shu, Dule and Li, Zijie and Farimani, Amir Barati},
+  journal={Journal of Computational Physics},
+  volume={478},
+  pages={111972},
+  year={2023},
+  publisher={Elsevier}
+}
+
+article{kim2022machine,
+  title={Machine-learning-based prediction of vortex-induced vibration in long-span bridges using limited information},
+  author={Kim, Sunjoong and Kim, Taeyong},
+  journal={Engineering Structures},
+  volume={266},
+  pages={114551},
+  year={2022},
+  publisher={Elsevier}
+}
+
+@article{bai2022machine,
+  title={Machine learning for vortex induced vibration in turbulent flow},
+  author={Bai, Xiao-Dong and Zhang, Wei},
+  journal={Computers \& Fluids},
+  volume={235},
+  pages={105266},
+  year={2022},
+  publisher={Elsevier}
+}
+
+@article{raissi2019deep,
+  title={Deep learning of vortex-induced vibrations},
+  author={Raissi, Maziar and Wang, Zhicheng and Triantafyllou, Michael S and Karniadakis, George Em},
+  journal={Journal of Fluid Mechanics},
+  volume={861},
+  pages={119--137},
+  year={2019},
+  publisher={Cambridge University Press}
+}
+
+@article{ma20221understanding,
+title = {Understanding the higher harmonics of vortex-induced vibration response using a trend-constrained, machine learning approach},
+journal = {Marine Structures},
+volume = {83},
+pages = {103195},
+year = {2022},
+issn = {0951-8339},
+doi = {https://doi.org/10.1016/j.marstruc.2022.103195},
+url = {https://www.sciencedirect.com/science/article/pii/S0951833922000363},
+author = {Leixin Ma and Themistocles L. Resvanis and J. Kim Vandiver},
+keywords = {Flow-induced vibration, Higher harmonics, Physics-constrained machine learning, Feature selection},
+abstract = {The spectra from cross-flow VIV signals contain peaks at the dominant vortex shedding frequency but also at several other frequencies, notably at three times and five times that frequency. These higher harmonic contributions are important because they are associated with high fatigue damage rates. The understanding of what controls higher harmonic response is far from complete. This paper presents a trend-constrained, data-driven model to discover important features (parameters) affecting the higher harmonic response of flexible cylinders subjected to vortex-induced vibrations. The predicted dependent parameter is the ratio of stress at the 3rd harmonic divided by the stress at the dominant VIV frequency. The known effects of damping and bending stiffness are introduced as physical constraints to improve the DNN predictions and aid in important parameter identification. The machine learning predictions with and without prior physical constraints are compared. The comparison suggests that the machine learning model with prior physical constraints better handles independent experimental datasets. It is confirmed that the higher stress ratios are associated with smaller damping parameter values and smaller bending stiffness ratios. The larger stress ratio is also found to be associated with traveling waves and single-mode-dominated responses.}
+}
+
+@article{ma2021enhancing,
+  title={Enhancing machine learning models with prior physical knowledge to aid in VIV response prediction},
+  author={Ma, Leixin and Resvanis, Themistocles L and Vandiver, J Kim},
+  booktitle={International Conference on Offshore Mechanics and Arctic Engineering},
+  volume={85185},
+  pages={V008T08A021},
+  year={2021},
+  organization={American Society of Mechanical Engineers}
+}
+
+@inproceedings{rudy2021learning,
+  title={Learning optimal parametric hydrodynamic database for vortex-induced crossflow vibration prediction of both freely-mounted rigid and flexible cylinders},
+  author={Rudy, Samuel and Fan, Dixia and Ferrandis, Jose del Aguila and Sapsis, Themistoklis and Triantafyllou, Michael S},
+  booktitle={ISOPE International Ocean and Polar Engineering Conference},
+  pages={ISOPE--I},
+  year={2021},
+  organization={ISOPE}
 }