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Researcher profile

Jie Yao

Jie Yao contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
physics.flu-dyncond-mat.mtrl-sciMachine Learningphysics.optics

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Published work

5 published item(s)

preprint2026arXiv

Identifying skin-friction generation structures in turbulent channel flows via canonical correlation decomposition

Flow structures directly responsible for local skin-friction generation in turbulent channel flows are identified using the newly developed Canonical Correlation Decomposition (CCD) method. The dominant structures take the form of streamwise streaks that are spanwise-localised around the position where the skin-friction is targeted and exhibit significantly shorter streamwise extent than those revealed using POD. The resulting CCD spectrum shows a clear low-rank behaviour; flow reconstruction using only the first 4 CCD modes recovers more than 80\% of the examined skin friction, as opposed to 2\% recovered by the leading 4 POD modes. When the opposition control technique is used to reduce drag, the application of CCD shows that drag reduction is achieved by lifting the original streak structures and generating smaller streaks with opposite phases underneath. These findings demonstrate that CCD isolates the causally relevant flow structures governing skin-friction generation and modification, which is expected to find use in various drag control applications in wall-bounded turbulence.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Long-horizon prediction of three-dimensional wall-bounded turbulence with CTA-Swin-UNet and resolvent analysis

Long-horizon prediction of three-dimensional (3D) wall-bounded turbulence with machine-learning methods remains a challenging task, due to the rapid accumulation of autoregressive errors and the substantially computational cost. To address these challenges, we present a hybrid machine-learning framework, in which a channel-time-attention Swin-UNet (CTA-Swin-UNet) and a multi-time-scale fusion correction (MTFC) strategy are developed to predict the turbulent flow fields in a wall-parallel plane, with affordable computational cost. Then, 3D flow fields are reconstructed via a resolvent-based spectral linear stochastic estimation (SLSE), rooting from the predicted planar flow. Results show that the CTA-Swin-UNet outperforms the baseline models (LSTM, FNO and traditional Swin-UNet) in both single-step prediction and autoregressive rollouts, indicating the effectiveness of introducing the CTA module into the Swin-UNet architecture. At the same temporal interval, the CTA-Swin-UNet remains stable for approximately 150 rollout steps, while the baseline models fail within 20 to 50 rollout steps. After introducing the MTFC strategy, a longer horizon upto 300 steps is achieved. Using the resolvent-based SLSE reconstruction further recovers the 3D flow structures and energy spectral distributions from the predicted planar inputs, which demonstrates that the proposed framework provides an effective and computationally efficient approach for long-horizon autoregressive prediction of 3D wall-bounded turbulence.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Pervasive beyond room-temperature ferromagnetism in a doped van der Waals magnet: Ni doped Fe$_5$GeTe$_2$ with $T_{\text{C}}$ up to 478 K

The existence of long range magnetic order in low dimensional magnetic systems, such as the quasi-two-dimensional (2D) van der Waals (vdW) magnets, has attracted intensive studies of new physical phenomena. The vdW Fe$_N$GeTe$_2$ ($N$ = 3, 4, 5; FGT) family is exceptional owing to its vast tunability of magnetic properties. Particularly, a ferromagnetic ordering temperature ($T_{\text{C}}$) above room temperature at $N$ = 5 (F5GT) is observed. Here, our study shows that, by nickel (Ni) substitution of iron (Fe) in F5GT, a record high $T_{\text{C}}$ = 478(6) K is achieved. Importantly, pervasive, beyond-room-temperature ferromagnetism exists in almost the entire doping range of the phase diagram of Ni-F5GT. We argue that this striking observation in Ni-F5GT can be possibly due to several contributing factors, in which the structural alteration enhanced 3D magnetic couplings might be critical for enhancing the ferromagnetic order.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Separation scaling for viscous vortex reconnection

Reconnection plays a significant role in the dynamics of plasmas, polymers and macromolecules, as well as in numerous laminar and turbulent flow phenomena in both classical and quantum fluids. Extensive studies in quantum vortex reconnection show that the minimum separation distance δ between interacting vortices follows a 1/2 scaling. Due to the complex nature of the dynamics (e.g., the formation of bridges and threads as well as successive reconnections and avalanche), such scaling has never been reported for (classical) viscous vortex reconnection. Using the direct numerical simulation of the Navier-Stokes equations, we study viscous reconnection of slender vortices, whose core size is much smaller than the radius of the vortex curvature. For separations that are large compared to the vortex core size, we discover that δ(t) between the two interacting viscous vortices surprisingly also follows the 1/2 power scaling for both pre- and post-reconnection events. The prefactors in this 1/2-power law are found to depend not only on the initial configuration but also on the vortex Reynolds number (or viscosity). Our finding in the viscous reconnection, complementing numerous works on quantum vortex reconnection, suggests that there is indeed a universal route for reconnection -- an essential result for understanding the various facets of the viscous vortex reconnection phenomena and their potential modeling, as well as possibly explaining turbulence cascade physics.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Phase-change silicon as an ultrafast active photonic platform

Phase change material (PCM) features distinct optical or electronic properties between amorphous and crystalline states. Recently, it starts to play a key role in the emerging photonic applications like optoelectronic display, dynamic wavefront control, on-chip photonic memory and computation. However, current PCMs do not refract effectively at visible wavelengths and suffer from deformation and decomposition, limiting the repeatability and vast visible wavelength applications. Silicon as the fundamental material for electronics and photonics, has never been considered as phase change material, due to its ultrafast crystallization kinetics. Here we show the striking fact that nanoscale silicon domains can be reversibly crystallized and amorphized under nanosecond laser pulses. For a typical disk resonator, it also provides a 25% non-volatile modulation at nanosecond time scale. We further show proof-of-concept experiments that such attributes could enable ultra-high resolution dielectric color display and dynamic visible wavefront control.

0 citations0 reviewsNo code linkedOpen access