Jidong Zhao

[ Research & Teaching Excellence | HKUST Researchers Develop New Model for Accurate Landslide Prediction with Applications in Sustainable Agriculture, Energy, Healthcare, and Beyond ] Navigating the unpredictable terrain of nature's changes, HKUST researchers pioneer a paradigm shift in accurate landslide prediction with the PUA-DEM model. From safeguarding agriculture to enhancing healthcare, their innovation transcends boundaries, illuminating the path towards a safer, more sustainable future. Under the visionary leadership of Prof. ZHAO Jidong, this groundbreaking model deciphers the intricate dance of granular behavior, reshaping our understanding of particle dynamics in various environments. With applications spanning from early landslide detection systems to revolutionizing pharmaceutical manufacturing, the implications are profound and far-reaching. Published in the esteemed Proceedings of the National Academy of Sciences (PNAS), this research heralds a new era of predictive precision, poised to mitigate the human impact of nature's formidable forces. Learn more about how this research can reshape sustainable agriculture, energy, healthcare, and more: hkust.edu.hk/news/hkust-res… #HKUST #ResearchBreakthrough #Innovation #SustainableTechnology #HealthcareInnovation #EnvironmentalScience

The above animation is simulation of thermally induced pressure wave in porous media under different fluid compressibility. @HkustSc

Jidu's new #CMAME paper introduces an enhanced MPM for modeling compressible fluid-driven porous media under full THM coupling. It considers fluid compressibility and therm expansivity via a node-based implicit scheme for stability and efficiency. Read: researchgate.net/publication/39…

Shiwei's new @ComGeotechnics paper on #GPU-empowered #MPM simulations of geophysical flows. The following simulates 2018 #Baige landslide, running only 46 mins on a desktop PC with RTX 4070 Ti to model 4.1 million MPM points and 100,000 times step: researchgate.net/publication/38…

A #CMAME paper collaborated with colleagues from @KyotoU_News presenting a new #peridynamics approach for #hydraulic #fracturing modeling with #leak-off effect. The paper is open access for free download @HkustSc : doi.org/10.1016/j.cma.…

Our new #JGR-Earth Surface paper with collaborators from @WHU_1893 presents a persistent homology-based approach combining monitoring data from #InSar with new indicators derived from spatiotemporal evolution of slope deformation @HkustSc : researchgate.net/publication/38…

No wars, more research! Our newly published #JFM paper on a #peridynamics approach for modeling coupled #fluid flows and #heat #transfer problems. Below is a simulation of Rayleigh-Bénard convection. It is open access and free for download @HkustSc : doi.org/10.1017/jfm.20…

The following is #capillary #fingering:

The above simulates #wetting induced #collapse in granular media, the following is a #viscous #fingering:

No wars, more research! Excited to share our @pnas paper featuring a unified pore-scale hydromechanics & DEM to resolve air-water interfaces, #capillary forces and grain #dynamics to model complex #triphasic granular behavior: pnas.org/doi/10.1073/pn…

@deepseek_ai is the real deal! Installed and tested it, so impressed with the thinking process to reach a final optimal recommendation! I wholeheartedly embrace open source for open science!

#TGNNS excels with diverse datasets for complex boundary conditions and advances our understanding of #multiscale behaviors in granular materials and paves the way for enhanced physics-based modeling in digital twins. Check out the full paper: bit.ly/40RDoYt

It is trained and validated with data from hierarchical multiscale modeling approach that combines the Material Point Method (#MPM) and Discrete Element Method (#DEM), and operates 100 times faster than traditional numerical simulations using state-of-the-art GPU-based DEMPM.

@swayzhao's new #CMAME paper proposes an innovative #deeplearning model, the Temporal Graph Neural Network-based Simulator (#TGNNS), for #granular #materials, enhancing particle dynamics representation and gaining exceptional robustness and efficiency.

The approach has been tested in various scenarios, including rolling and sliding interactions. Check out the ironing test simulation. Read the preprint: lnkd.in/dZD7Px5V, or the published version at Elsevier: lnkd.in/dxfPk79Z.

Weijian's new #CMAME paper presents a novel mortar segment-to-segment frictional contact approach for #MPM, featuring a kinematic update for boundary vertices & evolving contact normals, contact constraints for stable detection and energetic-barrier enforced non-penetration.

Tao Yu's 4th paper from his thesis published in #AdditiveManufacturing where we proposed a physics-based adaptive optimising strategy, based on high-fidelity #CFD modeling, to reduce keyhole-induced porosity in #laser #powder bed #fusion (#LPBF): lnkd.in/gM_fNRqR @HkustSc

Congrats to second-year PhD student Changyi Yang for winning #GeoShanghai2024 Best Paper Award:

PhD student Changyi published his new research in #JMPS on a #multihorizon, fully coupled #thermomechanical #peridynamics model (#TMPD) for modeling interactive thermo-mechanical behaviour and #fracturing in solids: lnkd.in/gP-_2vwk