arXiv subjects

Jinling Wang

Publications and source records attributed to Jinling Wang.

6 recordsLinked to original sources

arXiv2026

3D Point Cloud from Close-Range Photogrammetry for Defect Characterisation of Rubberised Concrete

While three-dimensional (3D) point clouds are widely used in civil engineering, mainstream LiDAR systems such as Terrestrial Laser Scanning (TLS) are physically constrained to laboratory environments. Since their laser spot size typically exceeds the width of microcracks, the beam physically bridges over voids, rendering TLS unsuitable for fine-scale defect analysis. Alternatively, close-range photogrammetry utilising Structure-from-Motion (SfM) and Multi-View Stereo (MVS) algorithms offers a solution for testing highly tortuous materials, and its utility at fine-scale remains underexplored. This study adapts photogrammetric workflows specifically for rubberised concrete (RuC), a sustainable composite exhibiting high ductility and complex fracture morphologies. High-resolution image sets were captured using a Canon DSLR and an iPhone 16 to generate dense 3D models. Comparisons revealed that the DSLR-based reconstruction achieved sub-millimetre resolution, demonstrating superior performance for fine-scale surface monitoring. An RGB-guided crack extraction method was developed to enhance the identification of surface defects and isolate potential crack areas from the background. The extracted crack regions were visually distinguishable and provided a well-structured geometrical representation of defect morphology. Furthermore, a Pre and Post-Test deformation analysis was conducted to quantify surface displacement across testing stages. The results confirm that this close-range photogrammetry workflow is a flexible, high-resolution alternative to LiDAR for surface inspection and deformation monitoring of specimens in laboratory settings. Ultimately, this approach establishes a robust geometric baseline for future automated 3D feature characterisation and material performance evaluation.

cs.CV↗

arXiv2026

Collective Nuclear Polaritons with Coherent and Tunable Excitation Dynamics

We propose collective nuclear polaritons formed by hybridizing a 229Th nuclear ensemble with a vacuum-ultraviolet cavity mode generated via four-wave mixing, achieving a collective light-matter coupling that scales as $\sqrt{N}$. In the strong-coupling regime the system displays vacuum Rabi oscillations, indicating the hybridization between cavity photons and nuclear excitations. In the superradiant regime, the stored excitation is released in a cooperative burst with peak intensity scaling as $N^2$. The emission lifetime shrinks from thousands of seconds to the millisecond scale and remains tunable. Detuning sweeps across the polariton avoided crossing allow adiabatic conversion of the photonic excitation into a collective nuclear excitation, enabling reversible quantum storage. Our results demonstrate that cavity-mediated nuclear polaritons enable deterministic lifetime engineering and coherent quantum storage in nuclear systems.

quant-ph↗

arXiv2025

Acoustic Black Holes in a Shock-Wave Exciton-Polariton Condensate

We demonstrate the spontaneous formation of acoustic black holes in exciton-polariton condensates triggered by discontinuous Riemann-type initial conditions. Starting from a quasi-conservative Gross-Pitaevskii model, we show that nonlinear dispersive shock waves naturally generate spatial regions where the local flow velocity exceeds the speed of sound, creating a self-induced transonic interface that functions as an acoustic horizon. Unlike previous schemes relying on externally engineered potentials or pump-loss landscapes, our approach reveals that the intrinsic nonlinear hydrodynamics of polariton fluids alone can lead to horizon formation. Using Whitham modulation theory and numerical simulations, we characterize the transition between subsonic and supersonic regimes and estimate the corresponding surface gravity and Hawking temperature. This mechanism opens a new route toward realizing polariton black holes and studying analogue gravitational effects, including Hawking-like emission, in Bose-Einstein quantum liquids.

cond-mat.mes-hall↗

arXiv2024

Co-Clustering Multi-View Data Using the Latent Block Model

The Latent Block Model (LBM) is a prominent model-based co-clustering method, returning parametric representations of each block cluster and allowing the use of well-grounded model selection methods. The LBM, while adapted in literature to handle different feature types, cannot be applied to datasets consisting of multiple disjoint sets of features, termed views, for a common set of observations. In this work, we introduce the multi-view LBM, extending the LBM method to multi-view data, where each view marginally follows an LBM. In the case of two views, the dependence between them is captured by a cluster membership matrix, and we aim to learn the structure of this matrix. We develop a likelihood-based approach in which parameter estimation uses a stochastic EM algorithm integrating a Gibbs sampler, and an ICL criterion is derived to determine the number of row and column clusters in each view. To motivate the application of multi-view methods, we extend recent work developing hypothesis tests for the null hypothesis that clusters of observations in each view are independent of each other. The testing procedure is integrated into the model estimation strategy. Furthermore, we introduce a penalty scheme to generate sparse row clusterings. We verify the performance of the developed algorithm using synthetic datasets, and provide guidance for optimal parameter selection. Finally, the multi-view co-clustering method is applied to a complex genomics dataset, and is shown to provide new insights for high-dimension multi-view problems.

stat.ME↗

arXiv2020

Recognition of Surface Oxygen Intermediates on NiFe Oxyhydroxide Oxygen-evolving Catalysts by Homogeneous Oxidation Reactivity

NiFe oxyhydroxide is one of the most promising oxygen evolution reaction (OER) catalysts for renewable hydrogen production, and deciphering the identity and reactivity of the oxygen intermediates on its surface is a key challenge but is critical to understanding the OER mechanism as well as designing water-splitting catalysts with higher efficiencies. Here, we screened and utilized in situ reactive probes that can selectively target specific oxygen intermediates with high rates to investigate the OER intermediates and pathway on NiFe oxyhydroxide. Most importantly, the oxygen atom transfer (OAT) probes (e.g. 4-(Diphenylphosphino) benzoic acid) could efficiently inhibit the OER kinetics by scavenging the OER intermediates, exhibiting lower OER currents, larger Tafel slopes and larger kinetic isotope effect values, while probes with other reactivities demonstrated much smaller effects. Combining the OAT reactivity with electrochemical kinetic and operando Raman spectroscopic techniques, we identified a resting Fe=O intermediate in the Ni-O scaffold and a rate-limiting O-O chemical coupling step between a Fe=O moiety and a vicinal bridging O. DFT calculation further revealed a longer Fe=O bond formed on the surface and a large kinetic energy barrier of the O-O chemical step, corroborating the experimental results. These results point to a new direction of liberating lattice O and expediting O-O coupling for optimizing NiFe-based OER electrocatalyst.

cond-mat.mtrl-sci↗

arXiv2014

A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization

Integration of inertial navigation system (INS) and global navigation satellite system (GNSS) is usually implemented in engineering applications by way of Kalman-like filtering. This form of INS/GNSS integration is prone to attitude initialization failure, especially when the host vehicle is moving freely. This paper proposes an online constrained-optimization method to simultaneously estimate the attitude and other related parameters including GNSS antenna's lever arm and inertial sensor biases. This new technique benefits from self-initialization in which no prior attitude or sensor measurement noise information is required. Numerical results are reported to validate its effectiveness and prospect in high accurate INS/GNSS applications.

cs.RO↗