arXiv subjects

Ming Fang

Publications and source records attributed to Ming Fang.

At least 19 recordsLinked to original sources

arXiv2026

Mitigating ray effects in rarefied flow simulations using an ensemble-of-subproblems strategy with stochastic discrete velocities

In this work, a ensemble-of-subproblems strategy with stochastic discrete velocities is extended to deterministic methods for mitigating ray effects in rarefied flow simulations. The strategy involves performing multiple independent subproblems, each using a small set of randomly sampled velocity points, and then averaging their solutions to obtain the final result. The core idea is to ensure that the distribution function at any velocity can contribute to the final result, approximating highly refined velocity-space resolution without increasing the memory requirement in any single subproblem. We incorporate this strategy within the DUGKS framework, and the resulting method is denoted as SDV-DUGKS. To evaluate the performance of the proposed method, we compare SDV-DUGKS with the original DUGKS on several test cases: (a) the Sod shock tube problem, (b) the one-dimensional Riemann problem, (c) the two-dimensional lid-driven cavity flow, and (d) the two-dimensional Riemann problem. The results show that, in the collisionless limit $\mathrm{Kn} \to \infty$: (1) for one-dimensional compressible flows, SDV-DUGKS reduces memory usage by approximately 2/3 compared with that of the original DUGKS while achieving good agreement; (2) for two-dimensional compressible flows, SDV-DUGKS requires one to two orders of magnitude less memory than the original DUGKS while achieving good agreement. Based on these results, it can be concluded that the proposed method serves as a reliable and effective tool for mitigating ray effects in rarefied flow simulations.

physics.comp-ph↗

arXiv2026

A memory-efficient deterministic method for multiscale gas flows using an ensemble-of-subproblems strategy with stochastic discrete velocities

Deterministic multiscale gas flow simulations have long suffered from the curse of dimensionality: the number of discrete velocities increases dramatically with the velocity space dimension and the Mach number, exhausting available memory and computational resources. To address this issue, this paper proposes a memory-efficient deterministic method based on an ensemble-of-subproblems strategy using stochastic discrete velocities. This strategy transforms the originally computationally expensive problem into a series of independently and efficiently solvable subproblems. To be concrete, the proposed method replaces the conventional large deterministic velocity set with multiple small random velocity sets. Each random set defines a subproblem, which is solved by a deterministic multiscale numerical scheme that computes macroscopic moments via Monte Carlo integration. The final flow field is obtained by arithmetic averaging over all sub-problems. In this work, we employ the discrete unified gas kinetic scheme (DUGKS) for spatial discretization and term the resulting method SDV-DUGKS. To validate the proposed method, several numerical test cases are conducted, including (a) the one-dimensional shock structure, (b) the two-dimensional cavity flow, and (c) supersonic flow around a square cylinder. The results of the one-dimensional shock structure confirm the feasibility of the proposed method. The two-dimensional cases demonstrate that, compared to its deterministic counterpart, the proposed method saves more than 80% of memory usage while maintaining comparable accuracy. These results indicate that the proposed method markedly reduces memory demand for multiscale flow simulations and exhibits strong potential to alleviate the curse of dimensionality that currently hinders deterministic multiscale numerical schemes from being applied to engineering problems.

physics.comp-ph↗

arXiv2026

The extended gas-kinetic theory from Pullin equation: the relaxation rates, transport coefficients and model equation

The Borgnakke-Larsen model, widely used in rarefied flow predictions, serves as the mainstream energy-exchange kernel for polyatomic gases. However, it lacks integrability and does not guarantee detailed balance, limiting theoretical foundations for near-continuum relaxation mechanisms, transport coefficients, and relaxation model equations. In this work, we adopt the Pullin equation, which possesses an integrable collision kernel and satisfies detailed balance, to analyze near-continuum relaxation. Considering only translational and rotational degrees, we obtain explicit analytical expressions for the relaxation rates of macroscopic variables including stress, temperatures, and heat fluxes by approximating the distribution function in mixed Hermite and Laguerre spaces. Based on the same elementary moments, we derive transport coefficients via Chapman-Enskog expansion, rigorously confirming a long-standing speculation that thermal conductivity depends on the degree of thermal non-equilibrium; under equilibrium, the results reduce to those of Mason and Monchick. Using the correct relaxation rates, we propose a novel Rykov-type relaxation model that captures the coupled relaxation of translational and rotational heat fluxes, a mechanism ignored in the widely used Rykov equation. The model is validated against benchmark test cases.

physics.comp-ph↗

arXiv2025

Wave-Particle-Mixedness Relationships Based on lp-norm Coherence

We investigate the relationships among the wave property, particle property and mixedness of quantum states based on the lp-norm coherence. By conforming that the lp-norm coherence is an appropriate measure of wave property and introducing a measure of particle property based on the differences between the maximal l2-norm coherence and the general l2-norm coherence, we present tradeoff relationships among the wave, particle and mixedness of quantum states. For 1<= p <2, we establish two kinds of tradeoffs of the wave, particle and mixedness with respect to the upper and lower bounds of the lp-norm coherence given by the l2-norm coherence. These trade relations give rise to compressive understanding of the intrinsic connections among the wave, particle and mixedness of quantum states, and cover some existing results as particular ones.

quant-ph↗

arXiv2025

SolPhishHunter: Towards Detecting and Understanding Phishing on Solana

Solana is a rapidly evolving blockchain platform that has attracted an increasing number of users. However, this growth has also drawn the attention of malicious actors, with some phishers extending their reach into the Solana ecosystem. Unlike platforms such as Ethereum, Solana has distinct designs of accounts and transactions, leading to the emergence of new types of phishing transactions that we term SolPhish. We define three types of SolPhish and develop a detection tool called SolPhishHunter. Utilizing SolPhishHunter, we detect a total of 8,058 instances of SolPhish and conduct an empirical analysis of these detected cases. Our analysis explores the distribution and impact of SolPhish, the characteristics of the phishers, and the relationships among phishing gangs. Particularly, the detected SolPhish transactions have resulted in nearly \$1.1 million in losses for victims. We report our detection results to the community and construct SolPhishDataset, the \emph{first} Solana phishing-related dataset in academia.

cs.CR↗

arXiv2024

Enhancing Visual Representation for Text-based Person Searching

Text-based person search aims to retrieve the matched pedestrians from a large-scale image database according to the text description. The core difficulty of this task is how to extract effective details from pedestrian images and texts, and achieve cross-modal alignment in a common latent space. Prior works adopt image and text encoders pre-trained on unimodal data to extract global and local features from image and text respectively, and then global-local alignment is achieved explicitly. However, these approaches still lack the ability of understanding visual details, and the retrieval accuracy is still limited by identity confusion. In order to alleviate the above problems, we rethink the importance of visual features for text-based person search, and propose VFE-TPS, a Visual Feature Enhanced Text-based Person Search model. It introduces a pre-trained multimodal backbone CLIP to learn basic multimodal features and constructs Text Guided Masked Image Modeling task to enhance the model's ability of learning local visual details without explicit annotation. In addition, we design Identity Supervised Global Visual Feature Calibration task to guide the model learn identity-aware global visual features. The key finding of our study is that, with the help of our proposed auxiliary tasks, the knowledge embedded in the pre-trained CLIP model can be successfully adapted to text-based person search task, and the model's visual understanding ability is significantly enhanced. Experimental results on three benchmarks demonstrate that our proposed model exceeds the existing approaches, and the Rank-1 accuracy is significantly improved with a notable margin of about $1\%\sim9\%$. Our code can be found at https://github.com/zhangweifeng1218/VFE_TPS.

cs.CV↗

arXiv2024

On Hecke algebras and $Z$-graded twisting, Shuffling and Zuckerman functors

Let $g$ be a complex semisimple Lie algebra with Weyl group $W$. Let $H(W)$ be the Iwahori-Hecke algebra associated to $W$. For each $w\in W$, let $T_w$ and $C_w$ be the corresponding $Z$-graded twisting functor and $Z$-graded shuffling functor respectively. In this paper we present a categorical action of $H(W)$ on the derived category $D^b(O_0^Z)$ of the $Z$-graded BGG category $O_0^Z$ via derived twisting functors as well as a categorical action of $H(W)$ on $D^b(O_0^Z)$ via derived shuffling functors. As applications, we get graded character formulae for $T_sL(x)$ and $C_sL(x)$ for each simple reflection $s$. We describe the graded shifts occurring in the action of the $Z$-graded twisting and shuffling functors on dual Verma modules and simple modules. We also characterize the action of the derived $Z$-graded Zuckerman functors on simple modules.

math.RT↗

arXiv2024

EffectiveASR: A Single-Step Non-Autoregressive Mandarin Speech Recognition Architecture with High Accuracy and Inference Speed

Non-autoregressive (NAR) automatic speech recognition (ASR) models predict tokens independently and simultaneously, bringing high inference speed. However, there is still a gap in the accuracy of the NAR models compared to the autoregressive (AR) models. In this paper, we propose a single-step NAR ASR architecture with high accuracy and inference speed, called EffectiveASR. It uses an Index Mapping Vector (IMV) based alignment generator to generate alignments during training, and an alignment predictor to learn the alignments for inference. It can be trained end-to-end (E2E) with cross-entropy loss combined with alignment loss. The proposed EffectiveASR achieves competitive results on the AISHELL-1 and AISHELL-2 Mandarin benchmarks compared to the leading models. Specifically, it achieves character error rates (CER) of 4.26%/4.62% on the AISHELL-1 dev/test dataset, which outperforms the AR Conformer with about 30x inference speedup.

cs.SD↗

arXiv2024

A novel Cercignani-Lampis boundary model for discrete velocity methods in predicting rarefied and multi-scale flows

To extend the discrete velocity method (DVM) and unified methods to more realistic boundary conditions, a Cercignani-Lampis (CL) boundary with different momentum and thermal energy accommodations is proposed and integrated into the DVM framework. By giving the macroscopic flux from the numerical quadrature of the incident molecular distribution, the reflected macroscopic flux can be obtained for the given accommodation coefficients. Then, an anisotropic Gaussian distribution can be found for the reflected molecules, whose parameters are determined by the calculated reflected macroscopic flux. These macroscopic flux and microscopic Gaussian distribution form a complete physical process for the reflected molecules. Furthermore, the CL boundary is integrated into the unified gas-kinetic scheme (UGKS), making it suitable for the simulation of both monatomic and diatomic gas flows, and it accommodates both the conventional Cartesian velocity space and the recently developed efficient unstructured velocity space. Moreover, this new GSI boundary is suitable for both explicit and implicit schemes, offering better performance for flow prediction. Finally, the performance of the new boundary is validated through a series of numerical tests covering a wide range of Knudsen and Mach numbers.

physics.flu-dyn↗

arXiv2024

Enabling pulse shape discrimination with commercial ASICs

Fast electronic readout for high-channel density scintillator-based systems is needed for radiation tracking and imaging in a wide range of applications, including nuclear physics, nuclear security and nonproliferation. Programmable electronics, like FPGAs and ASICs, provide a fast way of conditioning and processing the signal in real time. In this paper, we present a pulse shape discrimination (PSD) method based on the shaping circuit of a commercially available ASIC, the Citiroc1A by CAEN Technologies. We used two different shaping times per detector channel to calculate a shaping parameter that enables PSD. Using our new method, neutron and gamma-ray pulses detected by a d$_{12}$-stilbene scintillator can be effectively discriminated at light output values greater than 0.15 MeVee. While not achieving the PSD performance of traditional offline charge integration, our method does not require the transfer of data to a separate system for further processing and enables the direct deployment of high-channel density multi-particle detection systems. Moreover, the availability of a wider range of shaping times than those on the Citiroc1A can potentially further improve the PSD performance.

physics.ins-det↗

arXiv2024

Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localisation

This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.

stat.AP↗

arXiv2023

Rotation-Invariant Rapid TRISO-Fueled Pebble Identification Based on Feature Matching and Point Cloud Registration

Pebble bed reactor (PBR) relying on TRISO-fueled pebbles is one of the most promising Gen-IV reactor designs because of intrinsic safety and thermal efficiency. Fuel pebbles flow through PBR's core and the identification of individual pebbles exiting the core will be beneficial to improve safeguards and fuel management. We propose a pebble identification method that is fast, accurate, robust, and applicable to PBRs containing hundreds of thousands of pebbles. The identification relies on the internal distribution of TRISO fuel particles, which is a unique feature of each pebble. We experimentally demonstrated that X-ray CT can extract the particle distribution with high accuracy. We then applied the algorithm to identify a single pebble in a data set of 100,000 pebbles achieving 100% identification accuracy in 90,000 tests with the presence of arbitrary rotations and measurement noises. The average time to identify one pebble is below 50 s, compatible with PBR operation.

physics.data-an↗

arXiv2023

Simulation of Charge Collection in a Boron-coated Straw Detector for Emerging Fuel Cycles

Tristructural-isotropic (TRISO) fuel is currently one of the most mature fuel types for candidate advanced reactor types, namely pebble bed reactors (PBRs). In PBRs, TRISO-fueled pebbles can be re-introduced into the core several times before reaching their target burnup. Non-destructive techniques capable of assaying ${}^{235}$U mass in the pebble are therefore needed for nuclear material control and accountability during fuel recirculation. In this work, we have developed a new boron-coated straw (BCS) based neutron multiplicity counter (NMC) to estimate ${}^{235}$U mass in each pebble. BCS detectors are chosen for their inherent high insensitivity to gamma rays that will enable their use to assay also irradiated pebbles and high neutron detection efficiency, comparable to ${}^{3}$He detectors. The BCS-based NMC that we have designed was built by Proportional Technologies, Inc. (PTI) Houston, TX. In this work, we report the system-level simulation of the BCS-based NMC and the straw-level charge collection simulation coupled with a custom software to tally the detected pulse integral from the list mode energy deposited. We have developed a high-fidelity model of the NMC to simulate the response of a single straw detector to a ${}^{252}$Cf source. The simulated die-away time, single neutron count rate, and double neutron count rate agree well with measured values, with a relative difference within $\pm$0.4\%. The simulated charge spectrum agrees well with the measured one in the case of a round straw. We plan to use the NMC to perform active and passive interrogation of fresh and spent fuel pebbles.

physics.ins-det↗

arXiv2023

Feasibility of Neutron Coincidence Counting for Spent Fuel

High-temperature gas reactors rely on TRIstructural-ISOtropic (TRISO) fuel for enhanced fission product retention. Accurate fuel characterization would improve monitoring of efficient fuel usage and accountability. We developed a new neutron multiplicity counter (NMC) based on boron coated straw (BCS) detectors and used it in coincidence mode for 235U assay in TRISO fuel. In this work, we demonstrate that a high-efficiency version of the NMC encompassing 396 straws is able to estimate the 235U in used TRISO-fueled pebbles or compacts with a relative uncertainty below 2.5% in 100 s. We performed neutronics and fuel depletion calculation of the HTR-10 pebble bed reactor to estimate the neutron and gamma-ray source strengths of used TRISO-fueled pebbles with burnup between 9 and 90 GWd/t. Then, we measured a gamma-ray intrinsic efficiency of 10^-12 at an exposure rate of 340.87 R/h. The low gamma-ray sensitivity and high neutron detection efficiency enable the inspection of used fuel.

physics.ins-det↗

arXiv2023

Boron Coated Straw-based Neutron Multiplicity Counter for Neutron Interrogation of TRISO Fueled Pebbles

Pebble bed reactors (PBRs) can improve the safety and economics of the nuclear energy production. PBRs rely on TRIstructural-ISOtropic (TRISO) fuel pebbles for enhanced fission product retention. Accurate characterization of individual fuel pebbles would enable the validation of computational models, efficient use of TRISO fuel, and improve fuel accountability. We have developed and tested a new neutron multiplicity counter (NMC) based on 192 boron coated straw (BCS) detectors optimized for ${}^{235}$U assay in TRISO fuel. The new design yielded a singles and doubles neutron detection efficiency of 4.71% and 0.174%, respectively, and a die-away time of 16.7 $\mathrm{\mu}$s. The NMC has a low intrinsic gamma-ray detection efficiency of $8.71\times10^{-8}$ at an exposure rate of 80.3 mR/h. In simulation, a high-efficiency version of the NMC encompassing 396 straws was able to estimate the ${}^{235}$U in a pebble with a relative uncertainty and error both below 2% in 100 s.

physics.ins-det↗

arXiv2022

Mirror-reflective algebras and Tachikawa's second conjecture

Given an algebra with an idempotent, we introduce two procedures to construct families of new algebras, termed mirror-reflective algebras and reduced mirror-reflective algebras. We then establish connections among these algebras by recollements of derived module categories. In case of given algebras being gendo-symmetric, we show that the (reduced) mirror-reflective algebras are symmetric and provide new methods to construct systematically both higher dimensional (minimal) Auslander-Gorenstein algebras and gendo-symmetric algebras of higher dominant dimensions. This leads to a new formulation of Tachikawa's second conjecture for symmetric algebras in terms of idempotent stratifications.

math.RT↗

arXiv2022

Disambigutaion Decomposition of Mean Skin Friction and Heat Flux on Arbitrary-Curvature Surface

Since it is difficult to apply the existing method of friction and heat flux decomposition on the complex surface, a combined decomposition method of friction and heat flux with clear physical interpretation is proposed, which is based on FIK and RD decomposition method and can be applied to arbitrary surface. Based on this method, the aerothermodynamic characteristics of bistable states of curved compression ramps are analyzed from the perspective of energy transformation. The results show that the decrease of friction in the interaction region of the attachment state and the minimum values of friction in the separation bubble are all caused by the energy injection of the work by the adverse pressure gradient. The peak friction is mainly induced by the viscous dissipation, and its position is affected by the mechanical energy transport. The peak heat flux is mainly induced by viscous dissipation, and the enthalpy transport of the separation state plays a greater role in the peak heat flux generation than that of the attachment state. These results indicate that reducing viscous dissipation is a potential way for realizing friction and heat flux control simultaneously.

physics.flu-dyn↗

arXiv2022

Enabling PSD-capability for a High-density Channel Imager

Pulse shape discrimination (PSD) is crucial for non-proliferation and security applications, where fast neutrons need to be identified and measured in the presence of a strong gamma-ray background. The traditional charge-integration-based PSD method requires the storage and processing of hundreds of samples for every single pulse, which is time- and memory-consuming for high-density channel applications. In this work, we explored the possibility of implementing PSD using a commercial ASIC that allows the user to adjust the pulse shaping time. We demonstrated that PSD can be achieved by maximizing the difference between the pulse shaping circuit's responses to neutron and gamma-ray pulses.

physics.ins-det↗