arXiv subjects

J. S. Chen

Publications and source records attributed to J. S. Chen.

At least 19 recordsLinked to original sources

arXiv2026

A New Notion of Tykhonov Well-Posedness for Optimization Problems

Building upon the minimal time function, we propose and study a novel notion of Tykhonov well-posedness with respect to a set of directions for optimization problems. This concept generalizes the classical Tykhonov well-posedness by focusing on existence, stability and convergence along specific directions, rather than over the entire space. We first establish several characterizations of Tykhonov well-posedness with respect to a set of directions, formulated in terms of the diameter of level sets and admissible functions. We then investigate relationships between these level sets and admissible functions. To highlight the advantages of the proposed framework, we present several illustrative examples. In particular, we show that by selecting a suitable set of directions, optimization problems that are not well-posed in the classical sense may still be Tykhonov well-posed with respect to those directions. This viewpoint not only broadens the theoretical landscape of well-posedness but also has practical implications, as it allows numerical methods to be effectively adapted so that the generated sequences converge reliably to minimizers.

math.OC↗

arXiv2025

Investigating the Correlation between Force Output, Strains, and Pressure for Active Skeletal Muscle Contractions

Measuring the forces of individual muscles in a muscle group around a joint is non-trivial, and researchers have suggested using surrogates for individual muscle forces instead. Traditionally, experimentalists have shown that the force output of the skeletal muscle tissue can be correlated to the intra-muscular pressure (IMP) generated by the muscle belly. However, IMP proves difficult to measure in vivo, due to variations from sensor placement and invasiveness of the procedure. Numerical biomechanical simulations offer a tool to analyze muscle contractions, enabling new insights into the correlations among non-invasive experimentally measurable quantities such as strains, and the force output. In this work, we investigate the correlations between the muscle force output, the principal, shear and volumetric strains experienced by the muscle, as well as the pressure developed within the muscle belly as the tissue undergoes isometric contractions with varying activation profiles and magnitudes. It is observed that pressure does not correlate well with force output under higher sub-maximal and maximal activation levels, especially at locations away from the center of the muscle belly due to pressure relaxation effects. This study reveals strong correlations between force output and the strains at all locations of the belly, irrespective of the type of activation considered. This observation offers evidence for further in vivo studies using experimentally measurable principal and volumetric strains in the muscle belly as proxies for the force generation by the individual muscle and consequently enables the estimation on the contribution of various muscle groups to the total force.

q-bio.TO↗

arXiv2025

Interpolation-based reproducing kernel particle method

Meshfree methods, including the reproducing kernel particle method (RKPM), have been widely used within the computational mechanics community to model physical phenomena in materials undergoing large deformations or extreme topology changes. RKPM shape functions and their derivatives cannot be accurately integrated with the Gauss-quadrature methods widely employed for the finite element method (FEM) and typically require sophisticated nodal integration techniques, preventing them from easily being implemented in existing FEM software. Interpolation-based methods have been developed to address similar problems with isogeometric and immersed boundary methods, allowing these techniques to be implemented within open-source finite element software. With interpolation-based methods, background basis functions are represented as linear combinations of Lagrange polynomial foreground basis functions defined upon a boundary-conforming foreground mesh. This work extends the applications of interpolation-based methods to implement RKPM within open-source finite element software. Interpolation-based RKPM is applied to several PDEs, and error convergence rates are equivalent to classic RKPM integrated using high-order Gauss-quadrature schemes. The interpolation-based method is able to exploit the continuity of the RKPM basis to solve higher-order PDEs, demonstrated through the biharmonic problem. The method is extended to multi-material problems through Heaviside enrichment schemes, using local foreground refinement to reduce geometric integration error and achieve high-order accuracy. The computational cost of interpolation-based RKPM is similar to the smoothed gradient nodal integration schemes, offering significant savings over Gauss-quadrature-based meshfree methods while enabling easy implementation within existing finite element software.

math.NA↗

arXiv2024

Image-Based RKPM for Accessing Failure Mechanisms in Composite Materials

Stress distributions and the corresponding fracture patterns and evolutions in the microstructures strongly influence the load-carrying capabilities of composite structures. This work introduces an enhanced phase-field fracture model incorporating interface decohesion to simulate fracture propagation and interactions at material interfaces and within the constituents of composite microstructures. The proposed method employs an interface-modified reproducing kernel (IM-RK) approximation for handling cross-interface discontinuities constructed from image voxels and guided by Support Vector Machine (SVM) ma-terial classification. The numerical models are directly generated from X-ray microtomography image voxels, guided by SVM using voxel color code information. Additionally, a strain energy-based phase field variable is introduced, eliminating the need to solve coupled field problems. The effectiveness of this method is demonstrated in modeling crack growth both along interfaces and across matrix and inclusion domains and in predicting the corresponding structural-scale mechanical behavior in composite structures. Furthermore, the proposed method has been validated against experimentally observed crack patterns.

cs.CE↗

arXiv2024

Shape optimization of non-matching isogeometric shells with moving intersections

While shape optimization using isogeometric shells exhibits appealing features by integrating design geometries and analysis models, challenges arise when addressing computer-aided design (CAD) geometries comprised of multiple non-uniform rational B-splines (NURBS) patches, which are common in practice. The intractability stems from surface intersections within these CAD models. In this paper, we develop an approach for shape optimization of non-matching isogeometric shells incorporating intersection movement. Separately parametrized NURBS surfaces are modeled using Kirchhoff--Love shell theory and coupled using a penalty-based formulation. The optimization scheme allows shell patches to move without preserving relative location with other members during the shape optimization. This flexibility is achieved through an implicit state function, and analytical sensitivities are derived for the relative movement of shell patches. The introduction of differentiable intersections expands the design space and overcomes challenges associated with large mesh distortion, particularly when optimal shapes involve significant movement of patch intersections in physical space. Throughout optimization iterations, all members within the shell structures maintain the NURBS geometry representation, enabling efficient integration of analysis and design models. The optimization approach leverages the multilevel design concept by selecting a refined model for accurate analysis from a coarse design model while maintaining the same geometry. We adopt several example problems to verify the effectiveness of the proposed scheme and demonstrate its applicability to the optimization of the internal stiffeners of an aircraft wing.

math.OC↗

arXiv2024

N-Adaptive Ritz Method: A Neural Network Enriched Partition of Unity for Boundary Value Problems

Conventional finite element methods are known to be tedious in adaptive refinements due to their conformal regularity requirements. Further, the enrichment functions for adaptive refinements are often not readily available in general applications. This work introduces a novel neural network-enriched Partition of Unity (NN-PU) approach for solving boundary value problems via artificial neural networks with a potential energy-based loss function minimization. The flexibility and adaptivity of the NN function space are utilized to capture complex solution patterns that the conventional Galerkin methods fail to capture. The NN enrichment is constructed by combining pre-trained feature-encoded NN blocks with an additional untrained NN block. The pre-trained NN blocks learn specific local features during the offline stage, enabling efficient enrichment of the approximation space during the online stage through the Ritz-type energy minimization. The NN enrichment is introduced under the Partition of Unity (PU) framework, ensuring convergence of the proposed method. The proposed NN-PU approximation and feature-encoded transfer learning forms an adaptive approximation framework, termed the neural-refinement (n-refinement), for solving boundary value problems. Demonstrated by solving various elasticity problems, the proposed method offers accurate solutions while notably reducing the computational cost compared to the conventional adaptive refinement in the mesh-based methods.

math.NA↗

arXiv2023

Data-Driven Modeling of an Unsaturated Bentonite Buffer Model Test Under High Temperatures Using an Enhanced Axisymmetric Reproducing Kernel Particle Method

In deep geological repositories for high level nuclear waste with close canister spacings, bentonite buffers can experience temperatures higher than 100 °C. In this range of extreme temperatures, phenomenological constitutive laws face limitations in capturing the thermo-hydro-mechanical (THM) behavior of the bentonite, since the pre-defined functional constitutive laws often lack generality and flexibility to capture a wide range of complex coupling phenomena as well as the effects of stress state and path dependency. In this work, a deep neural network (DNN)-based soil-water retention curve (SWRC) of bentonite is introduced and integrated into a Reproducing Kernel Particle Method (RKPM) for conducting THM simulations of the bentonite buffer. The DNN-SWRC model incorporates temperature as an additional input variable, allowing it to learn the relationship between suction and degree of saturation under the general non-isothermal condition, which is difficult to represent using a phenomenological SWRC. For effective modeling of the tank-scale test, new axisymmetric Reproducing Kernel basis functions enriched with singular Dirichlet enforcement representing heater placement and an effective convective heat transfer coefficient representing thin-layer composite tank construction are developed. The proposed method is demonstrated through the modeling of a tank-scale experiment involving a cylindrical layer of MX-80 bentonite exposed to central heating.

cs.CE↗

arXiv2023

A Multi-Resolution Physics-Informed Recurrent Neural Network: Formulation and Application to Musculoskeletal Systems

This work presents a multi-resolution physics-informed recurrent neural network (MR PI-RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter identification of the MSK systems. The MSK application was selected as the model problem due to its challenging nature in mapping the high-frequency surface electromyography (sEMG) signals to the low-frequency body joint motion controlled by the MSK and muscle contraction dynamics. The proposed method utilizes the fast wavelet transform to decompose the mixed frequency input sEMG and output joint motion signals into nested multi-resolution signals. The prediction model is subsequently trained on coarser-scale input-output signals using a gated recurrent unit (GRU), and then the trained parameters are transferred to the next level of training with finer-scale signals. These training processes are repeated recursively under a transfer-learning fashion until the full-scale training (i.e., with unfiltered signals) is achieved, while satisfying the underlying dynamic equilibrium. Numerical examples on recorded subject data demonstrate the effectiveness of the proposed framework in generating a physics-informed forward-dynamics surrogate, which yields higher accuracy in motion predictions of elbow flexion-extension of an MSK system compared to the case with single-scale training. The framework is also capable of identifying muscle parameters that are physiologically consistent with the subject's kinematics data.

cs.LG↗

arXiv2023

Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures

This work presents an approach for automating the discretization and approximation procedures in constructing digital representations of composites from Micro-CT images featuring intricate microstructures. The proposed method is guided by the Support Vector Machine (SVM) classification, offering an effective approach for discretizing microstructural images. An SVM soft margin training process is introduced as a classification of heterogeneous material points, and image segmentation is accomplished by identifying support vectors through a local regularized optimization problem. In addition, an Interface-Modified Reproducing Kernel Particle Method (IM-RKPM) is proposed for appropriate approximations of weak discontinuities across material interfaces. The proposed method modifies the smooth kernel functions with a regularized heavy-side function concerning the material interfaces to alleviate Gibb's oscillations. This IM-RKPM is formulated without introducing duplicated degrees of freedom associated with the interface nodes commonly needed in the conventional treatments of weak discontinuities in the meshfree methods. Moreover, IM-RKPM can be implemented with various domain integration techniques, such as Stabilized Conforming Nodal Integration (SCNI). The extension of the proposed method to 3-dimension is straightforward, and the effectiveness of the proposed method is validated through the image-based modeling of polymer-ceramic composite microstructures.

cs.LG↗

arXiv2023

Discovery of Two Cyclotron Resonance Scattering Features in X-ray Pulsar Cen X-3 by Insight-HXMT

We present the results of the neutron star X-ray binary system Cen X-3 performed by $Insight$-HXMT with two observations during 2017 and 2018. During these two observations, the source reached a X-ray luminosity of $\sim 10^{38}$ erg s$^{-1}$ from 2 -- 105 keV. The analysis of the broadband X-ray spectrum reports the presence of two cyclotron resonance scattering features (CRSFs) with the fundamental line at $\sim$ 28 keV and the harmonic line at $\sim 47 $ keV. The multiple lines exist by fittings with different continuum models, like the absorbed NPEX model and a power-law with high energy exponential cutoff model. This is the first time that both fundamental and harmonic lines are detected in Cen X-3. We also show evidence of two cyclotron lines in the phase-resolved spectrum of Cen X-3. The CRSF and continuum spectral parameters show evolution with the pulse profile, and the two line centroid energy ratio does not change significantly and locates in a narrow value range of $1.6-1.7$ over the pulse phase. The implications of the discovering two cyclotron absorption features and phase-resolved spectral properties are discussed.

astro-ph.HE↗

arXiv2023

A Quasi-Conforming Embedded Reproducing Kernel Particle Method for Heterogeneous Materials

We present a quasi-conforming embedded reproducing kernel particle method (QCE-RKPM) for modeling heterogeneous materials that makes use of techniques not available to mesh-based methods such as the finite element method (FEM) and avoids many of the drawbacks in current embedded and immersed formulations which are based on meshed methods. The different material domains are discretized independently thus avoiding time-consuming, conformal meshing. In this approach, the superposition of foreground (inclusion) and background (matrix) domain integration smoothing cells are corrected by a quasi-conforming quadtree subdivision on the background integration smoothing cells. Due to the non-conforming nature of the background integration smoothing cells near the material interfaces, a variationally consistent (VC) correction for domain integration is introduced to restore integration constraints and thus optimal convergence rates at a minor computational cost. Additional interface integration smoothing cells with area (volume) correction, while non-conforming, can be easily introduced to further enhance the accuracy and stability of the Galerkin solution using VC integration on non-conforming cells. To properly approximate the weak discontinuity across the material interface by a penalty-free Nitsche's method with enhanced coercivity, the interface nodes on the surface of the foreground discretization are also shared with the background discretization. As such, there are no tunable parameters, such as those involved in the penalty type method, to enforce interface compatibility in this approach. The advantage of this meshfree formulation is that it avoids many of the instabilities in mesh-based immersed and embedded methods. The effectiveness of QCE-RKPM is illustrated with several examples.

cs.CE↗

arXiv2020

Artificial two-dimensional polar metal by charge transfer to a ferroelectric insulator

Integrating multiple properties in a single system is crucial for the continuous developments in electronic devices. However, some physical properties are mutually exclusive in nature. Here, we report the coexistence of two seemingly mutually exclusive properties-polarity and two-dimensional conductivity-in ferroelectric Ba$_{0.2}$Sr$_{0.8}$TiO$_3$ thin films at the LaAlO$_3$/Ba$_{0.2}$Sr$_{0.8}$TiO$_3$ interface at room temperature. The polarity of a ~3.2 nm Ba$_{0.2}$Sr$_{0.8}$TiO$_3$ thin film is preserved with a two-dimensional mobile carrier density of ~0.05 electron per unit cell. We show that the electronic reconstruction resulting from the competition between the built-in electric field of LaAlO$_3$ and the polarization of Ba$_{0.2}$Sr$_{0.8}$TiO$_3$ is responsible for this unusual two-dimensional conducting polar phase. The general concept of exploiting mutually exclusive properties at oxide interfaces via electronic reconstruction may be applicable to other strongly-correlated oxide interfaces, thus opening windows to new functional nanoscale materials for applications in novel nanoelectronics.

cond-mat.mtrl-sci↗

arXiv2019

Electronic correlation determining correlated plasmons in Sb-doped Bi$_2$Se$_3$

Electronic correlation is believed to play an important role in exotic phenomena such as insulator-metal transition, colossal magneto resistance and high temperature superconductivity in correlated electron systems. Recently, it has been shown that electronic correlation may also be responsible for the formation of unconventional plasmons. Herewith, using a combination of angle-dependent spectroscopic ellipsometry, angle resolved photoemission spectroscopy and Hall measurements all as a function of temperature supported by first-principles calculations, the existence of low-loss high-energy correlated plasmons accompanied by spectral weight transfer, a fingerprint of electronic correlation, in topological insulator (Bi$_{0.8}$Sb$_{0.2}$)$_2$Se$_3$ is revealed. Upon cooling, the density of free charge carriers in the surface states decreases whereas those in the bulk states increase, and that the newly-discovered correlated plasmons are key to explaining this phenomenon. Our result shows the importance of electronic correlation in determining new correlated plasmons and opens a new path in engineering plasmonic-based topologically-insulating devices.

cond-mat.mtrl-sci↗

arXiv2016

Controlling Kondo-like Scattering at the SrTiO3-based Interfaces

The observation of magnetic interaction at the interface between nonmagnetic oxides has attracted much attention in recent years. In this report, we show that the Kondo-like scattering at the SrTiO3-based conducting interface is enhanced by increasing the lattice mismatch and growth oxygen pressure PO2. For the 26-unit-cell LaAlO3/SrTiO3 (LAO/STO) interface with lattice mismatch being 3.0%, the Kondo-like scattering is observed when PO2 is beyond 1 mTorr. By contrast, when the lattice mismatch is reduced to 1.0% at the (La0.3Sr0.7)(Al0.65Ta0.35)O3/SrTiO3 (LSAT/STO) interface, the metallic state is always preserved up to PO2 of 100 mTorr. The data from Hall measurement and X-ray absorption near edge structure (XANES) spectroscopy reveal that the larger amount of localized Ti3+ ions are formed at the LAO/STO interface compared to LSAT/STO. Those localized Ti3+ ions with unpaired electrons can be spin-polarized to scatter mobile electrons, responsible for the Kondo-like scattering observed at the LAO/STO interface.

cond-mat.str-el↗

arXiv2014

Bandgap Controlling of the Oxygen-Vacancy-Induced Two-Dimensional Electron Gas in SrTiO3

We report very large bandgap enhancement in SrTiO3 (STO) films (fabricated by pulsed laser deposition below 800 °C), which can be up to 20% greater than the bulk value, depending on the deposition temperature. The origin is comprehensively investigated and finally attributed to Sr/Ti antisite point defects, supported by density functional theory calculations. More importantly, the bandgap enhancement can be utilized to tailor the electronic and magnetic phases of the two-dimensional electron gas (2DEG) in STO-based interface systems. For example, the oxygen-vacancy-induced 2DEG (2DEG-V) at the interface between amorphous LaAlO3 and STO films is more localized and the ferromagnetic order in the STO-film-based 2DEG-V can be clearly seen from low-temperature magnetotransport measurements. This opens an attractive path to tailor electronic, magnetic and optical properties of STO-based oxide interface systems under intensive focus in the oxide electronics community. Meanwhile, our study provides key insight into the origin of the fundamental issue that STO films are difficult to be doped into the fully metallic state by oxygen vacancies.

cond-mat.mtrl-sci↗

arXiv2013

Origin of the two-dimensional electron gas at LaAlO3/SrTiO3 interfaces: The role of oxygen vacancies and electronic reconstruction

The relative importance of atomic defects and electron transfer in explaining conductivity at the crystalline LaAlO3/SrTiO3 interface has been a topic of debate. Metallic interfaces with similar electronic properties produced by amorphous oxide overlayers on SrTiO3 have called in question the original polarization catastrophe model. We resolve the issue by a comprehensive comparison of (100)-oriented SrTiO3 substrates with crystalline and amorphous overlayers of LaAlO3 of different thicknesses prepared under different oxygen pressures. For both types of overlayers, there is a critical thickness for the appearance of conductivity, but its value is always 4 unit cells (around 1.6 nm) for the oxygen-annealed crystalline case, whereas in the amorphous case, the critical thickness could be varied in the range 0.5 to 6 nm according to the deposition conditions. Subsequent ion milling of the overlayer restores the insulating state for the oxygen-annealed crystalline heterostructures but not for the amorphous ones. Oxygen post-annealing removes the oxygen vacancies, and the interfaces become insulating in the amorphous case. However, the interfaces with a crystalline overlayer remain conducting with reduced carrier density. These results demonstrate that oxygen vacancies are the dominant source of mobile carriers when the LaAlO3 overlayer is amorphous, while both oxygen vacancies and polarization catastrophe contribute to the interface conductivity in unannealed crystalline LaAlO3/SrTiO3 heterostructures, and the polarization catastrophe alone accounts for the conductivity in oxygen-annealed crystalline LaAlO3/SrTiO3 heterostructures. Furthermore, we find that the crystallinity of the LaAlO3 layer is crucial for the polarization catastrophe mechanism in the case of crystalline LaAlO3 overlayers.

cond-mat.mtrl-sci↗

arXiv2011

Magnetic anisotropy of FePt: effect of lattice distortion and chemical disorder

We perform first principles calculations of the magnetocrystalline anisotropy energy in the five L10 FePt samples studied experimentally by Ding et al. [J. App. Phys. 97, 10H303 (2005)]. The effect of temperature-induced spin fluctuations is estimated by scaling the MAE down according to previous Langevin dynamics simulations. Including chemical disorder as given in experiment, the experimental correlation between MAE and lattice mismatch is qualitatively well reproduced. Moreover we determine the chemical order parameters that reproduce exactly the experimental MAE of each sample. We conclude that the MAE is determined by the chemical disorder rather than by lattice distortion.

cond-mat.mtrl-sci↗

arXiv2008

Wavelet Based Iterative Learning Control with Fuzzy PD Feedback for Position Tracking of A Pneumatic Servo System

In this paper, a wavelet-based iterative learning control (WILC) scheme with Fuzzy PD feedback is presented for a pneumatic control system with nonsmooth nonlinearities and uncertain parameters. The wavelet transform is employed to extract the learnable dynamics from measured output signal before it can be used to update the control profile. The wavelet transform is adopted to decompose the original signal into many low-resolution signals that contain the learnable and unlearnable parts. The desired control profile is then compared with the learnable part of the transformed signal. Thus, the effects from unlearnable dynamics on the controlled system can be attenuated by a Fuzzy PD feedback controller. As for the rules of Fuzzy PD controller in the feedback loop, a genetic algorithm (GA) is employed to search for the inference rules of optimization. A proportional-valve controlled pneumatic cylinder actuator system is used as the control target for simulation. Simulation results have shown a much-improved positiontracking performance.

cs.RO↗