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1. A Novel Stochastic Interacting Particle-Field Algorithm for 3D Parabolic-Parabolic Keller-Segel Chemotaxis System

   https://doi.org/10.1007/s10915-025-02816-1  

   Wang, Zhongjian; Xin, Jack; Zhang, Zhiwen (March 2025, Journal of Scientific Computing)

   Abstract We introduce an efficient stochastic interacting particle-field (SIPF) algorithm with no history dependence for computing aggregation patterns and near singular solutions of parabolic-parabolic Keller-Segel (KS) chemotaxis system in three-dimensional (3D) space. In our algorithm, the KS solutions are approximated as empirical measures of particles coupled with a smoother field (concentration of chemo-attractant) variable computed by a spectral method. Instead of using heat kernels that cause history dependence and high memory cost, we leverage the implicit Euler discretization to derive a one-step recursion in time for stochastic particle positions and the field variable based on the explicit Green’s function of an elliptic operator of the form Laplacian minus a positive constant. In numerical experiments, we observe that the resulting SIPF algorithm is convergent and self-adaptive to the high-gradient part of solutions. Despite the lack of analytical knowledge (such as a self-similar ansatz) of a blowup, the SIPF algorithm provides a low-cost approach to studying the emergence of finite-time blowup in 3D space using only dozens of Fourier modes and by varying the amount of initial mass and tracking the evolution of the field variable. Notably, the algorithm can handle multi-modal initial data and the subsequent complex evolution involving the merging of particle clusters and the formation of a finite time singularity with ease. 

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2. A Computational Framework for Predicting Properties From Multifield Processing Conditions in Polymer Matrix Composites

   https://doi.org/10.1115/SMASIS2020-2390  

   Widdowson, Denise; von Lockette, Paris; Erol, Anil; Rodriguez, Manuel A. (September 2020, ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems)

   null (Ed.)

   Abstract Composites can be tailored to specific applications by adjusting process variables. These variables include those related to composition, such as volume fraction of the constituents and those associated with processing methods, methods that can affect composite topology. In the case of particle matrix composites, orientation of the inclusions affects the resulting composite properties, particularly so in instances where the particles can be oriented and arranged into structures. In this work, we study the effects of coupled electric and magnetic field processing with externally applied fields on those structures, and consequently on the resulting material properties that arise. The ability to vary these processing conditions with the goal of generating microstructures that yield target material properties adds an additional level of control to the design of composite material properties. Moreover, while analytical models allow for the prediction of resulting composite properties from constituents and composite topology, these models do not build upward from process variables to make these predictions. This work couples simulation of the formation of microscale architectures, which result from coupled electric and magnetic field processing of particulate filled polymer matrix composites, with finite element analysis of those structures to provide a direct and explicit linkages between process, structure, and properties. This work demonstrates the utility of these method as a tool for determining composite properties from constituent and processing parameters. Initial particle dynamics simulation incorporating electromagnetic responses between particles and between the particles and the applied fields, including dielectrophoresis, are used to stochastically generate representative volume elements for a given set of process variables. Next, these RVEs are analyzed as periodic structures using FEA yielding bulk material properties. The results are shown to converge for simulation size and discretization, validating the RVE as an appropriate representation of the composite volume. Calculated material properties are compared to traditional effective medium theory models. Simulations allow for mapping of composite properties with respect to not only composition, but also fundamentally from processing simulations that yield varying particle configurations, a step not present in traditional or more modern effective medium theories such as the Halpin Tsai or double-inclusion theories. 

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3. Comparison of variational discretizations for a convection-diffusion problem

   Bacuta, Constantin; Bacuta, Cristina; Hayes, Daniel (December 2024, Revue Roumaine Mathématiques Pures et Appliquées)

   Beznea, Lucian; Putinar, Mihai (Ed.)

   For a model convection-diffusion problem, we obtain new error estimates for a general upwinding finite element discretization based on bubble modification of the test space. The key analysis tool is finding representations of the optimal norms on the trial spaces at the continuous and discrete levels. We analyze and compare three methods: the standard linear discretization, the saddle point least square and the upwinding Petrov-Galerkin methods. We conclude that the bubble upwinding Petrov-Galerkin method is the most performant discretization for the one dimensional model. Our results for the model convection-diffusion problem can be extended for creating new and efficient discretizations for the multidimensional cases. 

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4. Phonon Boltzmann Transport Equation Based Simulation of Frequency Domain Thermoreflectance Experiments

   https://doi.org/10.1115/IMECE2022-95630  

   Saurav, Siddharth; Mazumder, Sandip (October 2022, Proceedings of the International Mechanical Engineering Congress and Exposition, IMECE2022)

   Abstract The Boltzmann Transport equation (BTE) was solved numerically in cylindrical coordinates and in time domain to simulate a Frequency Domain Thermo-Reflectance (FDTR) experiment. First, a parallel phonon BTE solver that accounts for all phonon modes, frequencies, and polarizations was developed and tested. The solver employs the finite-volume method (FVM) for discretization of physical space, and the finite-angle method (FAM) for discretization of angular space. The solution was advanced in time using explicit time marching. The simulations were carried out in time domain and band-based parallelization of the BTE solver was implemented. The phase lag between the temperature averaged over the probed region of the transducer and the modulated laser pump signal was extracted for a pump laser modulation frequency ranging from 20–200 MHz. It was found that with the relaxation time scales used in the present study, the computed phase lag is underpredicted when compared to experimental data, especially at smaller modulation frequencies. The challenges in solving the BTE for such applications are highlighted. 

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5. Adjoint-based inversion for stress and frictional parameters in earthquake modeling

   https://doi.org/10.1016/j.jcp.2024.113447  

   Stiernström, Vidar; Almquist, Martin; Dunham, Eric M (December 2024, Journal of Computational Physics)

   We present an adjoint-based optimization method to invert for stress and frictional parameters used in earthquake modeling. The forward problem is linear elastodynamics with nonlinear rate-and-state frictional faults. The misfit functional quantifies the difference between simulated and measured particle displacements or velocities at receiver locations. The misfit may include windowing or filtering operators. We derive the corresponding adjoint problem, which is linear elasticity with linearized rate-and-state friction and, for forward problems involving fault normal stress changes, nonzero fault opening, with time-dependent coefficients derived from the forward solution. The gradient of the misfit is efficiently computed by convolving forward and adjoint variables on the fault. The method thus extends the framework of full-waveform inversion to include frictional faults with rate-and-state friction. In addition, we present a space-time dual-consistent discretization of a dynamic rupture problem with a rough fault in antiplane shear, using high-order accurate summation-by-parts finite differences in combination with explicit Runge–Kutta time integration. The dual consistency of the discretization ensures that the discrete adjoint-based gradient is the exact gradient of the discrete misfit functional as well as a consistent approximation of the continuous gradient. Our theoretical results are corroborated by inversions with synthetic data. We anticipate that adjoint-based inversion of seismic and/or geodetic data will be a powerful tool for studying earthquake source processes; it can also be used to interpret laboratory friction experiments. 

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