Search Results (1,602)

Developing effective CAR-T cell therapy for solid tumours remains challenging because of biological barriers such as antigen escape and an immunosuppressive microenvironment. The aim of this study is to develop a mathematical model of the spatio-temporal dynamics of tumour processes in order to assess key factors that limit treatment efficacy. We propose a reaction–diffusion model described by a system of partial differential equations for the densities of tumour cells and CAR-T cells, the concentration of immune inhibitors, and the degree of antigen escape. The methods of investigation include stability analysis and numerical solution of the model using a finite-difference scheme. The simulations show that antigen escape produces a resistant tumour core and relapse after an initial regression; increasing the escape rate from $\gamma =0.001$ to $0.1$ increases the final tumour volume at $t=100$ days from approximately 35.3 a.u. to 36.2 a.u. Parameter mapping further indicates that for $\gamma \le 0.01$ tumour control can be achieved at moderate killing rates ($k_{CT}\approx 1{\mathrm{day}}^{-1}$), whereas for $\gamma \ge 0.05$ comparable control requires $k_{CT}\approx 2$–$5{\mathrm{day}}^{-1}$. Repeated CAR-T administration improves durability: the residual normalised tumour volume at $t=100$ days decreases from approximately 4.5 after a single infusion to approximately 0.9 (double) and approximately 0.5 (triple), with a saturating benefit for further intensification. We conclude that the proposed model is a valuable tool for analysing and optimising CAR-T therapy protocols, and that our results highlight the need for combined strategies aimed at overcoming antigen escape. Full article

Accurate prediction of the stress–strain fields in fiber-reinforced composites is crucial for performance analysis and structural design. However, due to their complex microstructures, traditional finite element analysis (FEA) entails a very high computational cost. Therefore, this study proposes a conditional generative adversarial network (cGAN) framework, named FiberGAN, to enable rapid prediction of the microscopic stress–strain fields in fiber-reinforced composites. The method employs an adaptive representative volume element (RVE) generation algorithm to construct random fiber arrangements with fiber volume fractions ranging from 30% to 50% and uses FEA to obtain the corresponding stress and strain fields as training data. A U-Net generator, combined with a PatchGAN discriminator, captures both global distribution patterns and fine local details. Under tensile and shear loading conditions, the R² values of FiberGAN predictions range from 0.96 to 0.99, while the structural similarity index (SSIM) values range from 0.95 to 0.99. The error maps show that prediction residuals are mainly concentrated in high-gradient regions with small magnitudes. These results demonstrate that the proposed deep learning model can successfully predict stress–strain field distributions for different fiber volume fractions under various loading conditions. Full article

In this study, a curved sandwich beam with Functionally Graded Materials (FGM) face sheets and a homogeneous core under thermomechanical loads is investigated. The problem is studied numerically by the finite element method (FEM). Plane, eight nodes isoparametric elements are used, where the gradient of the material properties is incorporated into the formulation of the element. The effect of the thickness and volume fraction index (VFI) of the FGM face sheets on the stress and the temperature fields are studied. The results are valuable in the design of hydrogen mechanical applications, since the FGM sandwich curved beam could be a part of hydrogen storage tanks. Full article

To reduce the reliance on large training sets for representative volume element (RVE) generation using machine learning, this work presents a novel approach based on physics-informed neural network (PINN) to generate RVEs for unidirectional fiber-reinforced composites with non-uniform fiber distributions and high-volume fractions. The method embeds physical constraints including fiber non-overlap, volume fraction, and boundary conditions directly into the neural network’s loss function. This integration eliminates the need for large training datasets, which is typically required by traditional machine learning methods. Moreover, it achieves volume fractions exceeding 0.8, surpassing the jamming limit of conventional generation techniques. Exhaustive statistical measurements taken at different scales confirm that the proposed method could accurately reproduce local fiber distribution patterns in realistic microstructures while maintaining complete randomness at larger scales. Finite element analysis was employed on the generated RVEs to predict the elastic properties and damage behavior that taking into account the interfacial debonding and nonlinear damage in matrix. The predictions of both macroscopic mechanical properties (elastic properties and strength) and microscopic damage patterns show good agreement with experimental results. The proposed PINN-based framework provides an efficient and reliable tool for computational micromechanics of polymer matrix composites. Full article

The development of shale gas reservoirs relies on complex fracture networks created via multistage hydraulic fracturing, yet most existing models still use oversimplified fracture geometries and therefore cannot fully capture the coupled effects of multiscale fracture topology on flow and production. To address this gap, in this study, we combine fractal geometry with the Embedded Discrete Fracture Model (EDFM) to analyze the production dynamics of hydraulically fractured horizontal wells in shale gas reservoirs. A tree-like fractal fracture network is first generated using a stochastic fractal growth algorithm, where the iteration number, branching number, scale factor, and deviation angle control the self-similar hierarchical structure and spatial distribution of fractures. The resulting fracture network is then embedded into an EDFM-based, fully implicit finite-volume simulator with Non-Neighboring Connections (NNCs) to represent multiscale fracture–matrix flow. A synthetic shale gas reservoir model, constructed using representative geological and engineering parameters and calibrated against field production data, is used for all numerical experiments. The results show that increasing the initial water saturation from 0.20 to 0.35 leads to a 26.4% reduction in cumulative gas production due to enhanced water trapping. Optimizing hydraulic fracture spacing to 200 m increases cumulative production by 3.71% compared with a 100 m spacing, while longer fracture half-lengths significantly improve both early-time and stabilized gas rates. Increasing the fractal iteration number from 1 to 3 yields a 36.4% increase in cumulative production and markedly enlarges the pressure disturbance region. The proposed fractal–EDFM framework provides a synthetic yet field-calibrated tool for quantifying the impact of fracture complexity and design parameters on shale gas well productivity and for guiding fracture network optimization. Full article

Precise and programmable magnetic field control is essential for the reliable actuation of magnetic miniature robots in biomedical applications. However, the workspace of existing systems often relies on empirical designs and lacks a clear framework to define an entire workspace with independently controllable magnetic field strength, as well as precisely specified volume, shape, and position. Here, we present a rational design framework that systematically elucidates the fundamental principles governing the generation of uniform and gradient magnetic fields using spherically distributed magnetic coil arrays (SDMCAs). We first identify the eight independent parameters that fully define the magnetic field. Using both analytical and numerical methods, we demonstrate that the control of the magnetic field strength and gradient can be decoupled. This concept is then extended to three dimensions through the development of a finite element analysis (FEA) model, which accurately simulates the spatial magnetic field distribution of complex coil geometries. The simulation results are validated experimentally, showing excellent agreement. Finally, we propose a step-by-step SDMCA design workflow that enables precise control over the magnetic field parameters within a target workspace. This framework provides a practical and scalable approach for the development of high-performance magnetic actuation systems for miniature robots. Full article

A multiscale model is developed to investigate the mechanical behavior and failure of in situ particle reinforced titanium matrix composites (PTMCs). Through the microstructural observation of the heterogeneous microscopic and mesoscopic structures in the in situ TiB/Ti55531 composites, multiscale heterogeneous models coupled to the finite element method are employed to simulate the mechanical behaviors and failures. In the atomic scale, molecular dynamics (MD) simulations are applied to determine the traction-separation (T-S) responses of the cohesive zone model (CZM) describing the Ti/TiB interface. Then, the mesoscale representative volume element (RVE) model with heterogeneous structure, including the Ti55531 matrix, the TiB particles, and their interfaces represented by the parameterized CZM, is established. The volume fraction and distribution morphology of TiB particles result from the microstructural analysis of titanium matrix composites. The simulation results show that the Young’s modulus, tensile strength and elongation of multiscale are in excellent agreement with experimental results. The stress transfer, damage evolution and fracture behavior of the TiB particles in the composites are also analyzed using this multiscale approach. Full article

Water Alternating Gas (WAG) injection is a well-established enhanced oil recovery technique that improves sweep efficiency by combining the favorable displacement characteristics of waterflooding and gas injection. This work presents a sequential Picard–Newton formulation for simulating three-phase flow under WAG conditions in heterogeneous petroleum reservoirs. The mathematical model addresses slightly compressible, immiscible oil, water, and gas phases under constant-temperature conditions, with the governing equations discretized in space and time using the finite volume method. Reservoir heterogeneity is represented through geostatistical permeability fields generated by Sequential Gaussian Simulation, capturing the spatial correlations and anisotropy characteristic of subsurface formations. The methodology is applied to investigate WAG performance in heterogeneous reservoir models with mean permeabilities of 100, 200, and 400 × 10⁻¹⁵ m² under identical 1:1 injection ratios. The numerical results successfully reproduce the cyclic saturation and production behavior characteristic of WAG processes. Comparative analysis reveals that higher permeability enhances injectivity and cumulative recovery but accelerates gas breakthrough and, in the highest-permeability case, water breakthrough, as well as production decline, illustrating the trade-off between displacement efficiency and sweep control. These findings demonstrate that the proposed framework provides an efficient and physically consistent tool for evaluating WAG strategies in heterogeneous reservoirs, with potential application to field-scale optimization of advanced recovery operations. Full article

Under the premise of a certain damping layer volume, topological optimization design of its attach shape can enable a pipeline system to achieve optimal damping performance. This paper proposes a topology optimization method for vibration reduction in spatial pipelines with damping layers based on a finite element model. A parametric modeling approach is developed for the clamp-supported spatial pipeline with viscoelastic damping layer, and both clamp-support damping and damping layer material damping are considered. Using the progressive optimization method, an optimization model is established with the modal loss factor of the pipeline system as the objective function, the existence state of each damping layer element as the design variable, and the material volume as the constraint. Further, a case study is conducted. The correctness of the dynamic model is verified by hammer and frequency sweep tests. The optimization results indicate that retaining only 30% of the damping layer volume reduces weight by 70%, while vibration attenuation performance decreases by merely 2.46% compared to the fully coated configuration, demonstrating the effectiveness of the proposed topology optimization approach. Full article

To quantitatively assess the storm surge induced by Super Typhoon Doksuri (2023) along the complex coastline of Fujian Province, a high-resolution Finite-Volume Coastal Ocean Model (FVCOM) was developed, driven by a refined Holland–ERA5 hybrid wind field with integrated physical corrections. The hybrid approach retains the spatiotemporal coherence of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis in the far field, while incorporating explicit inner-core adjustments for quadrant asymmetry, sea-surface-temperature dependency, and bounded decay after landfall. A series of numerical experiments were conducted, including paired tidal-only and full storm-forcing simulations, along with a systematic sensitivity ensemble in which bottom-friction parameters were perturbed and the anomalous (typhoon-related) wind component was scaled by factors ranging from 0.8 to 1.2. Static sea-level rise (SLR) scenarios (+0.3 m, +0.5 m, +1.0 m) were imposed to evaluate their influence on extreme water levels. Storm surge extremes were analyzed using a multi-scale coastal buffer framework, comparing two extreme extraction methods: element-mean followed by time-maximum, and node-maximum then assigned to elements. The model demonstrates high skill in reproducing astronomical tides (Pearson r = 0.979–0.993) and hourly water level series (Pearson r > 0.98) at key validation stations. Results indicate strong spatial heterogeneity in the sensitivity of surge levels to both bottom friction and wind intensity. While total peak water levels rise nearly linearly with SLR, the storm surge component itself exhibits a nonlinear response. The choice of extreme-extraction method significantly influences design values, with the node-based approach yielding peak values 0.8% to 4.5% higher than the cell-averaged method. These findings highlight the importance of using physically motivated adjustments to wind fields, extreme-value analysis across multiple coastal buffer scales, and uncertainty quantification in future SLR-informed coastal risk assessments. By integrating analytical, physics-based inner-core corrections with sensitivity experiments and multi-scale analysis, this study provides an enhanced framework for storm surge modeling suited to engineering and coastal management applications. Full article

Continuous bladder volume monitoring in a wearable format can improve outcomes for patients with bladder dysfunction, heart failure, and other conditions requiring precise fluid management. Bioimpedance-based methods offer a promising, noninvasive solution; however, the influence of patient-specific anatomy, particularly waist circumference and subcutaneous fat thickness, remains poorly characterized. In this study, we use in silico finite element modeling to quantify how these anatomical factors affect two key bioimpedance metrics: voltage change ($\Delta V$) and voltage change ratio (VCR). Comprehensive simulations were performed across 15 virtual anatomies, generating a reference dataset for guiding future analog front-end and algorithm designs. We further compared generalized volume estimation models against conventional patient-specific void regression approaches. With appropriate input scaling, the generalized models achieved performance within 10% of patient-specific calibrations and, in some cases, surpassed them. Certain configurations reduced mean average error (MAE) by more than 20% relative to individualized models, potentially enabling a streamlined setup without the need for laborious ground-truth acquisition such as voided volume collection. These results demonstrate that incorporating simple anatomical scaling can yield robust, generalizable bladder volume estimation models suitable for wearable systems across diverse patient populations. Full article

The roll-to-plate (R2P) hot-embossing process is a newly developed molding technique for the high-throughput, high-efficiency fabrication of large-area microstructured optical elements. However, this technology is limited to flat surfaces, because the thickness of the freeform optical plate varies constantly due to its specific optical design, while the roll stays cylindrical during rolling. Therefore, we developed a new profile-tunable roll with several groups of semiconductor heater/coolers (SHCs) attached around the inside wall of the roll. These SHCs can achieve tunable roll profiles at desirable positions by regulating the current for the semiconductor and then the roll temperature, thereby producing optics with a selected freeform. In this paper, the circumferential bulging profiles and corresponding roll temperature fields were thoroughly investigated under various heater/cooler layouts and roll sizes. A circumferential finite element model of the profile-tunable roll was established using the finite element software MSC.MARC 2020 and then verified on the experimental platform. In addition, the fundamental relationship between the bulging values and temperature distributions of the roll and parameters, such as the outer diameter and inner diameter of the roll, the temperature of the semiconductor heater/cooler, and the single piece influence angle, was eventually established. This paper offers a unique fabrication method for high-volume optical freeform plates at extremely low cost and builds a foundation for further research on the axial deformation and temperature distribution of the developed roll for freeform optics and R2P hot-embossing experiments for freeform optical components. Full article

Microwave ablation, as a minimally invasive technique used for the treatment of tumors, is highly dependent on the performance of ablation antennas for its therapeutic effect. Clinically, antennas are required to form roughly spherical ablation zones with sufficient volume within a limited time. To meet this requirement, this paper establishes finite element models and conducts multi-objective optimization on fully water-cooled dipole antenna and partially water-cooled choke dipole antenna based on different water-cooled structures. On the premise of minimizing reflection coefficient and maximizing ablation volume, a three-dimensional objective space is constructed by introducing the minimization of roundness error, and the set of Pareto solutions is solved. The CRITIC-TOPSIS method is used to balance multi-objective conflicts and select the unique optimal solution from the Pareto set. By analyzing the optimal solution, simulation results show that the optimized antennas can effectively form near-spherical ablation shapes while minimizing the reflection coefficient and maximizing the ablation volume. Among these, the partially water-cooled antenna exhibits superior electromagnetic characteristics and ablation profile, whereas the fully water-cooled antenna demonstrates better temperature field behavior. Full article

Numerical modeling of asphalt concrete and other asphalt mixes used in road engineering is an actively developed research field. In this study, a framework combining the following aspects is presented: (1) reliable reconstruction of the real samples; (2) using realistic material models of the microstructure constituents; and (3) providing high numerical efficiency. Asphalt concrete microstructure was reconstructed using image processing. The Burgers material model was applied to the subdomains identified as the mastic, and the linear elastic model was used for the aggregate particles. In order to increase the numerical efficiency, the developed homogenization method was used to accelerate the finite element analysis. The main novelty of this study is the integration of the Burgers material model with the numerical homogenization in the small strains range. A homogenization error measured in the maximum norm was smaller than 7% in the presented numerical examples (6.8% for the elasticity and 6.9% for the viscoelasticity problem, respectively). Simultaneously, the observed reduction in the number of degrees of freedom was larger than 510 times. The obtained results confirmed the applicability of the developed methodology to the analysis of the viscoelastic materials in the range of the small strains. Full article

Heat pipe (HP) performance depends on several interacting physical phenomena, such as phase change and liquid transport within the wick. The latter is strongly affected by the permeability of the porous material, whose accurate evaluation is essential for a reliable prediction of the heat transfer capability. This work investigates the permeability of an additively manufactured aluminum wick by comparing two experimental and two numerical methods, using acetone and ethanol as working fluids. In the first experimental approach, the analytical capillary rise curve was fitted to data obtained through infrared thermography and by monitoring the fluid level decrease in an input reservoir. In the second, the mass flow rate through the samples was directly measured under an imposed pressure difference. Numerical simulations were performed using the Finite Volume Method in OpenFOAM and the Lattice Boltzmann Method in Palabos on computational domains reconstructed from microtomographic scans of a real wick. The permeability values, determined through the Darcy–Forchheimer formulation, were then used to estimate the maximum heat transport capability based on the capillary limit model for representative HP geometries. The results show that all four methods provide consistent permeability estimates, with deviations below $30\%$ in the porosity range relevant to real HPs. Full article