arXiv subjects

Arturo Rodriguez

Publications and source records attributed to Arturo Rodriguez.

14 recordsLinked to original sources

arXiv2026

N.E.O.N.-Bridge Geometry Determination: Turbulence Modeling of Individual N.E.O.N.-Bridge Segment

The N.E.O.N.-Bridge is a capstone project being developed by students at TAMUCC, under the oversight of Los Alamos National Laboratory. The project requires the development of a hull geometry for an autonomous bridge segment optimized to support onboard electronics and camera systems while maintaining stability in a dynamic water environment. Traditional ribbon bridge systems typically do not experience intense hydrodynamic loading due to current transportation and assembly methods, whereas the N.E.O.N-Bridge must continuously withstand forces from dynamic flow patterns. The requirement for a hull geometry to have both hydrodynamic design and rigidity, as in current ribbon bridges, has posed unique challenges. The current hull designs were evaluated through turbulent water-flow simulations performed with ANSYS Discovery. Boundary conditions were determined based on the forward motion of the bridge segment, simulating inlet and outlet flows, and the resulting pressure distribution. A waterline-based geometric constraint derived from the camera system's elevation enabled the simulation to model flow characteristics in an operational scenario. Velocity fields, pressure contours, and turbulent flow patterns were analyzed to identify areas of high loading and hydrodynamic inefficiencies. The findings will provide essential performance metrics that could be used to make design adjustments to the overall hull geometry. The simulation results will support improvements in stability, structural rigidity, and overall effectiveness of the hull geometry, advancing the development of the N.E.O.N-Bridge segments.

physics.flu-dyn↗

arXiv2026

Explicit and Implicit Finite Difference Solvers Implemented in JAX for Shock Wave Physics

Shock dynamics and nonlinear wave propagation are fundamental to computational fluid dynamics (CFD) and high-speed flow modeling. In this study, we developed explicit and implicit finite-difference solvers for the one-dimensional Burgers viscous equation to model shock formation, propagation, and dissipation. The governing equation, which incorporates convective and diffusive effects, serves as a simplified analogue of the Navier-Stokes equations. Using the Finite-JAX framework, each solver is implemented with upwind and central finite-difference schemes for the convective and diffusive terms, respectively. Time integration is performed using explicit forward Euler and implicit backward-time central space (BTCS) schemes under periodic and Dirichlet boundary conditions. Stability is ensured by the Courant-Friedrichs-Lewy (CFL) criteria for the convective and diffusive components. Numerical experiments quantify the accuracy, convergence, and real-time performance of JAX across CPUs, GPUs, and TPUs, demonstrating that JAX maintains fidelity while achieving portability. The results show that the explicit scheme captures impact accurately under strict time-step constraints, while the implicit formulation provides greater stability and accuracy at a higher computational cost. Taken together, these results establish a reproducible dataset for benchmarking CFD solvers and training machine learning models for nonlinear transport and impact-driven phenomena. Our new implementation of FiniteJAX enhances the portability, scalability, and performance of solvers based on the JAX framework developed by Google DeepMind.

physics.flu-dyn↗

arXiv2025

Verification of Convergent-Divergent Nozzle Designs in Propulsion Aerospace Applications

The performance of convergent and divergent nozzles is critical in aerospace propulsion systems, where the efficient expansion of high-temperature, high-pressure gases directly impacts thrust generation. In this study, we investigate a series of nozzle geometries using numerical simulations in ANSYS Fluent, guided by classical compressible flow theory, initially developed by Ludwig Prandtl. The governing equations of conservation of mass, momentum, and energy are solved under steady-state conditions, with emphasis on shock formation, boundary-layer effects, and Mach number distributions across the nozzle throat and divergent section. Parametric analyses are conducted to evaluate the influence of nozzle contour, area ratio, and throat geometry on flow acceleration and thrust coefficient. The results demonstrate close agreement with theoretical predictions of isentropic compressible flow while also highlighting deviations due to viscous and three-dimensional effects. These findings provide design insights for optimizing nozzle performance across propulsion applications, from launch vehicles to high-speed air-breathing systems. We obtained absolute error differences of 2.05 percent, 6.03 percent, and 9.9 percent in the throat temperature measurements for the RL10B2, SSME-40k, and A-1 nozzles, respectively.

physics.flu-dyn↗

arXiv2025

Numerical and analytical modeling of heat equation in current-carrying conductors using the heat equation implemented using Finite-JAX

Current-carrying conductors inevitably experience resistive heating due to the material's finite electrical conductivity. The resulting temperature distribution within the wire has essential implications for structural integrity, efficiency, and long-term reliability of electronic and power systems. In this work, we model the steady-state heat distribution in a current-carrying wire using the classical heat conduction equation. In a two-dimensional formulation, heat transport is considered both along and across the conductor. The governing partial differential equation is discretized using finite-difference methods implemented in Finite-JAX, with appropriate initial and boundary conditions, including the Dirichlet condition relevant to practical scenarios. Time integration is performed using the Euler explicit scheme, and stability constraints are systematically examined. To assess the accuracy of the numerical approach, we compare the computed temperature fields with the exact analytical solution of the heat equation for canonical geometry. Results show that the numerical prediction converges toward the analytical solution, with error norms decreasing at the expected order of accuracy. This study demonstrates how the heat equation provides a rigorous mathematical foundation for modeling resistive heating in conductors. The errors between the numerical and analytical solutions are 1.981 K, 0.8975 K, and 0.7917 K, corresponding to the L-infinity, L1, and L2 norms. For tensor computations, TPUs deliver the highest performance, surpassing GPUs and CPUs.

math.NA↗

arXiv2025

Cross-Model Verification of Wall-Bounded Flows using Finite-JAX

Accurate prediction of wall-bounded flows remains central to advancing both theoretical understanding and computational methods in fluid mechanics. In this study, we perform a numerical simulation of channel flow using a complementary approach: a high-performance, differentiable finite-difference solver developed in JAX (Finite-JAX), and an analytical solution derived from the Navier-Stokes Equations, also known as the Hagen-Poiseuille equation. The solver is applied to the incompressible Navier-Stokes equations, along with appropriate boundary conditions, to capture canonical flow features, including velocity profiles and pressure gradients. Cross-model verification is conducted by systematically comparing numerical results between Finite-JAX and the analytical solution, with a focus on velocity distributions. In addition, numerical results are benchmarked against analytical solutions for the laminar regime, allowing direct quantification of the verification accuracy. Our findings demonstrate that cross-model verification not only strengthens confidence in simulation fidelity but also provides a pathway for integrating differentiable solvers with established computational fluid dynamics platforms, paving the way for future fluid flow research. The performance of Finite-JAX on Wall-Bounded Flows is 0.014765 in the L2 norm.

physics.flu-dyn↗

arXiv2025

Computational Aerothermal Framework and Analysis of Stetson Mach 6 Blunt Cone

Accurately predicting aerothermal behavior is paramount for the effective design of hypersonic vehicles, as aerodynamic heating plays a pivotal role in influencing performance metrics and structural integrity. This study introduces a computational aerothermal framework and analyzes a blunt cone subjected to Mach 6 conditions, drawing inspiration from Stetson foundational experimental work published in 1983. While the findings offer significant insights into the phenomena at play, the study highlights an urgent necessity for integrating chemical kinetics to comprehensively capture non-equilibrium effects, thereby enhancing the predictive accuracy of computational fluid dynamics (CFD) simulations. This research implements a one-way coupling method between CFD simulations and heat conduction analysis, facilitating a thorough investigation of surface heat transfer characteristics. The numerical results elucidate discrete roughness elements' impact on surface heating and fluid dynamics within high-speed airflow. Furthermore, the investigation underscores the critical importance of accounting for non-equilibrium thermochemical effects in aerothermal modeling to bolster the accuracy of high-enthalpy flow simulations. By refining predictive computational tools and deepening understanding of hypersonic aerothermal mechanisms, this research lays a robust groundwork for future experimental and computational endeavors, significantly contributing to advancing high-speed flight applications.

physics.flu-dyn↗

arXiv2024

Current State of Atmospheric Turbulence Cascades

Turbulence cascade has been modeled using various methods; the one we have used applies to a more exact representation of turbulence where people use the multifractal representation. The nature of the energy dissipation is usually governed by partial differential equations that have been described, such as Navier-Stokes Equations, although usually in climate modeling, the Kolmogorov turbulence cascading approximation leads towards an isotropic representation. In recent years, Meneveau et al. have proposed to go away from Kolmogorov assumptions and propose multifractal models where we can account for a new anisotropic representation. Our research aims to use Direct Numerical Simulations (DNS) from the JHU Turbulence Database and Large Eddy Simulations (LES) we simulated using OpenFOAM to predict how accurate these simulations are in replicating Meneveau experimental procedures with numerical simulations using the same rigorous mathematical approaches. Modeling turbulence cascading using higher fidelity data will advance the field and produce faster and better remote sensing metrics. We have written computer code to analyze DNS and LES data and study the multifractal nature of energy dissipation. The box-counting method is used to identify the multifractal dimension spectrum of the DNS and LES data in every direction to follow Meneveau work to represent turbulence-cascading effects in the atmosphere better.

physics.flu-dyn↗

arXiv2024

Computational Analysis of the Temperature Profile Developed for a Hot Zone of 2500{\deg}C in an Induction Furnace

Temperature gradients developed at ultra-high temperatures create a challenge for temperature measurements that are required for material processing. At ultra-high temperatures, the components of the system can react and change phases depending on their thermodynamic stability. These reactions change the system's physical properties, such as thermal conductivity and fluidity. This phenomenon complicates the extrapolation of temperature measurements, as they depend on the thermal conductivity of multiple insulating layers. The proposed model is an induction furnace employing an electromagnetic field to generate heat reaching 2500 degrees Celsius. A heat transfer simulation applying the finite element method determined temperatures and verified experimentally at key locations on the surface of the experimental setup within the furnace. The computed temperature profile of cylindrical graphite crucibles embedded in a larger cylindrical graphite body surrounded by zirconia grog is determined. Compared to experimental results, the simulation showed a percentage error of approximately 3.4 percent, confirming its accuracy.

physics.comp-ph↗

arXiv2024

Partition of Unity Physics-Informed Neural Networks (POU-PINNs): An Unsupervised Framework for Physics-Informed Domain Decomposition and Mixtures of Experts

Physics-informed neural networks (PINNs) commonly address ill-posed inverse problems by uncovering unknown physics. This study presents a novel unsupervised learning framework that identifies spatial subdomains with specific governing physics. It uses the partition of unity networks (POUs) to divide the space into subdomains, assigning unique nonlinear model parameters to each, which are integrated into the physics model. A vital feature of this method is a physics residual-based loss function that detects variations in physical properties without requiring labeled data. This approach enables the discovery of spatial decompositions and nonlinear parameters in partial differential equations (PDEs), optimizing the solution space by dividing it into subdomains and improving accuracy. Its effectiveness is demonstrated through applications in porous media thermal ablation and ice-sheet modeling, showcasing its potential for tackling real-world physics challenges.

cs.LG↗

arXiv2024

Designing an Optimal Scoop for Holloman High-Speed Test Track Water Braking Mechanism using Computational Fluid Dynamics

Specializing in high-speed testing, Holloman High-Speed Test Track (HHSTT) uses water braking to stop vehicles on the test track. This method takes advantage of the higher density of water, compared to air, to increase braking capability through momentum exchange by increasing the water content in that section at the end of the track. By studying water braking using computational fluid dynamics (CFD), the forces acting on tracked vehicles can be approximated and prepared before actual testing through numerical simulations. In this study, emphasis will be placed on the brake component of the tracked sled, which is responsible for interacting with water to brake. By discretizing a volume space around our brake, we accelerate the water and air to simulate the brake coupling relatively. The multiphase flow model uses the governing equations of the gas and liquid phases with the finite volume method to perform 3D simulations. By adjusting the air and water inlet velocity, it is possible to simulate HHSTT sled tests at various operating speeds.

physics.flu-dyn↗

arXiv2024

Computational Investigation of Roughness Effects on Boundary Layer Transition for Stetson's Blunt Cone at Mach 6

In this aerothermal study, we performed a two-dimensional steady-state Computational Fluid Dynamics (CFD) and heat conduction simulation at Mach 6. The key to our methodology was a one-way coupling between CFD surface temperature as a boundary condition and the calculation of the heat transfer flux and temperatures inside the solid stainless-steel body of a nose geometry. This approach allowed us to gain insight into surface heat transfer signatures with corresponding fluid flow regimes, such as the one experienced in laminar fluid flow. We have also examined this heat transfer under roughness values encountered in Stetson's studies at the Wright-Patterson Air Force Base Ludwig tube. To validate our findings, we have performed this type of work on a blunt cone, specifically for the U.S. Air Force. The research focuses on predicting transition onset using laminar correlations derived from Stetson's experimental studies, examining the role of discrete roughness elements. Findings emphasize the importance of incorporating non-equilibrium effects in future computational frameworks to enhance predictive accuracy for high-speed aerodynamic applications.

physics.flu-dyn↗

arXiv2024

Empowering Abilities: Increasing Representation of Students with Disabilities in the STEM Field

The ExploreSTEM Summer Camps 2023 were designed to deliver inclusive STEM education to students aged 14 to 22 years with disabilities. This paper presents a thorough examination of the 2023 camp program, emphasizing the pivotal role of inclusive STEM education in potentially shaping students' personal and academic trajectories. The curriculum encompassed four weeklong fundamental STEM domains: Internet of Things (IoT), Computational Engineering, Artificial Intelligence (AI), and Augmented and Virtual Reality (AR/VR). Within Camp 1, students actively engaged with Dash robots, employing dedicated programming environments to command actions and gather sensor data, fostering interactions with the IoT platform and facilitating seamless data transmission. Camp 2 was dedicated to acquainting students with foundational computational engineering principles, establishing a robust framework for comprehending intricate engineering concepts. Camp 3 commenced with insightful presentations elucidating AI applications across multifaceted industries, including engineering, healthcare, and education, illuminating AI's pervasive influence on contemporary society. The primary aim of Camp 4 was to introduce students to the immersive domains of AR and VR, showcasing their applications beyond conventional STEM disciplines into everyday life experiences. The amalgamation of informative presentations, interactive activities, and a nurturing learning environment cultivated an engaging and enriching experience for all participants. By embracing inclusivity and harnessing innovative pedagogical approaches, the ExploreSTEM Summer Camps empowered students to explore, innovate, and excel within the dynamic realm of STEM education.

econ.GN↗

arXiv2024

Characterisation and simulation of stitched CMOS strip sensors

In high-energy physics, there is a need to investigate alternative silicon sensor concepts that offer cost-efficient, large-area coverage. Sensors based on CMOS imaging technology present such a silicon sensor concept for tracking detectors. The CMOS Strips project investigates passive CMOS strip sensors fabricated by LFoundry in a 150nm technology. By employing the technique of stitching, two different strip sensor formats have been realised. The sensor performance is characterised based on measurements at the DESY II Test Beam Facility. The sensor response was simulated utilising Monte Carlo methods and electric fields provided by TCAD device simulations. This study shows that employing the stitching technique does not affect the hit detection efficiency. A first look at the electric field within the sensor and its impact on generated charge carriers is being discussed.

physics.ins-det↗

arXiv2022

Characterization of Passive CMOS Strip Sensors

Recent advances in CMOS imaging sensor technology , e.g. in CMOS pixel sensors, have proven that the CMOS process is radiation tolerant enough to cope with certain radiation levels required for tracking layers in hadron collider experiments. With the ever-increasing area covered by silicon tracking detectors cost effective alternatives to the current silicon sensors and more integrated designs are desirable. This article describes results obtained from laboratory measurements of silicon strip sensors produced in a passive p-CMOS process. Electrical characterization and charge collection measurements with a 90Sr source and a laser with infrared wavelength showed no effect of the stitching process on the performance of the sensor.

physics.ins-det↗