We present an axisymmetric computational model to study the heating processes of gold nanoparticles, specifically nanorods, in aqueous medium by femtosecond laser pulses. We use a two-temperature model for the particle, a heat diffusion equation for the surrounding water to describe the heat transfer processes occurring in the system, and a thermal interface conductance to describe the coupling efficiency at the particle/water interface. We investigate the characteristic time scales of various fundamental processes, including lattice heating and thermal equilibration at the particle/surroundings interface, the effects of multiple laser pulses, and the influence of nanorod orientation relative to the beam polarization on energy absorption. Our results indicate that the thermal equilibration at the particle/water interface takes approximately 500 ps, while the electron-lattice coupling is achieved at approximately 50 ps when a 48×14 nm gold nanorod is heated to a maximum temperature of 1270 K with the application of a laser pulse having 4.70 J/m2 average fluence. Irradiation by multiple pulses arriving at 12.5 ns time intervals (80 MHz repetition rate) causes a temperature increase of no more than 3 degrees during the first few pulses with no substantial changes during the subsequent pulses. We also analyze the degree of the nanorods’ heating as a function of their orientation with respect to the polarization of the incident light. Lastly, it is shown that the temperature change of a nanorod can be modeled using its volume equivalent sphere for femtosecond laser heating within 5–15% accuracy.

In this study, a two-dimensional axisymmetric computational model of spark discharge in air is presented to provide a better understanding of the dynamics of the process. Better understanding of the modeling issues in spark discharge processes is an important issue for the automotive spark plug community. In this work we investigate the evolution of the shock front, temperature, pressure, density, geometry, and flow history of a plasma kernel using various assumptions that are typically used in spark discharge simulations. A continuum, inviscid, heat conducting, single fluid description of the flow is considered with radiative losses. Assuming local thermal equilibrium, the energy input due to resistive heating is determined using a specified current profile and temperature-dependent gas electrical conductivity in the gap. The spark discharge model focuses on the early time flow physics, the relative importance of conduction and radiation losses, the influence of thermodynamic model choice and ambient pressure effects.

A system level, steady-state thermodynamics model for an automotive PEM fuel cell system was developed to investigate the effects of vehicle speed and operating pressure on the size of the system components, heat and water formation, fuel consumption, fuel cell, and system efficiency. Moreover, the consequences of the choices of membrane’s thickness and ionic conductivity on thermal and system efficiencies as a function of vehicle speed are analyzed. The model consists of a PEM fuel cell stack model and supplementary models for all necessary auxiliary components. Results show that increasing the system pressure has a significant positive impact on the water balance characteristics of the system, since less water is needed to reach the required relative humidity levels for the reactants. On the other hand, the high-pressure system requires more power in order to operate the compressor, which in turn, decreases the system efficiency. Decreasing air stoichiometry at high operating pressures improves the water management but has no effect at low pressures. Results also show that increasing the membrane’s ionic conductivity and decreasing its thickness enhances the system efficiency especially at higher vehicle speeds. Lastly, it is obtained that the system efficiency decreases as the vehicle speed increases.

Marfan syndrome (MS) is a genetic disorder often associated with the development of aortic aneurysms, leading to severe vascular complications. The progression of this condition is intricately linked to hemodynamic factors such as wall shear stress (WSS) and von Mises stress, as abnormal distributions can contribute to thrombus formation, endothelial damage, and the worsening of aneurysmal conditions. In this study, six vascular models were analyzed: four representing diseased aortas with Marfan syndrome aneurysms and two healthy aortic models for comparison. The models were sourced from Vascular Model Repository, and computational fluid dynamics (CFD) simulations were conducted using a Newtonian fluid model and the shear stress transport (SST) k–ω turbulent transitional model to evaluate WSS and von Mises stress. Fluid–structure interaction was employed to incorporate vessel wall interaction, and pulsatile inlet velocity profiles were used to simulate physiological blood flow, capturing time-dependent hemodynamic variations. The results revealed significant differences between healthy and diseased aortic models. In healthy models, WSS was uniformly distributed, with values consistently below 40 Pa, reflecting stable vascular conditions. Conversely, the diseased models exhibited highly non-uniform WSS distributions, with notably lower values in aneurysmal regions, contributing to thrombus formation, with elevated WSS in areas like the carotid and subclavian arteries due to geometric and hemodynamic complexities. The von Mises stress analysis identified regions of heightened rupture risk, particularly on the superior side of case MS1, where both von Mises stress and WSS reached their highest values among all cases. Physics-informed neural networks demonstrated strong agreement with CFD results while significantly reducing computational cost, highlighting their potential for real-time clinical applications. These findings underscore the critical role of hemodynamic factors in aneurysm progression and rupture risk, offering valuable insights for optimizing diagnostic and therapeutic strategies in vascular diseases.