Anindya Ghoshal

The development of hypersonic aircraft is increasingly crucial for air defense and civil aviation; however, surface material ablation that these vehicles encounter while in flight continues to be a significant obstacle. Due to their ability to withstand high temperatures and high oxide melting-temperatures, ultra-high temperature ceramic matrix composites (UHTCMCs) represent a promising class of materials for these vehicles. Active oxidation of UHTCMCs has been highlighted in recent studies as a means of assessing the thermomechanical performance and longevity of leading edges. Current approaches incorporate experimental data into fluid–structure interaction (FSI) and computational fluid dynamics (CFD) simulations, but they rely on the assumption of chemical equilibrium, which means they miss important thermochemical interactions at the material interface in shock boundary-layer conditions and high-speed aerothermodynamics. Predicting material recession and the transition from passive to active oxidation during hypersonic flight requires an understanding of these interactions. The present research fills important scientific gaps by adding a new ablative model into a specialized aerothermal heating solver, Aeroheating and Thermal Analysis Code (ATAC-1), for thermal protection system (TPS) materials in high-speed flight scenarios. The model predicts the species that will be ablated from the vehicle surface by using experimental emissivity data for silicon carbide (SiC) and molecular dynamics (MD) simulations. This is a major step forward in ablative modeling. This method shows how physics-based atomistic simulations can directly improve predictions of complex macroscale hypersonic flow interactions and material recession within model-based engineering design frameworks by combining aerothermal analysis codes with MD-informed reactions.

High temperature exhaust ducts in modern gas turbine engines are exposed to particle-laden flows in which solid particle erosion can limit service life and degrade performance. This study evaluates the erosion response of Inconel 625 and three oxide/oxide ceramic matrix composites (Ox/Ox CMCs) reinforced with Nextel™ 312, 610, or 720 fibers under alumina jet impingement at 650 °C. Erosion experiments spanning impingement angles of 5° – 15° revealed angle- and material-dependent scar morphologies and degradation modes. Inconel exhibited ductile ploughing with discoloration from oxidation, whereas the CMCs showed brittle matrix removal and fiber fragmentation. Using exposure-normalized data, maximum wear depth versus impingement angle followed a power-law over 5° – 15°; however, invariance of depth wear rate across exposure was observed only for Inconel and N720. Elliptical contour fitting of profilometry maps enabled evaluation of a volume-to-surface area metric that plateaued at approximately 28 % of the maximum depth across materials, facilitating translation from concentrated jet erosion to an effective uniform erosion estimate. Scanning electron microscopy imaging revealed that Inconel’s erosion morphology varied strongly with impingement angle, while the CMCs displayed anisotropic fracture features governed by fiber orientation. These results provide a quantitative baseline for comparing composite and metallic materials and support the feasibility of Ox/Ox CMCs as potential erosion-resistant alternatives to conventional alloys in exhaust systems.

The molten sand that is a mixture of calcia, magnesia, alumina and silicate, known as CMAS, is characterized by its high viscosity, density and surface tension. The unique properties of CMAS make it a challenging material to deal with in high-temperature applications, requiring innovative solutions and materials to prevent its buildup and damage to critical equipment. Here, we use multiphase many-body dissipative particle dynamics simulations to study the wetting dynamics of highly viscous molten CMAS droplets. The simulations are performed in three dimensions, with varying initial droplet sizes and equilibrium contact angles. We propose a parametric ordinary differential equation (ODE) that captures the spreading radius behaviour of the CMAS droplets. The ODE parameters are then identified based on the physics-informed neural network (PINN) framework. Subsequently, the closed-form dependency of parameter values found by the PINN on the initial radii and contact angles are given using symbolic regression. Finally, we employ Bayesian PINNs (B-PINNs) to assess and quantify the uncertainty associated with the discovered parameters. In brief, this study provides insight into spreading dynamics of CMAS droplets by fusing simple parametric ODE modelling and state-of-the-art machine-learning techniques.

This paper presents a preliminary study of the effects residual plastic strains have on Lamb wave velocities and time of flight measurements. The potential application of this research is non-destructive evaluation and structural health monitoring, particularly reconstructing plastic strain fields. The finite deformation of a semi-infinite plate due to residual plastic strain is used to accommodate the changes in plate thickness and elongation. The results show that the S₀ mode exhibits significant variations in group velocity in the highly dispersive regions, as much as a 2% increase in velocity with a 1% plastic strain. However, for time of flight measurements, the plate elongation had an order of magnitude effect rather than showing velocity changes. By exploiting time delay measurements, it may be possible to use wave speed measurements to determine plastic zones through Lamb-like waves.

Strategically located Fiber Bragg Grating (FBG) Sensors have been proposed as an in situ method to increase the signal to noise ratio (SNR) for metallic and composite components. This paper presents a systematic study that investigates the viability of FBG Sensors under high strain rate loading by initially measuring 1D-strains in a compression Hopkinson bar experiment, followed by 2D full-field strain-tensor in impact and blast experiments on plates. Specifically, high strain rates from commercialized FBG Sensors are compared to traditional resistive and semi-conductor based strain gages under various levels of 1D high strain rate loading. In the projectile-plate impact experiments, full-field back-surface strain measured using FBG Sensor arrays are compared with that measured from 3D surface Digital Image Correlation (3D-sDIC) strain measuring technique. Finally, strains in welded steel plates subjected to high explosive discharge are monitored with mounted FBG Sensors on the back surface. From this study, potential improvements in the SNR of FBG Sensors are recommended, and the survivability of these sensors under more complex, dynamic loading is evaluated.

Embedded sensors are used in layers of composite structures to provide local damage detection. The presence of these sensors causes material and geometric discontinuities which in turn causes unwanted peaks of stress and strain with consequences on stiffness reduction. Often several of these sensors are embedded in structures aggregating the adverse effects of discontinuities to degrade the structural integrity. Structural damage is a sparse phenomenon and the mechanical metrics are smooth functions with few spikes near the location of damage. This sparsity and spikiness can be exploited to reduce the number of embedded sensors in composite structures. The goal of this paper is to adapt the compressed sensing theory and detect damage using far fewer sensors than conventionally possible. To demonstrate the efficacy of our approach, we performed a numerical experiment on a rectangular plate with a center hole, and have shown that the 2D strain-field can be recovered from few samples of discrete strain measurements acquired by embedded sensors.