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John Thornton

Publications and source records attributed to John Thornton.

Assessment of the Fluid Dynamics Boundary Condition in Ablating or Blowing Flows

Improved models of ablative thermal protection systems have enabled the treatment of materials and fluid behavior in a coupled manner. This paper reports a new approach to modeling the interface between fluid and material, with attention to the conservation of species mass flux and energy on the fluid side of the interface. The general equation is presented and is shown to recover the traditional uncoupled fluid/materials response interface. Including the chemical reaction terms on the CFD side of the interface makes the heat flux exchange independent of the thermodynamic reference state and, therefore, a measurable quantity. Doing so allows the material response solver to take as input the surface heat flux rather than a film coefficient. Removing the film coefficient approximation enables more direct solution of vehicle thermal response but requires consistency in the wall state. The mixing of the shock layer and pyrolysis gas is then computed with finite rate chemistry within the fluid solver. The boundary conditions described have been implemented in the DPLR v4.05.1 code. Char removal is captured using finite rate chemistry in DPLR’s gas surface interaction module. Aspects of coupling these solutions to material response are discussed.

Ablation

Assessment of the Fluid Dynamics Boundary Condition in Ablating or Blowing Flows

Improved models of ablative thermal protection systems have enabled the treatment of materials and fluid behavior in a coupled manner. This paper reports a new approach to modeling the interface between fluid and material, with attention to the conservation of species mass flux and energy on the fluid side of the interface. The general equation is presented and is shown to recover the traditional uncoupled fluid/materials response interface. Including the chemical reaction terms on the CFD side of the interface makes the heat flux exchange independent of the thermodynamic reference state and, therefore, a measurable quantity. Doing so allows the material response solver to take as input the surface heat flux rather than a film coefficient. Removing the film coefficient approximation enables more direct solution of vehicle thermal response but requires consistency in the wall state. The mixing of the shock layer and pyrolysis gas is then computed with finite rate chemistry within the fluid solver. The boundary conditions described have been implemented in the DPLR v4.05.1 code. Char removal is captured using finite rate chemistry in DPLR’s gas surface interaction module. Aspects of coupling these solutions to material response are discussed.

Ablation

Porous Microstructure Analysis (PuMA) software

The Porous Microstructure Analysis (PuMA) software was developed to provide a robust and efficient framework for computing material properties based on their microstructures. The development was motivated by advancements in X-ray microtomography, an imaging technology that can resolve the structure of a material at a sub-micron scale, in 3D and even in 4D (over time). PuMA provides the capability of computing a comprehensive spectrum of properties, from the most fundamental geometric features of a microstructure, to advanced anisotropic thermo-elastic properties. In addition, the software can generate artificial microstructures, ranging from simple analytical shapes to complex fibrous woven and non- woven geometries, which can be used in performance optimization studies. This presentation will highlight many of the capabilities of the recent open-source release.

microtomography

Uranus Probe Entry and Descent Trajectory Design

Uranus has been recently selected as the priority destination for a future Flagship-class mission. The present study designed a mission concept including an orbiter and an atmospheric probe to Uranus. Specific concerns explored by this study included meeting structural requirements under high deceleration loads, designing a Thermal Protection System (TPS) to withstand the high heat fluxes for Uranus entry, and ensuring communication availability for science data up-link between the probe and the orbiter. The results of the study were used to support the 2023-2032 Planetary Science and Astrobiology Decadal Survey.

Uranus Mission Concept

Porous Microstructure Analysis (PuMA) software

- Motivation and objectives - Overview of PuMA - Open-source release - Material properties computation - Artificial geometry generation - Property homogenization for anisotropic media - Fiber orientation - Conductivity - Elasticity - Permeability

homogenization

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography