Search NASA⌕ Search

Engineering topics

Joseph C Schulz

Publications and source records attributed to Joseph C Schulz.

Coupled Fluid Dynamics and Material Response Simulations for Nitrogen High Enthalpy Flows

The study focuses on the interaction of nitrogen flows with thermal protection systems during atmospheric re-entry for NASA flight missions. The Ares multiphysics coupling tool is employed to investigate the coupling between the fluid (US3D) and material response (Icarus) solvers using various modeling approaches. These approaches include the equilibrium thin-film coefficients approach, a weakly coupled approach with temperature coupling, and an approach considering the full chemical composition of the surface and the transfer of pyrolysis gases. The objective is to understand and accurately represent the mechanisms of nitrogen interaction with the surface, such as nitridation and catalytic recombination. The study aims to assess the accuracy of the different approaches by comparing them to experimental results obtained from NASA arc-jet facilities. By addressing these challenges and improving the understanding of nitrogen-surface interactions, it is expected to enhance the design and performance analysis of thermal protection systems for future missions.

Ablation↗

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗

Stochastic Reconstruction of Thermal Protection Material Properties from Arc-Jet Experiments

Material response models are used to assess reliability using variances in the bond-line temperature predictions based on uncertainties in trajectory, aerothermal environment, and material properties. A key deficiency in the current approach is that input uncertainties are too often subjective, empirical, or ad-hoc, and are not rigorously linked to the arc-jet test data used to develop the TPS material model. While materials such as PICA are well understood, future missions may require more novel materials such as HEEET where unknown uncertainties have real consequences on the ability to assess reliability. A quantifiable estimate of reliability requires an iterative methodology where the parameters driving the variance in bond-line temperature (for example) are systematically identified. A test campaign to collect data or develop new models can then be identified to reduce those input uncertainties. A Bayesian inference loop defines these connections mathematically, i.e., prior knowledge about uncertainty is updated based on observation. While these concepts are well known (and often applied intuitively in a non-rigorous approach), only recent advances in reduced-order modelling have made them computationally viable methods for engineering. By replacing deterministic inverse methods with stochastic approaches, the hope is new materials proposed for future missions can more rapidly be developed with a greater understanding of the TPS material reliability. Two additional steps for the analysis of arc jet test data are discussed. The first is ability to construct a reduced-order model using material response simulations (Icarus/US3D) of the arc-jet test articles, and the second is the inclusion of this surrogate model in the Bayesian inversion process. Both capabilities will be demonstrated using prior PICA arc-jet test data. The quality of a surrogate model will be investigated and the variances on the calibrated material properties will be compared to our current understanding of the PICA material model.

Material response↗

Icarus Application to Dragonfly Heatshield

Icarus, an in-house material response solver developed at NASA Ames, is applied to perform 2-D bondline-temperature analysis on the heatshield surface of the latest Dragonfly entry system design for a mission to Titan. Two axisymmetric domains are used: the near-shoulder region and the entire heatshield. The heatshield consists of a PICA TPS bonded to a layered system of Aluminum honeycomb wrapped by an M55J carbon-fiber facesheet. The backshell, which is also included for more accurate analysis, consists of similar materials layered. Icarus simulations using both domains indicate that the in-plane thermal conductivity property of the M55J facesheet is observed to play a dominant role in bondline temperature. Similarly, the maximum bondline temperature is found around the PICA-tile-interface region instead of the near-shoulder region or the stagnation point based on the current trajectory using the orthotropic properties of M55J. Therefore, these findings indicate the significance of 2-D or higher-dimensional material modeling analysis in fully understanding how bondline temperature behaves across the heatshield and obtaining a basis for TPS design locations. Verification at different radial locations ahead of the shoulder, where thermal conduction is close to 1-D, between Icarus (2-D), Icarus (1-D), and FIAT is performed and good agreement is observed. With the entire heatshield domain, the total mass loss of the aeroshell materials is approximately 3% of their initial mass potentially due to thermal decomposition of phenolic resins inside PICA under the current high-heating environment.

TPS material modeling↗