Engineering topics

Jeremie Bernard Erwin Meurisse

Publications and source records attributed to Jeremie Bernard Erwin Meurisse.

5 records

NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

NASA NTRSDate not supplied

Material Response Modeling of Ablative Thermal Protection Systems using PATO

Developing thermal protection systems (TPS) for future space vehicles involves an extensive design and test cycle. A key component of the cycle is determining margins for a safe design that rely on confidence in the performance of the TPS. Predicting the complicated multiphysics phenomena that occur during atmospheric entry requires high-fidelity modeling tools. To this end, the Porous-material Analysis Toolbox based on OpenFOAM (PATO) has been developed. PATO is an open-source software for computing material response of reactive porous materials submitted to high-temperature environments. Recent applications of PATO include computation of the full heatshield 3D material response from the Mars Science Laboratory atmospheric entry and ablation during arc jet testing. Current efforts are underway to loosely couple PATO with other discipline specialized codes including hypersonic computational fluid dynamics (CFD) to assess the effects of pyrolysis-gas blowing into the boundary layer and computational solid mechanics to address modeling of mechanical erosion. Surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation are also being added.

Thermal Protection Systems↗

NASA NTRSDate not supplied

Updates on the Predictive Materials Modeling Software Tools

Updates on NASA‘s efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. The PMM effort is part of the Entry Systems Modeling (ESM) project under NASA’s Game Changing Development (GCD) program. To reduce the need for extensive testing and accelerate the design cycle process, ESM is developing simulation and modeling tools that enable the characterization of the properties of thermal protection materials and their response to extremely hot plasma. The Porous Microstructure Analysis (PuMA) software has been developed to compute effective material properties and perform material response simulations on digitized microstructures of porous media. PuMA is able to import three-dimensional digital images obtained from X-ray microtomography or to generate artificial microstructures that mimic real materials. PuMA also provides a module for interactive 3D visualizations. Version 3, which was recently released as open-source, includes modules to compute simple morphological properties such as porosity, volume fractions, pore diameter, and specific surface area. Additional capabilities include the determination of effective thermal and electrical conductivity (both radiative and solid conduction - including the ability to simulate local anisotropy for the latter); effective diffusivity and tortuosity from the continuum to the rarefied regime; techniques to determine the local material orientation, as well as mechanical properties (elasticity coefficients), and permeability. Computed properties are then used to inform a macro-scale material response model, such as those implemented in the Porous material Analysis Toolbox based on OpenFOAM (PATO) software developed within ESM. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale, assuming Local Thermal Equilibrium. Recent efforts include the development of a mechanical erosion model as well as a unified model allowing an intrinsic coupling between fluid and material. Comparison to flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI] and Mars 2020 MEDLI2) is critical in order to validate these computational tools. Examples of ablative material response using the code will be presented, including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrated the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains through the use of massively parallel computations.

material modeling↗

NASA NTRSDate not supplied

Derivation of Effective Properties Based on Porous Scale Simulations Using Filtering Techniques

This study presents a method for derivation of effective properties at the interface and in-depth of porous materials. The method defines a Representative Elementary Volume (REV) and applies filtering techniques to computer effective properties such as porosity and flow quantities, such as velocity and pressure. The script, developed to process the data was tested on the VTK type files that contain the mesh information and the flow solution. The method allows to choose between two types of filters, such as cellular and top-hat and define the size of the REV and number of samples along the domain. Extraction of the REV from the domain is performed to exact boundaries requested for the user. This is done using a triangulation technique and cutting through the cells to comply to the requested boundaries of the volume. The method can be applied to both structured and unstructured meshes. Filtering the material porosity and flow quantities involves integration of the numerical data. The algorithm provides three integration methods, such as Riemann sum, Monte Carlo and Quadrature rule to perform the integration. The Monte-Carlo technique permits the use of either uniform or linearly spaced distribution of points. The Quadrature rule is currently applicable to tetrahedral element types. The Monte Carlo and Quadrature rule methods require interpolation of the flow quantities at the sample points. For interpolation, two methods were tested and are readily available, Gaussian interpolation and re-sampling. It has been shown that re-sampling method has better consistency and acceptable accuracy in interpolation of the data. The algorithm was written in Python language and uses a number of modules. The major module besides numpy is PyVista. It is used to process the computational domain, clip the REV and interpolate the data. Quadrature rule integration was performed using a quadpy module. ParaView software was used externally to convert the flow solution to the VTK (or more specifically VTU) format. Integration of ParaView in the same environment with PyVista encountered problems and could not be implemented in this work. The developed algorithm is expected to be applicable to unstructured meshes and more complex porous structures as soon as the data can be passed in VTK type format. With the report is provided Python script for filtering the solution and a Matlab script for simple generation and processing of 2-D and 3-D porous channel geometries. The two scripts don't communicate.

Alexsander Zibitsker↗

NASA NTRSDate not supplied

Coupling CFD and Material Response for Analysis of Mars Entry

In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases [1]. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code [2], are used with a blowing boundary condition in the DPLR hypersonic CFD code [3]. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver [4], is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.

Heat Transfer↗