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NASA NTRS2022

MLtool Python Code

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine Learning↗

NASA NTRS2020

Integrated Modeling and Development of Component-Based Embedded Software in Scala

Programming of embedded systems is challenging due to the low-level design patterns normally applied in the implementation of such systems. Furthermore, programming languages normally considered suitable for this level of programming, such as C and C++, are themselves low-level compared to more modern programming languages. We report on an effort exploring modeling and programming of embedded systems in modern high-level programming languages combining object-oriented and functional programming. We present an integration of four separate internal DSLs (libraries), considered useful for embedded program- ming, in the Scala programming language, for programming and testing component-based systems. These include a DSL for defining components and their connections, and a DSL for programming the individual components as hierarchical state machines. Two additional DSLs support testing, and include a DSL for writing temporal logic flavored test oracles for monitoring program executions, and a DSL for rule-based test input generation. The paper discusses the gap between Scala as used here and the needs for embedded systems programming.

Bocchino, Robert↗

NASA NTRS2022

Test Facilities for SHERLOC Laser Development

The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) instrument is a deep UV laser based spectrometer that is part of NASA’s Mars Perseverance rover. The laser is a pulsed 248.6 nm NeCu hollow cathode gas discharge laser. The design, development, and testing of lasers and laser power supplies (LPS) were performed by scientists and engineers at the Jet Propulsion Laboratory (JPL) and Photon Systems Inc. (PSI). While these lasers had been used previously in extreme terrestrial environments, before they had to be qualified for operation and functionality over the expected range of environmental situations (temperature cycling, vibration, mechanical shock, low pressure corona emission testing) over the course of mission life time. The SHERLOC laser/LPS testing facilities consisted of custom-tailored environmental test chambers with metrology/control electronics. A custom LabVIEW software package was developed to autonomously operate all test facilities using a multi-threaded, object-oriented programming architecture, tasked with interfacing with many instruments simultaneously for operation and data acquisition.

Houck, Andrew↗

NASA NTRS2023

Python Based Plume Dynamics Estimation Tool (PyPDET) Rapid Plume Strike Analysis for RPOD Maneuvers in Deep Space Operations

I worked as a NASA Intern during the Summer 2023 term in the DS-00 division under the supervision of my mentor, Dr. Jonathan Pitt. Our goal was to build on our previous work from 2022 to develop a plume strike estimation tool using a prescribed physics methodology and model plume impingement effects while considering the dynamics of a rendezvous, operations, proximity, and docking (RPOD) maneuver. This tool supports previously configured CFD-DSMC calculations by allowing for rapid analysis of initial designs using a low-fidelity source flow model. Engineers can then use the high-fidelity CFD-DSMC tool to consolidate results as they work towards finalizing a design. This year’s project was focused on developing a software application that other engineers would be using in their analysis. Thus, the user’s experience was considered in the development of this application. Proper documentation, testability, and modularity of the codebase was our priority. For example, the project included auto documentation procedures to start building towards a User Manual, while also including dedicated demonstration cases for more explicit communication of functionality. Also, this project included a framework for testing the source code for future developments. Additionally, care was taken to develop the code using an Object-Oriented Programming approach. Thus, allowing for a modular extensibility of functionality in anticipation of future developments. The core work of this project was developing an algorithm that would transform the visiting vehicle and associated thruster data according to the kinematics described in the jet firing history. It would then calculate the estimated plume strikes on two of the target vehicles and write data accordingly into a VTK file. Summer work is to conclude by developing and presenting a PowerPoint slide deck at the intern exit briefing on August 11 th , 2023. Once the model for simple plume strike calculations is developed and tested there are several avenues to explore to continue development of this tool. These are also discussed in this report.

Plume Impingement↗

NASA NTRSDate not supplied

Graphical User Interface (GUI) Implementation for Agent-Based Microbial Radiobiology Model

Sending human life past the Low Earth Orbit (LEO) to explore the Moon and Mars will be challenging. The Earth’s magnetic field naturally protects life from deep-space particle radiation such as Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE); these will pose health risks to humans in deep space. Research has been done to investigate these effects, like BioSentinel, the first biological CubeSat to fly beyond the LEO, designed to culture yeast in a microfluidic device and record optical measurements of growth and metabolism. However, experiments can only report cell damage as bulk growth curves, while deep-space radiation causes damage that is heterogeneous among individual cells. AMMPER is an open-source, agent-based, computational model coded in Python to simulate the effects of deep-space radiation on individual yeast cells (Saccharomyces cerevisiae) to facilitate interpretation of biological radiation experiments. Version 1.0 of the code ran in a command line interface (CLI), limiting use to those familiar with modularization, object-oriented programming, and computational models. Here we present a graphical user interface (GUI) for AMMPER to increase its accessibility. GUI development included converting input points and UI files, designing an application and logo, and expanding program packages. Additionally, we added optical assistance that corresponded with simulation parameters, which included simulation type, cell type, ROS model, and radiation dosage, as well as customizable display and file exportation features. Following a pilot testing period, its structure was updated further to enhance abilities, adding increased runs, video visualization, data plotting, and an educational/tutorial component. Future work will include creating a bit installer and runtime environment for AMMPER. Ultimately, the creation of the GUI has two main goals: to facilitate the integration of computational models into the work of researchers in microbial radiobiology, and to act as an interactive and visual resource for space biology education.

yeast↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

NASA NTRS2026

Updates and Modernization of NASA’s Chemical Equilibrium with Applications (CEA) Code

NASA’s Chemical Equilibrium with Applications (CEA) code is a foundational tool for propulsion system analysis. It provides equilibrium chemistry, rocket performance, shock, and detonation calculations used across NASA and the broader aerospace community. NASA Engineering and Safety Center (NESC) Activity TI-22-01730 modernized the legacy CEA2 Fortran code into CEA v3, a Fortran 2008, object-oriented software package with expanded interface support, updated thermochemical data, improved maintainability, and substantially improved workflow integration. The modernized code preserves backward compatibility with legacy CEA input workflows while enabling direct use from modern analysis environments, including Python, C, MATLAB, and automated design studies.

Mark K Leader↗

NASA NTRS2026

Updates and Modernization of the Chemical Equilibrium with Applications (CEA) Code

Combustion↗

DOE OSTI2018

Elk: A New MOOSE Framework Application for Radio-frequency Electromagnetics

A new tool in-development for general electromagnetic (EM) simulation for modeling radio-frequency (rf) systems is presented. The primary motivation for development of this tool is to leverage the flexibility and high-performance-computing capability of the Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework developed by Idaho National Laboratory (INL) for complex EM problems. A MOOSE application (or MOOSE App) enables the end user to create a fully-functional simulation scenario without needing explicit knowledge of the underlying finite-element weak form implementation. MOOSE combines the libMesh library and the PetSc suite as the finite element and solver libraries, giving a robust platform for solving highly non-linear, coupled sets of PDEs such as those found in EM and plasma physics problems. Initial validation efforts have included standard waveguide and antenna benchmarks with the current focus being field validation against the well-known capacitively-coupled GEC Reference Cell (GEC-CCP). The results of this effort will be outlined and discussed. Future work plans including cold-plasma rf wave propagation studies and coupling to the plasma fluid MOOSE App, Zapdos [Lindsay et al 2016 J. Phys. D: Appl. Phys. 49 235204], will also be discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

FEAA90: Physics-based Creep Simulation of Thick Section Welds in High Temperature and Pressure Applications

Welded microstructures of ?’-strengthened, nickel-based alloy, 740H, contain significant microstructural heterogeneities that can have a strong influence on the dislocation dynamics, resulting in very different creep behavior compared to the base metal. Crystal plasticity-based finite element method (CPFEM) has been widely used to incorporate the effect of microstructural heterogeneities on deformation at the polycrystalline scale and is being utilized in this work to model the creep behavior of 740H GTA welds. Current model development is focused on secondary creep considering dislocation climb, glide, and, anti-phase boundary shearing or Orowan looping. A dislocation-density based CPFEM model addressing these mechanisms is currently being implemented in the Multi-Physics Object Oriented Simulation Environment (MOOSE: mooseframework.org) software that provides the ability to solve problems involving multiple physics concurrently and implicitly. Short term creep tests at 700-800°C of cross weld and all-weld metal samples from GTA welds in Alloy 740 will be used to determine input parameters for the model. Long term creep tests at 750°C on Alloy 740H GTA welds will be used to validate the results of modeling and simulation. The model will also be applied to welds with microstructures that develop during hybrid laser arc welding (HLAW) of Alloy 740H to evaluate the effect of weld microstructure on of the validity of the model.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

Validation Studies using ELK and the Open-Source MOOSE Framework Application Zapdos for Electromagnetic Coupled Plasma Simulation

An open source simulation platform that captures electromagnetics, plasma chemistry, and fluid treatment of the plasma domain would be a powerful tool for studying low temperature plasma (LTP) phenomena. Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) open source framework, ELK, CRANE, and Zapdos are combined to provide open source simulation capability for the LTP community. This talk presents continued validation of the general electromagnetic (EM) simulation tool ELK (Electromagnetic Library for Kinetics & fluids). Previous validation efforts focused on simulating standard waveguide and antenna benchmarks in vacuum and linear dielectrics, but ELK has since been coupled with the MOOSE-based plasma fluid application Zapdos [Lindsay et al 2016 J. Phys. D: Appl. Phys. 49 235204] to perform radio-frequency (rf) capacitively coupled plasma (CCP) system simulation. Plasma validation efforts initially focused on electrostatic benchmarks to demonstrate ELK-Zapdos code coupling and then moved to electromagnetic benchmarks based on interesting geometries and conditions (VHF effects in a CCP reactor, microwave heating, etc.). Results and progress in these efforts will be summarized and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Coupling of Pronghorn and RELAP-7 for a Pebble Bed Reactor

High temperature gas cooled reactors (HTGR) are a candidate for timely Gen-IV reactor technology deployment because of high technology readiness and walk-away safety. Among HTGRs, pebble bed reactors (PBRs) have attractive features such as low excess reactivity and online refueling. Pebble bed reactors pose unique challenges to analysts and reactor designers such as continuous burnup distribution depending on pebble motion and recirculation, radiative heat transfer across a variety of gas-filled gaps, and long design basis transients such as pressurized and depressurized loss of forced circulation. Modeling and simulation is essential for both the PBR’s safety case and design process. In order to verify and validate the new generation codes the Nuclear Energy Agency (NEA) Data bank provide a set of benchmarks data together with solutions calculated by the participants using the state of the art codes of that time. An important milestone to test the new PBR simulation codes is the OECD NEA PBMR-400 benchmark which includes thermal hydraulic and neutron kinetic standalone exercises as well as coupled exercises and transients scenarios. In this work, the reactor multiphysics code MAMMOTH and the thermal hydraulics code Pronghorn, both developed by the Idaho National Laboratory (INL) within the multiphysics object-oriented simulation environment (MOOSE), have been used to solve Phase 1 exercises 1 and 2 of the PBMR-400 benchmark. The steady state results are in agreement with the other participants’ solutions demonstrating the adequacy of MAMMOTH and Pronghorn for simulating PBRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Multiphysics coupling plan

In this chapter, multiphysics coupling simulations of nuclear reactor systems are reviewed. On the one hand, the mainstream methods of multiphysics coupling are demonstrated. The fundamental theory and coupling scheme of operator splitting methods, Jacobian-free Newton–Krylov methods, and approximate block Newton methods are summarized and presented. On the other hand, some significant works on neutronic and thermal-hydraulic codes coupling, and large research project, including NURESAFE European project, Multiphysics Object-Oriented Simulation Environment plan, and Consortium for the Advanced Simulation of Light Water Reactors project, are reviewed. This chapter helps the readers have a better understanding on the worldwide current status of multiphysics coupling research.

Gui, Miao↗

DOE OSTI2021

Coupled Microbial-Conversion and Computational-Fluid-Dynamics (CFD) Models for Butanediol Production in Micro-Aerated Reactors

Microbial conversion of substrates to macromolecules has been widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries. These bioreactions are also being investigated in the production of low-value commodities such as biofuels [1]. Gas-liquid mass-transfer and transport-reaction coupling are important challenges when designing and scaling up these reactor systems. Experiments in wellmixed small-scale reactors have enabled characterization of microbial reactivity, while their coupling with macroscale transport remains relatively unexplored. In this work, we use a coupled metabolic-CFD model to study the action of a genetically engineered microbe Zymomonas mobilis [2] on sugars to produce 2,3-Butanediol (BDO). BDO is an important hydrocarbon intermediate that can be catalytically upgraded to several fuels and chemicals [3]. An important aspect to this particular microbial conversion is the need for micro-aerated environments as opposed to traditional aerobic fermentation. Slight variations in oxygen concentration can result in competing reaction pathways that disable BDO production. Hence, gas-liquid mass transfer and transport need to be optimized in large-scale reactors to maximize BDO production, for which CFD is a valuable tool. The aerobic-fermentation CFD model previously developed by the authors [5] for simulating bubble-column and airlift reactors at scale was used in this study. The Reynolds-averaged mass, momentum and energy transport equations for interpenetrating gas and liquid phase are solved in this model along with the transport and interphase mass transfer of oxygen. Our previous work used a phenomenological model for microbial oxygen uptake that neglected microbial growth and other reaction pathways. In this work, a detailed metabolic model enabled prediction of product formation and inhibition pathways. In order to manage computational cost, we used a subcycling technique [6] that takes advantage of the clear separation in transport (~ 200 sec) and reaction (~ 2-3 hours) timescales. The CFD model is first solved to steady state, after which the metabolic model is advanced at every cell in the computational domain using the local oxygen concentration. The CFD model is then run to achieve a new steady state that provides a new oxygen distribution for the metabolic model. This process, where reaction and fluid updates are interleaved together, is iterated until reactants are completely exhausted. This work will examine the performance of different reactor designs such as bubble column and airlift reactors at scale (250-500 m3). Oxygen mass-transfer coefficient and distribution are critically analyzed among reactors, and optimization studies pertaining to aeration is presented. Furthermore, it has been observed in experiments that high BDO production may be achieved by manipulating the aerobic environment over the course of reaction, such that oxygen concentration is high during the growth phase, and very low as sugar is depleted. This characteristic will be addressed by our simulations for which a timedependent scheduling strategy for aeration is presented that maximizes BDO production. [1] Humbird, D., Davis, R., and McMillan, J., Aeration costs in stirred-tank and bubble column bioreactors, Biochemical Engineering Journal, 127, 161—166, 2017 [2] Yang, S., Mohagheghi, A., Franden, M. A., Chou, Y.-C., Chen, X., Dowe, N., Himmel, M. E., and Zhang, M., Metabolic engineering of zymomonas mobilis for 2, 3-butanediol production from lignocellulosic biomass sugars. Biotechnology for biofuels, 9(1):189, 2016 [3] Kim, S. J., Sim, H. J., Kim, J. W., Lee, Y. G., Park, Y. C., and Seo, J. H., Enhanced production of 2,3-butanediol from xylose by combinatorial engineering of xylose metabolic pathway and cofactor regeneration in pyruvate decarboxylase-deficient Saccharomyces cerevisiae. Bioresource Technology, 245:1551–1557, 2017 [4] Weller, H., Tabor, G., Jasak, H. and Fureby, C., A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in physics, 12, 6, 620--631, 1998

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Initial Developments in Modeling Graphite Behavior

Graphite is used in High Temperature Reactor designs as a moderator, reflector and core material responsible for protecting the fuel and maintaining structural stability. From a safety perspective, it is imperative to be able to predict how graphite will behave under reactor operating conditions which may compromise the core’s structural integrity or fuel’s safety performance. The following report summarizes recent modeling work undertaken at Idaho National Laboratory which focuses on graphite degradation behavior. One phenomenon which is explored in this report and can cause significant degradation to graphite properties is oxidation. Oxidation behavior in graphite is highly temperature dependent. At low temperatures, oxygen can fully penetrate a component and cause a homogeneous damage profile. At high temperatures, only the graphite near the surface of a component is affected. Understanding and modeling this temperature dependence is essential to predicting graphite behavior. In this report, three graphite models are discussed. The first model is used to investigate strength loss after low temperature oxidation. It does this by generating an approximate graphite microstructure then determining the required load to cause crack propagation. It has been shown that the model reproduces the quasi brittle stress versus strain relationship observed in graphite. Strength loss results from the model are shown to match experimental values. The second model investigates strength loss under high temperature oxidation conditions. This model is more applicable to full scale graphite components where the oxidation damage is often inhomogeneous throughout a component. The third model computes stresses in graphite under reactor conditions. Specifically, the model incorporates the effect of creep, irradiation dose, thermal strains, and oxidation in order to predict internal stresses in a component. All of these models are implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open source, parallel finite element framework.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Summary of Work on a Software Adapter for Project Requirements and MBSE

The National Reactor Innovation Center (NRIC) has funded the development of a digital pipeline to pull a project’s requirements from IBM’s Rational Dynamic Object Oriented Requirements System (DOORS), save them to Deep Lynx, then push them into the corresponding project in Innoslate. These utilities are accessible from a web browser and allow a project’s functional and business requirements to be tied to its tree of model-based systems engineering (MBSE) data.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Demonstration of Bison/TRACE Coupling (CRAB) Through Validation Case LOFT L2-5

The postulated pressurized water reactor (PWR) accident known as a large-break loss of coolant accident (LOCA) is still of great concern to the current nuclear reactor fleet. Research through experiments, modeling, and simulation is active in the field of LOCAs and new modeling tools are under continuous development. The BISON fuel performance code, developed at the Idaho National Laboratory (INL), is one such tool that has been very active in the development of models and the simulation of accidents. With recent model developments, Bison has been used to simulate LOCA cladding burst experiments and full integral LOCA experiments with favorable results. Bison is a thermomechanical code that must be fed boundary conditions (BC) for phenomena occurring outside of the fuel rod. These BCs include moderator or outer cladding temperature, coolant pressure, and rod linear power or neutron flux. These BCs can be supplied from a function or, preferably, another coupled code. Bison is built on the Multiphysics Object Oriented Simulation Environment (MOOSE) framework which allows for ease of code coupling. A framework is currently in place that allows codes external to MOOSE to communicate with MOOSE applications as if they were a MOOSE application. Through a recent MOOSE/BISON development, with collaboration from the U.S. Nuclear Regulatory Commission (NRC), BISON has been coupled with the NRC system code TRAC/RELAP Advanced Computational Engine (TRACE). Simulation results of the initial validation loss of flow test (LOFT) L2-5 case from this research will be presented.

42 ENGINEERING↗