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DOE OSTI2017

University of Wisconsin Nuclear Reactor Modeling Improvements

The University of Wisconsin Nuclear Reactor converted from HEU to LEU fuel in 2009. As part of the conversion process, an MCNP model was developed to predict flux distributions and depletion in the core. This core model included an unforeseen excess reactivity bias, resulting in an overestimate of core reactivity, and requiring the core configuration to be shuffled in 2011. The original model was constructed by hand and in order to account for radial and axial burnup in the fuel, and to include sufficient detail in the geometric features, the input file was over 17,000 lines long. Given the challenges in assessing the quality of such a long and complicated MCNP model, this project was designed to build an MCNP model based on a minimal set of input quantities in a modular and repeatable fashion. A Python code was implemented to write the MCNP input file from fundamental reactor data, both geometric and material. The recent conversion to LEU fuel provides a unique opportunity to characterize fuel composition quite accurately in the core. The goal of this project is to produce an accurate, maintainable model that can be used with future reactor physics experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2009

OLTARIS: On-Line Tool for the Assessment of Radiation in Space

The effects of ionizing radiation on humans in space is a major technical challenge for exploration to the moon and beyond. The radiation shielding team at NASA Langley Research Center has been working for over 30 years to develop techniques that can efficiently assist the engineer throughout the entire design process. OLTARIS: On-Line Tool for the Assessment of Radiation in Space is a new NASA website (http://oltaris.larc.nasa.gov) that allows engineers and physicists to access a variety of tools and models to study the effects of ionizing space radiation on humans and shielding materials. The site is intended to be an analysis and design tool for those working radiation issues for current and future manned missions, as well as a research tool for developing advanced material and shielding concepts. The site, along with the analysis tools and models within, have been developed using strict software practices to ensure reliable and reproducible results in a production environment. They have also been developed as a modular system so that models and algorithms can be easily added or updated.

Sandridge, Chris A.↗

NASA NTRSDate not supplied

Lunar Water Extraction Via Lunar Auger Dryer ISRU (LADI)

In 2009, the Lunar Reconnaissance Orbiter (LRO) and Lunar Crater Observation and Sensing Satellite (LCROSS) provided definitive proof of water in the Lunar’s southern permanently shadowed region (PSR)1. Both the 2020 NASA Technology Taxonomy2 and the Lunar Surface Innovation Initiative (LSII) team identified capability gaps in icy regolith transfer and reactor processing in Permanently Shadowed Region (PSR) environmental conditions. A water processing plant operating inside the PSR can continuously process water (and volatiles) for both breathable air and propellant. NASA’s Johnson Space Center (JSC) fabricated a unique breadboard test stand for validating the feasibility of this concept,developed a lunar auger dryer sizing tool, and identified the physical flow and thermal models required to design an Engineering Development Unit (EDU) for environmental testing. Over the two years this project was active, models were developed including: a) a sizing tool that scales the auger parameters based on production targets, b) accurate thermal models in both lab and lunar conditions, c) a Discreet Element Model (DEM) for observing particle effects in low-g, and d) incorporated these subsystem models into a MATLAB parametric Modular Open System Approach (MOSA) system model. These models were validated by testing the auger in both a mechanical and thermal system configuration. The results of this testing increased the Technology Readiness Level (TRL) of the Lunar Auger Dryer ISRU (LADI) system to TRL 4.

Lunar↗

DOE OSTI2022

Towards a Benchmark Experiment with the Compact Nuclear Power Source

The Compact Nuclear Power Source (CNPS) was a high-assay low enriched uranium (HALEU) tristructural isotropic (TRISO)-fueled, graphite-moderated microreactor constructed in 1987 at Los Alamos National Laboratory. The reactor, conceived as a power source for short-range radar stations, was designed to be "walk-away safe," and was cooled by heat pipes and ambient air. Though the project was formally cancelled after the fuel and moderator material had been received, its potential to meaningfully advance the body of critical and integral data was evident, and critical experiments with a mock-up of the reactor proceeded at TA-18 until its disassembly in 1991. The reflector and some components of the core would later go on to see service as part of the New Production Reactor Modular High-Temperature Gas-Cooled Reactor (NP-MHTGR) critical experiments. In light of the progress made by groups like Westinghouse and X-Energy towards contemporary graphite-moderated microreactors, the system remains an attractive candidate for the basis of a benchmark experiment even today. Uncertainties remain, however, in some features of the system–inconsistencies in the dimensions and composition of the reactor’s components as described in literature and implemented in current computational models. The identification, quantification, and to the extent possible, the minimization of these uncertainties is a crucial task on the path towards creating a benchmark based on the CNPS system. The present work seeks to initiate this process with a survey of available documentation and improvements to the accuracy of CNPS neutronics models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Pebble Tanker Model for Nuclear Criticality Safety Needs

This report documents a study performed to investigate the requirements for criticality safety benchmark experiments for high-assay, low-enriched uranium (HALEU) fuel in transportation applications. In this work, an exploratory application model, the “Pebble Tanker,” was developed to represent TRISO fuel in a transportation scenario for an analysis of the validation basis in industrial quantities. An aspect of the criticality validation process involves assessing the “similarity” between application and experimental benchmark systems through an integral index parameter evaluation. Here, this includes propagating nuclear data uncertainties and calculating a correlation coefficient (hereinafter referred to as “c k ”) to evaluate the similarity of benchmark experiments compared with the application Pebble Tanker model. Finding sufficient critical benchmark experiments allows for the evaluation of bias and bias uncertainty, thus determining the upper subcritical limit (USL) of the transportation package. A target k eff of ~0.94 was used in this work to establish appropriate modeling conditions, reflecting a reasonable estimate for a USL. Two container models were investigated: one with the Hermes-type pebble and one with the Pebble Bed Modular Reactor (PBMR)–type pebble. The models were simplified, considering only fuel, containment structure, and either water or air. This allows a focus on the underlying physics of applications involving TRISO fuel pebbles using the Pebble Tanker model. A crucial consideration is the transport package's ability to safely hold pebbles while flooded, maintaining subcritical conditions. Tools available in the SCALE 6.3.1 suite—the CSAS6-Shift, TSUNAMI-3D-Shift, and TSUNAMI-IP sequences—were employed for neutronics and sensitivity and uncertainty (S/U) analysis of the Pebble Tanker. Findings demonstrated sufficient available critical experiment benchmarks to perform a validation of the Pebble Tanker in the most reactive state, i.e., when the Tanker is flooded.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

A tungsten external heater for BX90 diamond anvil cells with a range up to 1700 K

Resistive heating of a sample in a diamond anvil cell (DAC) can generate a homogeneous temperature field across the sample chamber with reliable temperatures measured by a thermocouple. It is of importance in experiments aiming at exploring phase diagrams and quantifying thermoelastic properties of materials. Here, we present a ring-heater design developed for BX90 diamond anvil cells (DACs). Furthermore, it is made of a ring-shaped aluminum oxide holder hosting a tungsten wire coil inside and coupled with Ar + 2% H 2 gas to prevent oxidation during experiment. This modular plug-and-play design enables in situ studies of samples via x-ray diffraction up to a temperature of 1700 K. Temperature in the BX90 sample volume as measured through a thermocouple was calibrated using the melting point of gold. As an application of this design, we report the thermal expansion coefficient of MgO at 9.5(1) GPa.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Compact Cloud Condensation Nucleus Counter for Unmanned Aerial Systems (UAS) and Long-Term Monitoring Applications (Final Report)

Brechtel Manufacturing Incorporated (BMI) is developing a compact, modular suite of new aerosol measurement technologies optimized for use on Unmanned Aerial Vehicles (UAVs) and other applications where space, weight, power and cost are significant barriers to deployment. The project is focused on a cloud condensation nucleus counter that exposes sampled particles to a simulated cloud environment and counts how many of the particles grow to micron-sized droplets. The new development helps address the need for reduced uncertainties in climate model sensitivities to ambient aerosol properties by promoting the capability to perform aerosol measurements more often, in more locations, and at reduced cost. Applications of the new technology include long-term measurements of the aerosol effects on cloud radiation, microphysical and precipitation processes, weather prediction and modelling studies, and weather modification studies.

47 OTHER INSTRUMENTATION↗

NASA NTRS1995

Geophysical phenomena classification by artificial neural networks

Space science information systems involve accessing vast data bases. There is a need for an automatic process by which properties of the whole data set can be assimilated and presented to the user. Where data are in the form of spectrograms, phenomena can be detected by pattern recognition techniques. Presented are the first results obtained by applying unsupervised Artificial Neural Networks (ANN's) to the classification of magnetospheric wave spectra. The networks used here were a simple unsupervised Hamming network run on a PC and a more sophisticated CALM network run on a Sparc workstation. The ANN's were compared in their geophysical data recognition performance. CALM networks offer such qualities as fast learning, superiority in generalizing, the ability to continuously adapt to changes in the pattern set, and the possibility to modularize the network to allow the inter-relation between phenomena and data sets. This work is the first step toward an information system interface being developed at Sussex, the Whole Information System Expert (WISE). Phenomena in the data are automatically identified and provided to the user in the form of a data occurrence morphology, the Whole Information System Data Occurrence Morphology (WISDOM), along with relationships to other parameters and phenomena.

Gough, M. P.↗

NASA NTRS2015

The Rapid Response Radiation Survey (R3S) Mission Using the HiSat Conformal Satellite Architecture

The Rapid Response Radiation Survey (R3S) experiment, designed as a quick turnaround mission to make radiation measurements in Low Earth Orbit (LEO), will fly as a hosted payload in partnership with NovaWurks using their Hyper-integrated Satlet (HISat) architecture. The need for the mission arises as the Nowcast of Atmospheric Ionization Radiation for Aviation Safety (NAIRAS) model moves from a research effort into an operational radiation assessment tool. Currently, airline professionals are the second largest demographic of radiation workers and to date their radiation exposure is undocumented in the USA. The NAIRAS model seeks to fill this information gap. The data collected by R3S, in addition to the complementary data from a NASA Langley Research Center (LaRC) atmospheric balloon mission entitled Radiation Dosimetry Experiment (RaD-X), will validate exposure prediction capabilities of NAIRAS. The R3S mission collects total dose and radiation spectrum measurements using a Teledyne μDosimeter and a Liulin-6SA2 LED spectrometer. These two radiation sensors provide a cross correlated radiometric measurement in combination with the Honeywell HMR2300 Smart Digital Magnetometer. The magnetometer assesses the Earth's magnetic field in the LEO environment and allows radiation dose to be mapped as a function of the Earth's magnetic shielding. R3S is also unique in that the radiation sensors will be exposed on the outer surface of the spacecraft, possibly making this the first measurements of the LEO radiation environment with bare sensors. Viability of R3S as an extremely fast turnaround mission is due, in part, to the nature of the robust, well-defined interfaces of the conformal satellite HiSat Architecture. The HiSat architecture, which was developed with the support of the Defense Advanced Research Projects Agency's (DARPA's) Phoenix Program, enabled the R3S system to advance from the first concept to delivery of preliminary design review (PDR) level documents in 29 calendar days. The architecture allows for interface complexities between the specific devices and the satellite bus to be resolved in a standardized interface control document (ICD). The ICD provided a readymade framework to interface to the modular satellite bus. This modularity allowed for approximately 90% of the R3S system to be designed and fabricated in two months without constraint of the hosting satellite's development cycle. This paper discusses the development of the R3S experiment as made possible by use of the HiSat architecture. The system design and operational modes of the experiment are described, as well as the experiment interfaces to the HiSat satellite via the user defined adapter (UDA) provided by NovaWurks. This paper outlines the steps taken by the project to execute the R3S mission in the 4 months of design, build, and test. Additionally portrayed is the ground work done at LaRC to posture the organization for a fast response and the process by which the opportunity was identified as aligning with key strategic goals. Finally, a description of the engineering process is provided, including the use of facilitated rapid/concurrent engineering sessions, the associated documentation, and the review process employed.

Miller, Nathanael A.↗

DOE OSTI2025

Should I stay or should I flow? An exploration of phase‐separated metallosupramolecular liquid crystal polymers

Abstract Dynamic liquid crystalline polymers (dLCPs) incorporate both liquid crystalline mesogens and dynamic bonds into a single polymeric material. These dual functionalities impart order‐dependent thermo‐responsive mechano‐optical properties and enhanced reprocessability/programmability enabling their use as soft actuators, adaptive adhesives, and damping materials. While many previous works studying dynamic LCPs utilize dynamic covalent bonds, metallosupramolecular bonds provide a modular platform where a series of materials can be accessed from a single polymeric feedstock through the variation of the metal ion used. A series of dLCPs were prepared by the addition of metal salts to a telechelic 2,6‐bisbenzimidazolylpyridine (Bip) ligand endcapped LCP to form metallosupramolecular liquid crystal polymers (MSLCPs). The resulting MSLCPs were found to phase separate into hard and soft phases which aids in their mechanical robustness. Variations of the metal salts used to access these materials allowed for control of the thermomechanical, viscoelastic, and adhesive properties with relaxations that can be tailored independently of the mesogenic transition. This work demonstrates that by accessing phase separation through the incorporation of metallosupramolecular moieties, highly processable yet robust MSLCP materials can be realized. This class of materials opens the door to LCPs with bulk flow behavior that can also be utilized as multi‐level adhesives.

Chemistry↗

DOE OSTI2022

Event driven readout architecture with non-priority arbitration for radiation detectors

A novel event driven readout architecture, EDWARD (Event Driven with Access and 8 Reset Decoder) architecture, for highly granular pixel detectors is presented. It incorporates, inter alia, an asynchronous arbitration tree based on Seitz' arbiters, removing the need for an imposed prioritization scheme. It also provides protection against glitches during readout. The system allows not only reading pixel activities, but also retrieving additional data, both analog and digital, from the pixels. A novel in-channel logic allows the entire readout process to be split into consecutive phases for additional flexibility. All operations are controlled by only one edge of the clock signal, seen as an acknowledge token, so there is no dead time between readouts.

47 OTHER INSTRUMENTATION↗

NASA NTRS1973

Shuttle active thermal control system development testing. Volume 7: Improved radiator coating adhesive tests

Silver/Teflon thermal control coatings have been tested on a modular radiator system projected for use on the space shuttle. Seven candidate adhesives have been evaluated in a thermal vacuum test on radiator panels similar to the anticipated flight hardware configuration. Several classes of adhesives based on polyester, silicone, and urethane resin systems were tested. These included contact adhesives, heat cured adhesives, heat and pressure cured adhesives, pressure sensitive adhesives, and two part paint on or spray on adhesives. The coatings attached with four of the adhesives, two silicones and two urethanes, had no changes develop during the thermal vacuum test. The two silicone adhesives, both of which were applied to the silver/Teflon as transfer laminates to form a tape, offered the most promise based on application process and thermal performance. Each of the successful silicone adhesives required a heat and pressure cure to adhere during the cryogenic temperature excursion of the thermal-vacuum test.

Reed, M. W.↗

NASA NTRS1987

Spacecraft technology trends - A view from the past

Future spacecraft will be sent on missions to complete the exploration of the solar system, to return samples from celestial bodies, record the process of creation of stars, galaxies, and the universe itself, to provide a continuous record of earth processes, and to maintain vital space communications. A key ingredient to projecting the future is to comprehend the historic record and to understand the significance of trends. This paper focuses on spacecraft cost and life trends, as well as those of the major subsystems. Throughout the history of the 'space age' there has been significant progress in the performance of spacecraft and their subsystems. However, various aspects of spacecraft performance lag behind what is technically feasible by a considerable margin. In addition, examination of the historical trend implies that future spacecraft will likely continue to be relatively unique in their design features. This is in contrast to the technically realizable future attributes such as large space platforms, modularity, system autonomy and on-orbit repair and servicing.

Hudson, Wayne R.↗

NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗

DOE OSTI2019

Current Status of SAMMY [Slides]

SAMMY is used to analyze experimental data mainly in the resolved range to generate evaluated data files for use in transport codes. The code base in SAMMY is still mostly F77, i.e., fixed line length and almost no use of modules. SAMMY is used in production environments, so during the modernization its functionality cannot be lost. That means we cannot simply rewrite it from scratch. Modernization is needed to allow us to add new features (for example new and improved algorithms in the resolved range). SAMMY has a large suite of regression tests that can be run and whose outputs can be checked automatically. During the modernization process, we will not change the results of these regression tests, except if errors in the original coding are found and corrected. Future plans for SAMMY include converting all container array access to Fortran allocate (or use C++ storage) and finishing the conversion to use C++ storage for all resonance parameters. We have an initial C++ implementation of the cross section reconstruction from R-Matrix parameters, used in AMPX. We will update this code, add reconstruction of angular data and derivatives and will use it in AMPX and SAMMY. Once this is done, we can start to add new features to the R-Matrix algorithm, like complex channel radii or relativistic effects. We also intend to modularize SAMMY to separate cross section reconstruction, experimental effect etc. from the Bayes fitting routines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling

We report that carbon fiber reinforced plastics (CFRPs) are attracting growing attention in industry because of their enhanced properties. Preforming of thermoset carbon fiber prepregs is one of the most common production techniques of CFRPs. To simulate preforming, several computational methods have been developed. Most of these methods, however, obtain the material properties directly from experiments such as uniaxial tension and bias-extension where the coupling effect between tension and shear is not considered. Neglecting this coupling effect deteriorates the prediction accuracy of simulations. To address this issue, we develop a Bayesian model calibration and material characterization approach in a multiscale finite element preforming simulation framework that utilizes mesoscopic representative volume element (RVE) to account for the tension-shear coupling. A new geometric modeling technique is first proposed to generate the RVE corresponding to the close-packed uncured prepreg. This RVE model is then calibrated with a modular Bayesian approach to estimate the yarn properties, test its potential biases against the experiments, and fit a stress emulator. Finally, the predictive capability of this multiscale approach is further demonstrated by employing the stress emulator in the macroscale preforming simulation which shows that this approach can provide accurate predictions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Two-loop master integrals for leading-color $$ pp\to t\overline{t}H $$ amplitudes with a light-quark loop

Abstract We compute the two-loop master integrals for leading-color QCD scattering amplitudes including a closed light-quark loop in$$ t\overline{t}H $$ t t ¯ H production at hadron colliders. Exploiting numerical evaluations in modular arithmetic, we construct a basis of master integrals satisfying a system of differential equations inϵ-factorized form. We present the analytic form of the differential equations in terms of a minimal set of differential one-forms. We explore properties of the function space of analytic solutions to the differential equations in terms of iterative integrals which can be exploited for studying the analytic form of related scattering amplitudes. Finally, we solve the differential equations using generalized series expansions to numerically evaluate the master integrals in physical phase space. As the first computation of a set of two-loop seven-scale master integrals, our results provide valuable input for analytic studies of scattering amplitudes in processes involving massive particles and a large number of kinematic scales.

Physics↗