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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part I: Flux and Eigenvalue Solutions

Computing in the energy dimension is one of the greatest challenges confronting present-day deterministic neutron transport solvers. Accurately resolving the neutron flux as neutrons downscatter across resonances in the nuclear cross sections currently requires considerable computing power and suffers from approximation errors. Flux uncertainty resulting from the uncertainty of the resonance structure is the single-largest cause of reactivity uncertainty. Any additional reference solution for the critical neutron downscattering problem with resonance phenomena would be a boon to verification and validation of neutronics codes. This paper establishes a benchmark to verify the accuracy of neutron transport criticality solvers along the energy dimension. For the first time, the analytic solution of the flux amplitude is derived in the particular case of an infinite homogeneous medium with isotropic scattering in the center of mass and an arbitrary number of no-threshold, neutral particle reaction resonances (e.g., radiative capture, fission, and resonance scattering). Furthermore, original analytic expressions are established to quantify the discrepancy between the ψ k (E) and ψ α (E) flux amplitudes, respective solutions of the multiplication factor k, or the exponential time-evolution frequency α eigenproblems. The physical study of these relations led to analysis of their first-order relative difference near the criticality condition α=0. Finally, numerical solutions are provided to a benchmark problem constituted of the first resonance of 239 Pu, the 6.67-eV resonance of 238 U, and a scattering isotope with a flat cross section, allowing for the computational verification of the energy resolution of current neutron transport criticality codes. Through these novel results, this analytic benchmark can serve as a reference to verify the energy resolution and sensitivity analysis of neutron transport criticality calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2021

Verifying Mars 2020 Sampling and Caching Robotic Functions with Position Budgeting Process and Tool

The Mars 2020 Perseverance Rover was launched on July 30th, 2020 with one of the most complex robotic systems ever implemented on an interplanetary mission. Much of this robotic complexity resides in the Rover Sampling and Caching Subsystem (SCS) to enable collection of Martian samples for eventual return to earth and preparation of surfaces for close-up surface science observations. Two robotic arms are used by SCS: the large Robotic Arm (RA) positions the coring drill and science instruments mounted to the Turret for surface interactions, and the smaller Sample Handling Assembly (SHA) manipulates Sample Tube Assemblies (STA) within the Adaptive Caching Assembly (ACA) to prepare them for sample collection, processing, and hermetic sealing. The robotic arms interact with the Martian surface and other SCS components in many ways and in a variety of configurations, with positioning accuracy requirements ranging from tens of millimeters for some surface interactions down to sub-millimeter accuracy for some ACA interactions.This paper describes the process and tool used to calculate the SCS robotic interaction positioning budgets and verify the as-built hardware when delivered. To ensure that these robotic systems are able to perform their tasks, each robotic interaction with another element was broken down into its composite functions. To calculate a positioning budget margin for each function, an allowable was defined and then compared to the list of error sources that contribute to misalignment. Across the subsystem, over 250 functions were identified to be assessed, with almost 500 error sources feeding into their budget calculations. In addition to using as-built values in the budgets for SCS Verification and Validation (V&V) after the hardware was complete, these budgets were populated with design data during the design phase to identify areas of concern and guide hardware design to ensure positive position budget margins.Because of the size of the SCS team that had inputs to the positioning budgets and the sheer number of items in the budgets that needed to be created, updated, and verified, having a tool that would allow for simultaneous access and robust data integrity and processing was imperative. To accomplish this, a web-based MySQL database was created that allowed users to create function position budgets, link individual errors and allowables to them, and view function position budget margin reports. Each error and allowable records data for lateral, normal, angular, and clocking errors, with the ability to add as-built data for up to four different hardware builds. Margin reports can be generated for either design values alone or replacing design data with as-built data when available. These as-built reports are used for final verification of the SCS positioning requirements. Ultimately, the SCS positioning budget process and database tool led to successful interactions during test and an SCS robotic system that is ready to perform sample acquisition and caching on the surface of Mars.

Williams, Jeffrey↗
NASA NTRS1989

Initial Ada components evaluation

The SAIC has the responsibility for independent test and validation of the SSE. They have been using a mathematical functions library package implemented in Ada to test the SSE IV and V process. The library package consists of elementary mathematical functions and is both machine and accuracy independent. The SSE Ada components evaluation includes code complexity metrics based on Halstead's software science metrics and McCabe's measure of cyclomatic complexity. Halstead's metrics are based on the number of operators and operands on a logical unit of code and are compiled from the number of distinct operators, distinct operands, and total number of occurrences of operators and operands. These metrics give an indication of the physical size of a program in terms of operators and operands and are used diagnostically to point to potential problems. McCabe's Cyclomatic Complexity Metrics (CCM) are compiled from flow charts transformed to equivalent directed graphs. The CCM is a measure of the total number of linearly independent paths through the code's control structure. These metrics were computed for the Ada mathematical functions library using Software Automated Verification and Validation (SAVVAS), the SSE IV and V tool. A table with selected results was shown, indicating that most of these routines are of good quality. Thresholds for the Halstead measures indicate poor quality if the length metric exceeds 260 or difficulty is greater than 190. The McCabe CCM indicated a high quality of software products.

Moebes, Travis↗
NASA NTRS2020

Progress on LISA Colloid Microthruster Technology Development

Colloid microthrusters have been operated successfully in flight, providing drag-free and precision control for spacecraft that can be used for future applications such as gravity wave and exoplanet observatories. The Space Technology 7 Disturbance Reduction System (ST7- DRS) technology demonstration payload included eight Busek Colloid Micro-Newton Thrusters (CMNTs) as part of the Laser Interferometer Space Antenna (LISA) Pathfinder mission that launched in December of 2015. The CMNTs provided full attitude and precision drag-free control of the spacecraft with <10 nm/√Hz stability along the most sensitive axis during commissioning, nominal, and extended mission phases through April of 2017. Performance requirements (≤0.1 μN/√Hz) were met and models were validated based on on- orbit measurements of test mass motion and actuation during the 60-day nominal and 30-day extended missions. In 2018, the European Space Agency (ESA) selected LISA to be the agency’s next “large-class” mission, currently in Phase A, with a launch scheduled for 2034 and a 12.5-year duration, including the transfer (1.5 years), commissioning (1 year), nominal (4 or 6 years), and extended (6 or 4 years) phases of the mission, which sets the lifetime and consumables requirement. NASA is considering a significant contribution of hardware to the ESA-led mission, potentially including colloid microthrusters. In preparation, NASA is developing five technologies to TRL 5 and 6, including the colloid microthrusters, to be ready for infusion into LISA by the mission adoption review (MAR), currently scheduled for 2024. While ST7-DRS effectively brought the CMNTs to TRL 7, additional lower-TRL flow control components must be developed for full redundancy, reducing the system-level TRL back to 4. Key to the future of the colloid microthruster technology will be to use lessons learned and keep as much of the heritage from the ST7 design as possible while updating the system to support redundancy and lifetime requirements of a flagship-class mission. This paper describes the technology plan and progress to reach TRL 6 by the MAR, focusing on near- term plans to reach TRL 5 by the end of March 2022 for the LISA Colloid Microthrusters (CMTs). Work includes requirements development and sizing studies, breadboard and brassboard hardware developments at Busek, including relevant lifetime and environment testing, and lifetime modeling, verification and validation efforts at JPL, UCLA, and UCI.

Gamero-Castaño, Manuel↗
NASA NTRS2022

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗
NASA NTRSDate not supplied

Predicting Fiber Failure of Plain Weave Fabric with Recursive Multiscale Micromechanics

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of machine learning models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based, modeling of material behavior at various length scales, and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using machine learning (ML) techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train machine learning models and the defining model parameters and architectures. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in for various types of machine learning models while following outlined best practices for effective data management. An effective schema for machine learning data and models can help prevent the recreation of virtual/real training data and surrogate models, can help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Failure↗
DOE OSTI2021

Involute Working Group – FSI Analysis of Fuel Plates Using Finite Volume and Finite Element Methods

The three involute plate research reactors RHF, HFIR, and FRM II have expressed an interest in using computational software to carry their steady-state safety analysis. Since these tools represent a significant departure from the methods used currently (one-dimensional), the acceptability of the new approach by regulators requires thorough verification and validation of these tools. Therefore, Argonne National Laboratory and the three involute-plate reactors formed an informal group called the Involute Working Group aiming at qualifying computational tools to perform steady-state safety analysis. The present report focuses on a comparison of finite volume and finite element methods to model solids in fluid-structure interaction problems with the goal to estimate the coolant flow-induced fuel plate deflections obtained with the two methods. The finite volume method will be obsoleted in STARCCM+ by the end of 2021, nevertheless, this evaluation is important because the method was used by ANL researchers to model the response of the fuel plates, despite its drawbacks, which are discussed in the report. It was essential to check how those estimates compare to the results obtained with the finite element method that is considered superior for structural analysis. Various geometries, i.e., flat, cylindrical and circle-involute fuel plates, as well as coolant flow speed, were considered. The comparison shows that, independently of the plate geometry, the finite volume method significantly underestimates the deflection as compared to finite element method for coarser meshes. When the discretization is developed as a result of a mesh sensitivity study using finite element method, the result obtained using finite volume method can be a few times smaller than the corresponding finite element method solution. A code-to-code comparison , between STAR-CCM+ and LS-DYNA was included in the analysis. Within the LS-DYNA models, two types of finite element formulations were used: solid and shell finite elements. Mesh sensitivity study showed that both approaches converge to a similar value that was obtained with STAR-CCM+ finite element solver. The evaluation of the computational solvers was extended by adding two benchmark cases from the STAR-CCM+ Verification Suite and presented in the Appendix A. The selected cases are: (1) bending of a cantilever beam under external load, and (2) cylindrical shell deformation analysis, known in the literature as ‘Scordelis-Lo roof’. The problems were solved with finite volume, and finite element methods, and the results confirmed the previously discussed findings. The analysis shows that the finite element solver is superior to the finite volume solver in terms of representation of model geometry and estimating the structural behavior of fuel plates. Depending on the ratio of the load to the flexibility of the plate, the finite volume solver can greatly under- or overestimate the structural response if a very carefully selected mesh is not used.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2024

Workshop on the Role of Design Assurance in System-Wide Safety’s Safety Demonstrator Series

This report summarizes a three-hour hybrid in-person/online workshop on June 7, 2024 on the topic of design assurance and the Safety Demonstrator Series (SDS), which was held at NASA Ames Research Center. The SDS provides an operational demonstration of, and recommendations for, requirements and standards necessary to monitor, assess, and mitigate risks to assure safety in disaster-oriented operations. Over sixty NASA personnel participated in the workshop. Four main topics were discussed: (1) assurance needs for the Safety Demonstrator Series, (2) assurance and the In-Time Aviation Safety Management System (IASMS), (3) in-time assurance: existing efforts and future opportunities, and (4) demonstrating assurance tools in the Safety Demonstrators. Key takeaways are as follows: 1. Design assurance tools can be used to assure an In-Time Aviation Safety Management System, the systems that comprise it, and other systems or missions. Assurance must consider both systems and components and include the interactions between elements in both a systems/aircraft context and a systems-of-systems/airspace context. 2. Design-time assurance activities can support the identification of monitors needed for operational assurance activities (i.e., the “monitor” function in the monitor-assess-mitigate paradigm at the heart of the IASMS concept). 3. A major opportunity for design-time assurance tools to contribute to the IASMS concept is to support rapid re-validation of systems. This will be particularly important for (1) supporting novel operations in the IASMS, where operational data may disprove design-time assumptions (motivating re-analysis of system safety) and (2) adapting technologies (e.g., AI/ML for autonomous operations) to new operational domains, where there may be new or different safety considerations not included in the initial scope of operations. 4. There are several design assurance tools under development in the System-Wide Safety project that can support assurance of Services, Functions, and Capabilities (SFCs) in the Safety Demonstrators. Transitioning these tools from one-off research projects into a functioning part of IASMS assurance will require closer integration between these tools. 5. It is not clear whether the role of design assurance tools is primarily as a part of IASMS architecture or as an external check on IASMS. The workshop consisted of four discussion topics initiated via four lightning talks by System-Wide Safety researchers. Discussions utilized Mural to engage both in-person and online participants in the hybrid format. Polls and surveys were also utilized to gather participant input. The workshop closed with a reflection activity for participants, as well as new ideas for collaboration and coordination of ongoing System-Wide Safety research.

design assurance↗
NASA NTRS2012

The Pursuit of K: Reflections on the Current State-of-the-Art in Stress Intensity Factor Solutions for Practical Aerospace Applications

The elastic stress intensity factor (SIF, commonly denoted as K) is the foundation of practical fracture mechanics (FM) analysis for aircraft structures. This single parameter describes the first-order effects of stress magnitude and distribution as well as the geometry of both structure/component and crack. Hence, the calculation of K is often the most significant step in fatigue analysis based on FM. This presentation will provide several reflections on the current state-of-the-art in SIF solution methods used for practical aerospace applications, including a brief historical perspective, descriptions of some recent and ongoing advances, and comments on some remaining challenges. Newman and Raju made significant early contributions to practical structural analysis by developing closed-form SIF equations for surface and corner cracks in simplified geometries, often based on empirical fits of finite element (FE) solutions. Those solutions (and others like them) were sometimes revised as new analyses were conducted or limitations discovered. The foundational solutions have exhibited striking longevity, despite the relatively "coarse" FE models employed many decades ago. However, in recent years, the accumulation of different generations of solutions for the same nominal geometry has led to some confusion (which solution is correct?), and steady increases in computational capabilities have facilitated the discovery of inaccuracies in some (not all!) of the legacy solutions. Some examples of problems and solutions are presented and discussed, including the challenge of maintaining consistency with legacy design applications. As computational power has increased, the prospect of calculating large numbers of SIF solutions for specific complex geometries with advanced numerical methods has grown more attractive. Fawaz and Andersson, for example, have been generating literally millions of new SIF solutions for different combinations of multiple cracks under simplified loading schemes using p-version FE methods. These data are invaluable, but questions remain about their practical use, because the tabular databases of key results needed to support practical life analysis can occupy gigabytes of storage for only a few classes of geometries. The prospect of using such advanced numerical methods to calculate in real time only those K solutions actually needed to support a specific crack growth analysis is also tempting, but the stark reality is that the computational cost is still so high that the approach is not practical except for specific, critical application problems. Some thoughts are offered about alternative paradigms. Compounding approaches are some of the earliest building blocks of SIF development for more complex geometries. These approaches are especially attractive because of their very low computational cost and their conceptual robustness; they are, in some ways, an intriguing contrast and complement to the brute-force numerical methods. In recent years, researchers at NRC-Canada have published remarkable results showing how compounding approaches can be used to generate accurate solutions for very difficult problems. Examples are provided of some successes--and some limitations--using this approach. These closed-form, tabulated numerical, and compounding approaches have typically been used for simple remote loading with simple load paths to the crack. However, many significant cracks occur in complex stress gradient fields. This is a job for weight function (WF) methods, where the arbitrary stress distribution on the crack plane in the corresponding uncracked body (typically determined using FE methods) is used to determine K. Several significant recent advances in WF methods and solutions are highlighted here. Fueled by advanced 3D numerical methods, many new solutions have been generated for classic geometries such as surface and corner cracks with wide ranges of geometrical validity. A new WF formulation has also be developed for part-through cracks considering the arbitrary stress gradients in all directions in the crack plane (so-called bivariant solutions). Basic WF methods have recently been combined with analytical expressions for crack plane stresses to develop a large family of accurate SIF solutions for corner, surface, and through cracks at internal or external notches with very wide ranges of shapes, sizes, acuities, and offsets. Finally, WF solutions are much faster than FE or boundary element solutions, but can still be much slower than simple closed-form solutions, especially for bivariant solutions that can require 2D numerical integration. Novel pre-integration and dynamic tabular methods have been developed that substantially increase the speed of these advanced WF solutions. The practical utility of advanced SIF methods, including both WF and direct numerical methods, is greatly enhanced if the FM life analysis can be directly and efficiently linked with digital models of the actual structure or component (e.g., FE models for stress analysis). Two recent advances of this type will be described. One approach directly interfaces the FM life analysis with the FE model of the uncracked component (including stress results). Through a powerful graphical user interface, simplified FM life models can be constructed (and visualized) directly on the component model, with the computer collecting the geometry and stress gradient information needed for the life calculation. An even more powerful paradigm uses expert logic to automatically build an optimum simple fracture model at any and every desired location in the component model, perform the life calculation, and even generate fatigue crack growth life contour maps, all with minimal user intervention. This paradigm has also been extended to the automatic calculation of fracture risk, considering uncertainty or variability in key input parameters such as initial crack size or location. Another new integrated approach links the engineering life analysis, the component model, and a 3D numerical fracture analysis built with the same component model to generate a table of SIF values at a specific location that can then be employed efficiently to perform the life calculation. Some attention must be given to verification and validation (V&V) issues and challenges: how good are these SIF solutions, how good is good enough, and does anyone believe the life answer? It is important to think critically about the different sources of error or uncertainty and to perform V&V in a hierarchal, building-block manner. Some accuracy issues for SIF solutions, for example, may actually involve independent material behavior issues, such as constraint loss effects for crack fronts near component surfaces, and can be a source of confusion. Recommendations are proposed for improved V&V approaches. This presentation will briefly but critically survey the range of issues and advances mentioned above, with a particular view towards assembling an integrated approach that combines different methods to create practical tools for real-world design and analysis problems. Examples will be selectively drawn from the recent literature, from recent enhancements in the NASGRO and DARWIN computer codes, and from previously unpublished research

CraigMcClung, R.↗
NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗
NASA NTRS2007

Full Life-Cycle Defect Management Assessment: Initial Inspection Data Collection Results and Research Questions for Further Study

It is often the case in software projects that when schedule and budget resources are limited, the Verification and Validation (V&V) activities suffer. Fewer V&V activities can be afforded and moreover, short-term challenges can result in V&V activities being scaled back or dropped altogether. As a result, too often the default solution is to save activities for improving software quality until too late in the life-cycle, relying on late-term code inspections followed by thorough testing activities to reduce defect counts to acceptable levels. As many project managers realize, however, this is a resource-intensive way of achieving the required quality for software. The Full Life-cycle Defect Management Assessment Initiative, funded by NASA s Office of Safety and Mission Assurance under the Software Assurance Research Program, aims to address these problems by: Improving the effectiveness of early life-cycle V&V activities to make their benefits more attractive to team leads. Specifically, we focus on software inspection, a proven method that can be applied to any software work product, long before executable code has been developed; Better communicating this effectiveness to software development teams, along with suggestions for parameters to improve in the future to increase effectiveness; Analyzing the impact of early life-cycle V&V on the effectiveness and cost required for late life-cycle V&V activities, such as testing, in order to make the tradeoffs more apparent. This white paper reports on an initial milestone in this work, the development of a preliminary model of inspection effectiveness across multiple NASA Centers. This model contributes toward reaching our project goals by: Allowing an examination of inspection parameters, across different types of projects and different work products, for an analysis of factors that impact defect detection effectiveness. Allowing a comparison of this NASA-specific model to existing recommendations in the literature regarding how to plan effective inspections. Forming a baseline model which can be extended to incorporate factors describing: the numbers and types of defects that are missed by inspections; how such defects flow downstream through software development phases; how effectively they can be caught by testing activities in the late stages of development. The model has been implemented in a prototype web-enabled decision-support tool which allows developers to enter their inspection data and receive feedback based on a comparison against the model. The tool also allows users to access reusable materials (such as checklists) from projects included in the baseline. Both the tool itself and the model underlying it will continue to be extended throughout the remainder of this initiative. As results of analyzing inspection effectiveness for defect containment are determined, they can be shared via the tool and also via updates to existing training courses on metrics and software inspections. Moreover, the tool will help satisfy key CMMI requirements for the NASA Centers, as it will enable NASA to take a global view across peer review results for various types of projects to identify systemic problems. This analysis can result in continuous improvements to the approach to verification.

Shull, Forrest↗
DOE OSTI2025

ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing

Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly translated codes from one programming model to another. We evaluate a number of base models and compare and contrast their features and characteristics that make them a viable starting point. In this paper, we focus on the OpenMP offload porting capabilities of ChatPORT. We build our training data using kernels from the Heterogeneous Computing Benchmarks (HeCBench) [12] and the OpenMP Validation and Verification suite [5] to fine-tune the base models. We then test the model using unseen kernels extracted from the HeCBench benchmark suite. Our results show that: (1) not all open LLMs geared towards HPC are aware of programming models like OpenMP, (2) although all base models benefit from fine-tuning they learn differently and produce different correctness rates, (3) depending on the memory size and compute resource available, different base models can be used for fine-tuning without significantly affecting the quality of transpiled code they generate, (4) fine-tuning improved the correctness rate of the LLM by an average of 43.2%, and (5) feedback-based training data further increased the correctness rate by an average of 6% over the LLMs tested.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2021

Microstructure-Based Estimation of Strength and Ductility Distributions for \(\alpha +\beta \) Titanium Alloys

Titanium alloys are processed to develop a wide range of microstructure configurations and therefore material properties. While these properties are typically measured experimentally, a framework for property prediction could greatly enhance alloy design and manufacturing. In this work, a microstructure-sensitive framework is presented for the prediction of strength and ductility as well as estimates of the bounds in variability for these properties. The framework explicitly considers distributions of microstructure via new approaches for instantiation of structure in synthetic samples. The parametric evaluation strategy, including the finite element simulation package FEpX, is used to create and test virtual polycrystalline samples to evaluate the variability bounds of mechanical properties in Ti-6Al-4V. Critical parameters for the property evaluation framework are provided by measurements of single crystal properties and advanced characterization of microstructure and slip system strengths in 2D and 3D. Property distributions for yield strength and ductility are presented, along with the validation and verification steps undertaken. Comparisons between strain localization and slip activity in virtual samples and in experimental grain-scale strain measurements are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Contact pressure analysis to allow improved design for the clearing plate in a biomass comminution system

For biomass processing systems, feedstocks with small but equal sizes can improve flowability and thermochemical outputs. The Crumbler rotary shear system was designed to achieve such ideal feedstocks to reduce costs and energy throughout the biomass supply chain. Improving the wear resistance of major components in this system is important to decrease the cost. Accelerating the feedstock flow through the rotary shear machine plays an equivalent role of improving its efficiency. An analytical analysis and a finite-element analysis of the stationary clearing plate are presented in this work. Here, these tools are used to investigate the effect of contact surface curvature on the impact pressure. The optimized new clearing plate design is expected to improve the component’s lifetime and wood chips flowability. The field tests confirm that the trend of the new clearing plate design guided by FEA. The optimization method, model verification, and validation experience applied in this work can also be applied to other static components with similar simple contact wear problems.

09 BIOMASS FUELS↗
DOE OSTI2020

SCALE capabilities for high temperature gas-cooled reactor analysis

The SCALE code system’s ability to address stochastic distributions of fuel particles within a graphite matrix has been revisited in both multigroup (MG) features and continuous-energy (CE) Monte Carlo methods. Furthermore, this paper describes current and emergent SCALE capabilities within the CSAS sequence to address double-heterogeneous systems and presents verification and validation studies of these methods and data. Good agreement was obtained for a high temperature gas-cooled reactor (HTGR) fuel pebble model between CSAS MG eigenvalue calculations and corresponding CE reference solutions. Code-to-code comparisons for this HTGR pebble model showed good agreement of CSAS-KENO and CSAS-Shift CE calculations and the Serpent and MCNP codes in terms of eigenvalues and reaction rate ratios. Validation studies based on two HTGR experiments resulted in good agreement between MG and CE results, as well as between experiment and calculation, although the level of agreement was significantly influenced by the applied ENDF/B nuclear data library.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Lattice physics calculations using the embedded self-shielding method in polaris, Part II: Benchmark assessment

Polaris is a 2D multigroup lattice physics capability in the SCALE code system used for the analysis of light water reactor fuel designs. In this work, verification and validation results of Polaris in SCALE 6.2 are presented. The SCALE/KENO continuous-energy Monte Carlo code is used as a reference to compare the results of more than 2,000 combinations of pressurized water reactor and boiling water reactor lattice designs and state points. Radiochemical assay measurements were also used to assess the accuracy of depletion calculations. Results show that Polaris, with ENDF/B-VII.1 cross section library, produces accurate lattice physics data for core simulators.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Analysis of ZPPR-15 experimental data for VTR software validation

As part of the Versatile Test Reactor (VTR) program, extensive validation work is being performed to demonstrate the fidelity of the Argonne Reactor Code (ARC) software package presently used for the core design studies. It is anticipated that this software will be also used for initial operations although additional software may be introduced at a later time to supplement or replace some components. The validation work was focused on accumulating reactor models that are consistent with the VTR and thus can be used to validate the accuracy of predictions made by the software used to design and operate the VTR. The U.S. does not have any active experimental facilities that can neutronically mockup the VTR core design. However, in the past, the U.S. had extensive experimental facilities for fast reactor neutronics. In that regard, the ZPPR-15 experiments carried out at ANL during the 1980s work best because the fuel form is closest to the VTR design, there is a considerable amount of processed data available for use, and existing staff are already familiar with the experimental machine and measurements. Because of previous collaborative work, many of the ZPPR-15 loadings of interest have already been processed into MCNP and preliminary ARC models, and a full uncertainty quantification has already been completed for many of the ZPPR-15 measurements. This manuscript covers the recent analysis work on the ZPPR-15 experiments and compares it with the experimental results. With respect to the ARC software components, this manuscript focuses on validation of the MC 2 , DIF3D and GAMSOR using the ZPPR-15 experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Reproducible benchmark for the SNAP 8 experimental reactor at dry conditions

Here, this work provides fully reproducible benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor. Validation benchmarks of the criticality configuration experiments under dry conditions with no coolant are presented. In addition, relevant reactivity worth experiments, and measurement of power distributions are validated and presented here. Discrepancies between modeled and experimental results are at most 110 pcm for fuel and poison worths, and critical configurations that do not manipulate control elements are within 50 pcm. Larger discrepancies found in reflector element worth experiments are due to experimental methodology which was noted as being simplified due to limited calculational capabilities at the time, while discrepancy in the control element manipulated critical configuration is due the absence of structural components for modeling simplification. Power distributions closely follow what was observed in experiment with expected peaking in reflecting elements. All models are well documented with cited references describing and justifying assumptions, simplifications, and adjustments to reproduce the models with any nuclear safety codes; model inputs and outputs are stored in the snapReactors GitHub repository.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗