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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗

DOE OSTI2020

Initial conceptual demonstration of control co-design for WEC optimization

Abstract While some engineering fields have benefited from systematic design optimization studies, wave energy converters have yet to successfully incorporate such analyses into practical engineering workflows. The current iterative approach to wave energy converter design leads to sub-optimal solutions. This short paper presents an open-source MATLAB toolbox for performing design optimization studies on wave energy converters where power take-off behavior and realistic constraints can be easily included. This tool incorporates an adaptable control co-design approach, in that a constrained optimal controller is used to simulate device dynamics and populate an arbitrary objective function of the user’s choosing. A brief explanation of the tool’s structure and underlying theory is presented. To demonstrate the capabilities of the tool, verify its functionality, and begin to explore some basic wave energy converter design relationships, three conceptual case studies are presented. In particular, the importance of considering (and constraining) the magnitudes of device motion and forces in design optimization is shown.

16 TIDAL AND WAVE POWER↗

DOE OSTI2019

Strategies for Minimizing Occupational Radiation Exposure in Cardiac Imaging

Purpose of Review: Radiation safety has been at the center of interest of both researchers and healthcare institutions. This review will summarize and shed light on the various techniques adapted to reduce staff exposure to ionizing radiation (IR) in the field of cardiac imaging. Recent Findings: In the last years, with the advance of awareness and the development of new technologies, there have been several tools and techniques adapted. The breakthrough of several technologies to lower radiation dose and shorten the duration of diagnostic tests associated with IR, the use of protection devices by staff members, and mostly the awareness of exposure to IR are the hallmark of these advances. Using all these measures has led to a significant decrease in staff exposure to IR. Summary: Reducing staff exposure to meet the “As Low As Reasonably Achievable” principle is feasible. This review introduces the most important strategies applied in cardiac imaging.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS1994

A software architecture for automating operations processes

The Operations Engineering Lab (OEL) at JPL has developed a software architecture based on an integrated toolkit approach for simplifying and automating mission operations tasks. The toolkit approach is based on building adaptable, reusable graphical tools that are integrated through a combination of libraries, scripts, and system-level user interface shells. The graphical interface shells are designed to integrate and visually guide a user through the complex steps in an operations process. They provide a user with an integrated system-level picture of an overall process, defining the required inputs and possible output through interactive on-screen graphics. The OEL has developed the software for building these process-oriented graphical user interface (GUI) shells. The OEL Shell development system (OEL Shell) is an extension of JPL's Widget Creation Library (WCL). The OEL Shell system can be used to easily build user interfaces for running complex processes, applications with extensive command-line interfaces, and tool-integration tasks. The interface shells display a logical process flow using arrows and box graphics. They also allow a user to select which output products are desired and which input sources are needed, eliminating the need to know which program and its associated command-line parameters must be executed in each case. The shells have also proved valuable for use as operations training tools because of the OEL Shell hypertext help environment. The OEL toolkit approach is guided by several principles, including the use of ASCII text file interfaces with a multimission format, Perl scripts for mission-specific adaptation code, and programs that include a simple command-line interface for batch mode processing. Projects can adapt the interface shells by simple changes to the resources configuration file. This approach has allowed the development of sophisticated, automated software systems that are easy, cheap, and fast to build. This paper will discuss our toolkit approach and the OEL Shell interface builder in the context of a real operations process example. The paper will discuss the design and implementation of a Ulysses toolkit for generating the mission sequence of events. The Sequence of Events Generation (SEG) system provides an adaptable multimission toolkit for producing a time-ordered listing and timeline display of spacecraft commands, state changes, and required ground activities.

Miller, Kevin J.↗

DOE OSTI2026

HydraGNN_GFM_FineTuning4Materials v1.0

This repository enables fine-tuning of the HydraGNN Predictive GFM 2026 — an open-source ensemble of pre-trained graph foundation models for atomistic materials modeling, developed at Oak Ridge National Laboratory. The GFM 2026 is freely available and downloadable via Globus from the OLCF Data Constellation (DOI: 10.13139/OLCF/2562660). Starting from these pre-trained weights, this repository provides a complete transfer learning pipeline for adapting the GFM ensemble to domain-specific molecular and materials property prediction tasks. It includes: 1) Utilities for ensemble fine-tuning with task-specific output heads 2) Example pipelines for eight widely-used materials and molecular datasets 3) Tools for model adaptation and head configuration 4) Data preprocessing utilities for each supported dataset 5) Benchmarking and evaluation scripts

Ungerboeck, Linda↗

DOE OSTI2014

Attribute Studies of Points, Perforators, Knives, and Lithic Caches from Ayn Ab$\bar{u}$ Nukhayla

This is an in-depth study of two distinct tool types recovered from the Early Neolithic site of Ayn Abu Nukhayla, located in southern Jordan. This occupation dates to 9,500 to 7,500 BP in the Pre-Pottery Neolithic B and is comprised of regionally varied settlements reflecting a range of economic adaptations. The two tool types of concern are Nahal Hemar Knives (so named for their resemblance to a similar tool found in the Israeli site of Nahal Hemar Cave) and Nukhayla perforators. The analyses focus on creating an overall description of the tool assemblages themselves while also attempting to identify changes in tool morphology through space and time. The tools are compared with similar types from across the Neolithic Levant in an attempt to draw comparisons between the assemblages found at Ayn Abu Nykhayla and other sites from the same period.

Nowell, April↗

DOE OSTI2014

Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.

Etingov, Pavel↗

DOE OSTI2023

Improvements in Reflected Target Non-intrusive Assessment (ReTNA)

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. In 2022, NREL presented a new indoor optical measurement system to measure fully assembled heliostats during development and on the assembly line for quality assurance purposes, which has undergone significant development in the last year, including the installation of a new, larger laboratory setup. This system, called ReTNA (Reflected Target Non-intrusive Assessment), uses a printed pattern as a deflectometry target. Using printed pattern features as deflectometry targets instead of fringes allows the software to measure the surface slope in two dimensions, eliminating the need to for changing, projected targets. In the last year, NREL's ReTNA tool has been adapted to use a tall, thin target, that only spans one dimension of the mirror, and a camera moving on an automatic track system. We will present these new developments, including the new setup, target patterns, software methodology for fast, automatic optical analysis, and important lessons learned throughout the process. ReTNA results will be compared to established tools, to establish the uncertainty of this new method. ReTNA leverages recent improvements in computer vision and photogrammetry to remove as much careful calibration from the setup process as possible, making the tool low cost, simple, and portable. While it will not achieve the resolution of a fringe deflectometry system, its advantages make it well suited for CSP evaluation, and allow it to fill a different industry need.

concentrating solar power↗

DOE OSTI2018

Conservation management and ecosystem services in midwestern United States agricultural systems

The recognition that agricultural systems provide services beyond food production has motivated federal legislation and associated programs that promote sustainable management and conservation of productive working lands. This study evaluates the ability of the USDA Natural Resources Conservation Service's (NRCS) Conservation Measurement Tool (CMT), which has been used to determine eligibility for enrollment in the Conservation Stewardship Program, to reflect changes in ecosystem services resulting from the use of conservation management practices on croplands. This work evaluates four macroconcerns or outcomes (soil erosion, soil quality, water quality, and air quality) that are quantified within the tool by comparing CMT scores tabulated according to practices reported by farmers involved in grain producing operations in the US Midwest with soil health measures (dynamic soil properties [DSPs]) determined on 72 Illinois farm fields. Three management practice categories-Conventional, Conservation, and Organic-were evaluated. The CMT identified significant differences among management categories, and scores ranked consistently higher for Organic than Conventional or Conservation systems. Direct analysis of DSPs suggested that there were relatively small differences among soil health indicators measured on farms under varied management; this implies that the CMT might be overemphasizing the influence of selected management practices. The evaluation of multivariate relationships between the practices scored in the CMT and DSPs revealed that soil properties like soil pH and particulate organic matter-carbon (POM-C) can be used to improve the accuracy of the tool. They also show how relationships between questions (practices) and outcomes suggested by DSPs vary among farming categories and suggest this type of practice-based tool should be adapted by embedding factors to scale farming systems or, preferably, by adding questions that better describe important factors (e.g., plant productivity and fertilizer timing, rate, and form of application) and their interactions with other factors known to influence specific outcomes. This work shows how field data describing practices, properties, and outcomes can be used to statistically evaluate and refine conservation scoring tools.

conservation measurement tool↗

NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or aerial wildfire operations reports to better understand the risks present. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement. These applications can benefit from the use of state-of-the-art natural language processing techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of adaptation of NLP tools to the aviation domain by fine-tuning transformer based models using aviation data sets. In 2018, a novel language model based on neural units (also called transformers) was created and became known as “Bidirectional Encoder Representations from Transformers” or BERT. This architecture combined with large amounts of English training data and innovative semi-supervised training tasks set the standard for what would later emerge as Large Language Models. The performance of these models was further improved by hyperparameter tuning and refinement of the semi-supervised training task and resulted in “Robustly Optimized BERT Pre-training Approach through hyperparameter tuning” or RoBERTa models. These pre-trained Large Language Models proved to be useful for a wide variety of natural language processing tasks such as text classification and question answering through a process called fine-tuning. The transformer architecture with pre-trained weights served as the basis with the last few layers replaced with layers fine-tuned to perform a new task e.g., a layer that provides a label for the entire input text. This process of fine-tuning can also be used to adapt the models to new domains; e.g., BioBERT started with the pre-trained BERT model and was completed by additional fine-tuning and training on biomedical documents. Transformer-based architectures can also be used to create rich representations of text called embeddings which can serve as the input to other machine learning models. This allows simpler algorithms such as logistic regression to use context-rich representations of the text while still remaining quick to train and evaluate. In the world of aviation, there is a growing demand for natural language processing and understanding but the domain presents unique challenges. Due to the technical content (and specialized language) of most aviation documents, fine-tuning pre-trained Large Language Models to specific tasks has not met the benchmark on natural language processing tasks set by simpler models trained from scratch on the data. To address this deficiency, this paper evaluates the improvements from fine-tuning a Large Language Model on a large set of aviation documents using the original semi-supervised training tasks before performing specific natural language tasks. In fine-tuning, a domain-specific dataset is used on the original training task but with the pre-trained Large Language Model instead of starting from a random initialization. This approach allows the model to be adapted to the specific domain language without discarding the information gained from training on general English data. This paper utilized two major dataset types to train and assess the RoBERTa fine-tuning performance. The first are 7,057 Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the semi-supervised fine-tuning. The second type is the 494 document classification labels to be used for evaluation. This down-stream evaluation aims to show the performance of the fine-tuned model, better understand how much data is needed for an effective fine-tuning, and how fine-tuning can be adapted for different applications in-the domain. After semi-supervised training, evaluation begins by encoding the documents for classification using the fine-tuned RoBERTa model. Then a logistic regression classifier is trained to label the document type and compared against our ground truth labels. This currently leads to a 82.8% accuracy on 10-fold cross validation showing improvement over baseline RoBERTa which achieved 81.0%. We plan to measure the improvements on additional tasks and it is expected that these improvements will lead to more robust models that can tackle the natural language processing challenges present in aviation datasets.

ATM↗

NASA NTRS2015

Jovian plasma modeling for mission design

The purpose of this report is to address uncertainties in the plasma models at Jupiter responsible for surface charging and to update the jovian plasma models using the most recent data available. The updated plasma environment models were then used to evaluate two proposed Europa mission designs for spacecraft charging effects using the Nascap-2k code. The original Divine/Garrett jovian plasma model (or "DG1", T. N. Divine and H. B. Garrett, "Charged particle distributions in Jupiter's magnetosphere," J. Geophys. Res., vol. 88, pp. 6889-6903,1983) has not been updated in 30 years, and there are known errors in the model. As an example, the cold ion plasma temperatures between approx.5 and 10 Jupiter radii (Rj) were found by the experimenters who originally published the data to have been underestimated by approx.2 shortly after publication of the original DG1 model. As knowledge of the plasma environment is critical to any evaluation of the surface charging at Jupiter, the original DG1 model needed to be updated to correct for this and other changes in our interpretation of the data so that charging levels could beproperly estimated using the Nascap-2k charging code. As an additional task, the Nascap-2k spacecraft charging tool has been adapted to incorporate the so-called Kappa plasma distribution function--an important component of the plasma model necessary to compute the particle fluxes between approx.5 keV and 100 keV (at the outset of this study,Nascap-2k did not directly incorporate this common representation of the plasma thus limiting the accuracy of our charging estimates). The updating of the DG1 model and its integration into the Nascap-2k design tool means that charging concerns can now be more efficiently evaluated and mitigated. (We note that, given the subsequent decision by the Europa project to utilize solar arrays for its baseline design, surface charging effects have becomeeven more of an issue for its mission design). The modifications and results of those modifications to the DG1 model to produce the new DG2 model presented here and the steps taken to integrate the DG2 predictions into Nascap-2k are described in this report.

Voyager 2↗

NASA NTRS2015

Jovian Plasma Modeling for Mission Design

Garrett, Henry B.↗

DOE OSTI2021

Universal dwell time optimization for deterministic optics fabrication

Computer-Controlled Optical Surfacing (CCOS) has been greatly developed and widely used for precision optical fabrication in the past three decades. It relies on robust dwell time solutions to determine how long the polishing tools must dwell at certain points over the surfaces to achieve the expected forms. However, as dwell time calculations are modeled as ill-posed deconvolution, it is always non-trivial to reach a reliable solution that 1) is non-negative, since CCOS systems are not capable of adding materials, 2) minimizes the residual in the clear aperture 3) minimizes the total dwell time to guarantee the stability and efficiency of CCOS processes, 4) can be flexibly adapted to different tool paths, 5) the parameter tuning of the algorithm is simple, and 6) the computational cost is reasonable. In this study, we propose a novel Universal Dwell time Optimization (UDO) model that universally satisfies these criteria. First, the matrix-based discretization of the convolutional polishing model is employed so that dwell time can be flexibly calculated for arbitrary dwell points. Second, UDO simplifies the inverse deconvolution as a forward scalar optimization for the first time, which drastically increases the solution stability and the computational efficiency. Finally, the dwell time solution is improved by a robust iterative refinement and a total dwell time reduction scheme. The superiority and general applicability of the proposed algorithm are verified on the simulations of different CCOS processes. A real application of UDO in improving a synchrotron X-ray mirror using Ion Beam Figuring (IBF) is then demonstrated. The simulation indicates that the estimated residual in the 92.3 mm × 15.7 mm CA can be reduced from 6.32 nm Root Mean Square (RMS) to 0.20 nm RMS in 3.37 min. After one IBF process, the measured residual in the CA converges to 0.19 nm RMS, which coincides with the simulation.

36 MATERIALS SCIENCE↗

NASA NTRS1998

A Robust Parallel Adaptive Mesh Refinement Software Library for Unstructured Meshes

The design and development of a software tool for performing parallel adaptive mesh refinement in unstructured computations on multiprocessor systems are described.

parrallel adaptive mesh refinement unstructured me↗

DOE OSTI2019

Highly interactive, steered scientific workflows on HPC systems: optimizing design solutions

Scientific workflows are becoming increasingly important in high performance computing (HPC) settings, as the feasibility and appeal of many simultaneous heterogeneous tasks increases with increasing hardware capabilities. Currently no HPC-based workflow platform supports a dynamically adaptable workflow with interactive steering and analysis at run-time. Furthermore, for most workflow programs, compute resources are fixed for a given instance, resulting in a possible waste of expensive allocation resources when tasks are spawned and killed. Here we describe the design and testing of a run-time-interactive, adaptable, steered workflow tool capable of executing thousands of parallel tasks without an MPI programming model, using a database management system to facilitate task management through multiple live connections. We find that on the Oak Ridge Leadership Computing Facility pre-exascale Summit supercomputer it is possible to launch and interactively steer workflows with thousands of simultaneous tasks with negligible latency. For the case of particle simulation and analysis tasks that run for minutes to hours, this paradigm offers the prospect of a robust and efficient means to perform simulation-space exploration with on-the-fly analysis and adaptation.

Ossyra, John R↗

DOE OSTI2015

SU-E-J-78: Adaptive Planning Workflow in a Pencil Beam Scanning Proton Therapy Center

Purpose: The susceptibility of proton therapy to changes in patient setup and anatomy necessitates an adaptive planning process. With the right planning tools and clinical workflow, an adaptive plan can be created in a timely manner without adding significant workload to the treatment planning staff. Methods: In our center, a weekly QA CT is performed on most patients to assess setup, anatomy change, and tumor response. The QA CT is fused to the treatment planning CT, the contours are transferred via deformable registration, and the plan dose is recalculated on the QA CT. A physicist assesses the dose distribution, and an adaptive plan is requested based on tumor coverage or OAR dose changes. After the physician confirms or alters the deformed contours, a dosimetrist develops an adaptive plan using our TPS adaptation module. The plan is assessed for robustness and is then reviewed by the physician. Patient QA is performed within three days following the first adapted treatment. Results: Of the patients who received QA CTs, 19% required at least one adaptive plan (18.5% H&N, 18.5% brain, 11.1% breast, 14.8% chestwall, 14.8% lung, 18.5% pelvis and 3.8% abdomen). Of these patients, 14% went on a break, while the remainder was treated with the previous plan during the re-planning process. Adaptive plans were performed based on tumor shrinkage, anatomy change or positioning uncertainties for 37.9%, 44.8%, and 17.3% of the patients, respectively. On average, 3 full days are required between the QA CT and the first adapted plan treatment. Conclusion: Adaptive planning is a crucial component of proton therapy and should be applied to any site when the QA CT shows significant deviation from the plan. With an efficient workflow, an adaptive plan can be applied without delaying patient treatment or burdening the dosimetry and medical physics team.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Identifying limitations in screening high-throughput photocatalytic bimetallic nanoparticles with machine-learned hydrogen adsorptions

The Sabatier principle is of fundamental importance to computational catalyst discovery, saving researchers time and expense by predicting catalytic activity in silico at scale. However, as polycrystalline and nanoscale catalysts increasingly dominate industry, computational screening tools must be adapted to these uses. In this work, we demonstrate the effectiveness of computational adsorption energy screening in nanocatalysis by comparing a multisite adsorption energy prediction workflow against a large experimental dataset of hydrogen evolution activities over bimetallic nanoparticles. Comparing 16 million hydrogen adsorption energy predictions with the hydrogen evolution activity of 5300 experiments across 84 monometallic and bimetallic systems, we discover that favorable adsorption energies are a necessary condition for experimental activity, but other factors often determine trends in practice. Finally, about half of the bimetallic search space can be excluded from experimental screens using hydrogen adsorption predictions, but this method may become significantly more powerful when combined with other screening tools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

HiSpatialCluster: A novel high‐performance software tool for clustering massive spatial points

Abstract In the era of big data, spatial clustering is a very important means for geo‐data analysis. When clustering big geo‐data such as social media check‐in data, geotagged photos, and taxi trajectory points, traditional spatial clustering algorithms are facing more challenges. On the one hand, existing spatial clustering tools cannot support the clustering of massive point sets; on the other hand, there is no perfect solution for self‐adaptive spatial clustering. In order to achieve clustering of millions or even billions of points adaptively, a new spatial clustering tool—HiSpatialCluster—was proposed, in which the CFSFDP (clustering by fast search and finding density peaks) idea to find cluster centers and the DBSCAN (density‐based spatial clustering of applications with noise) idea of density‐connect filtering for classification are introduced. The tool’s source codes and other resources have been released on Github, and experimental evaluation was performed through clustering massive taxi trajectory points and Flickr geotagged photos in Beijing, China. The spatial clustering results were compared with those through K‐means and DBSCAN as well. As a spatial clustering tool, HiSpatialCluster is expected to play a fundamental role in big geo‐data research. First, this tool enables clustering adaptively on massive point datasets with uneven spatial density distribution. Second, the density‐connect filter method is applied to generate homogeneous analysis units from geotagged data. Third, the tool is accelerated by both parallel CPU and GPU computing so that millions or even billions of points can be clustered efficiently.

Chen, Yiran↗