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ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

DOE OSTI2024

Strategies and Good Practices to Support Robust Stakeholder Engagement in Multi-Sector Energy Transition Planning

This document discusses strategies and good practices to facilitate diverse stakeholder engagement and inclusive decision-making within the context of complex energy system modernization studies and multi-sector energy transition planning, drawing upon the knowledge and expertise of numerous USAID, NREL, and other DOE laboratory practitioners with international and domestic energy planning experience. Examples of multi-sector energy transition analyses from the United States are included in this document to draw out relevant lessons learned and experience for the USAID-NREL Partnership - strategies and good practices will be updated over time as new insights emerge through collaboration with international partners and stakeholders. Considerations included within this document can also be used to support stakeholder engagement at the sector level (e.g., for power, transport, buildings), in addition to integrated approaches.

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Using machine learning to improve efficiency and accuracy of burnup measurements at PBR reactors [Slides]

The outline of the slides include: Motivations of the work; Modeling and simulation; Machine learning model; Results and comparison study with linear regression; and Conclusions. This work was done to help PBR designers and operators understand the burnup measurement better. We look forward to discussing the results in detail with industrial collaborators.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training

Federated finetuning is crucial for unlocking the knowledge embedded in pretrained Large Language Models (LLMs) when data are geographically distributed across clients. Unlike finetuning with data from a single institution, federated finetuning allows collaboration across multiple institutions, enabling the utilization of diverse and decentralized datasets while preserving data privacy. Given the high computing costs of LLM training and the emphasis on energy efficiency in Federated Learning (FL), Low-Rank Adaptation (LoRA) has emerged as a widely adopted algorithm due to its significantly reduced number of trainable parameters. However, this assumes that all data silos have the necessary computing resources to compute local updates of LLMs. Nevertheless, in practice, the computing resources across clients are highly heterogeneous: while some may have access to hundreds of GPUs, others might have limited or no GPU access. Recently, federated finetuning using synthetic data has been proposed, allowing clients to participate in a collaborative training run without training LLMs locally. However, our experimental results reveal a performance gap between models trained using synthetic data and those trained using local updates. Motivated by the observed heterogeneity in computing resources and the performance gap, we propose a novel two-stage algorithm that leverages the storage and computing capabilities of a strong server. In the first stage, under the coordination of the strong server, clients with limited computing resources collaborate to generate synthetic data, which is transferred to and stored on the strong server. In the second stage, the strong server uses this synthetic data on behalf of the resource-constrained clients to perform federated LoRA finetuning alongside clients with sufficient computing resources. This approach ensures that all clients can participate in the finetuning process. Experimental results demonstrate that incorporating local updates from even a small fraction of clients improves performance compared to using synthetic data for all clients. Furthermore, we incorporate the Gaussian mechanism in both stages to guarantee client-level differential privacy.

Wang, Jiayi [ORNL]↗

NASA NTRS2011

Contribution of Spaceflight Environmental Factors to Vision Risks

The risk of visual impairment and elevated intracranial pressure as a result of low-earth orbit microgravity exposure has directed our attention and research efforts to the eye. While the alterations observed in astronauts returning from long duration missions include vision and neuroanatomical changes observed by non-invasive methods, other effects and subsequent tissue responses at the molecular and cellular level can only be studied by accessing the tissue itself. As a result of this need, several studies are currently taking place within the Human and Health Countermeasures Element (HHC) that use animal models for eye research. The rodent eye has many similarities to the human eye, and both rats and mice have historically been used as models of human eye disease, aiding in the identification of the disease genes, elucidation of mechanisms of disease, as well as in the assessment of therapeutic treatments. These studies attempt to answer two central questions in the etiology of possible vision alterations in the environment of space exploration missions. The first is: what effects and response mechanisms take place in the different eye structures at the cellular and molecular level? The second question is directed to elucidate the contribution of the various environmental stressors (radiation, nutrition, fluid shift) to these effects. Collaborative approaches with internal and external investigators have allowed performing these studies in a most cost-effective fashion, providing preliminary data and laying the bases for testing further hypotheses in future and specifically designed animal experiments. From a study centered on the radioadaptive response in mice, we have learned that the retina responds to low and high dose gamma radiation by elevating antioxidant-related genes at early time points (4hrs) and that this response returns to control levels after 1 day post-irradiation. We are expanding this research with another collaborative study that investigates the combined effects of radiation exposure and iron overload on sensitivity to radiation injury in rat eyes. All main eye structures will be analyzed in this study: retina, lens and cornea. A study in collaboration with the Space Human Factors and Habitability Element (SHFH) investigates the effects of lunar dust exposure on the rat cornea. It is anticipated that common underlying oxidative stress mechanisms of damage may be observed as a result of these three stressors: radiation, nutritional iron and lunar dust. The contribution of fluid shift is addressed by a study using rats subjected to hindlimb suspension. The hypothesis to be tested in this study is that the mechanical stress imparted by the pressure differential across the optic disc and lamina cribosa will impact oxygenation (therefore causing oxidative stress and hypoxia) and cell survival. This study also includes the assessment of two nutritional antioxidant countermeasures: epigallocatechin gallate (green tea) and resveratrol. Finally, as a result of two successful tissue sharing efforts, we are proceeding with the analysis of eye samples of mice aboard two shuttle missions: STS-133 and STS-135. Results from the STS-133 study are presented in an independent abstract. Briefly, the results show that spaceflight represents a source of environmental stress that directly translates into oxidative and cellular stress in the retina. Similar analysis is also planned for the cornea. These samples add large value to our current vision research as they provide data on the direct effects of low-earth orbit spaceflight on eye structures and physiology.

Zanello, Susana B.↗

DOE OSTI2016

TH-F-202-02: Current Applications of MRI in Radiotherapy

MRI has excellent soft tissue contrast and can provide both anatomical and physiological information. It is becoming increasingly important in radiation therapy for treatment planning, image-guided radiation therapy, and treatment assessment. It is critically important at this time point to educate and update our medical physicists about MRI to prepare for the upcoming surge of MRI applications in radiation therapy. This session will review important basics of MR physics, pulse sequence designs, and current radiotherapy application, as well as showcase exciting new developments in MRI that can be potentially useful in radiation therapy. Learning Objectives: To learn basics of MR physics and understand the differences between various pulse sequences To review current applications of MRI in radiation therapy.To discuss recent MRI advances for future MRI guided radiation therapy Partly supported by NIH (1R21CA165384).; W. Miller, Research supported in part by Siemens Healthcare; G. Li, My clinical research is in part supported by NIH U54CA137788. I have a collaborative research project with Philips Healthcare.; J. Cai, jing cai.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-F-202-03: Advances in MRI for Radiation Therapy

60 APPLIED LIFE SCIENCES↗

NASA NTRS2011

Open Collaboration: A Problem Solving Strategy That is Redefining NASA's Innovative Spirit

In 2010, NASA's Space Life Sciences Directorate announced the successful results from pilot experiments with open innovation methodologies. Specifically, utilization of internet based external crowdsourcing platforms to solve challenging problems in human health and performance related to the future of spaceflight. The follow-up to this success was an internal crowdsourcing pilot program entitled NASA@work, which was supported by the InnoCentive@work software platform. The objective of the NASA@work pilot was to connect the collective knowledge of individuals from all areas within the NASA organization via a private web based environment. The platform provided a venue for NASA Challenge Owners, those looking for solutions or new ideas, to pose challenges to internal solvers, those within NASA with the skill and desire to create solutions. The pilot was launched in 57 days, a record for InnoCentive and NASA, and ran for three months with a total of 20 challenges posted Agency wide. The NASA@work pilot attracted over 6,000 participants throughout NASA with a total of 183 contributing solvers for the 20 challenges posted. At the time of the pilot's closure, solvers provided viable solutions and ideas for 17 of the 20 posted challenges. The solver community provided feedback on the pilot describing it as a barrier breaking activity, conveying that there was a satisfaction associated with helping co-workers, that it was fun to think about problems outside normal work boundaries, and it was nice to learn what challenges others were facing across the agency. The results and the feedback from the solver community have demonstrated the power and utility of an internal collaboration tool, such as NASA@work.

Rando, Cynthia M.↗

NASA NTRS2011

Open Collaboration: A Problem Solving Strategy That Is Redefining NASA's Innovative Spirit

In 2010, NASA?s Space Life Sciences Directorate announced the successful results from pilot experiments with open innovation methodologies. Specifically, utilization of internet based external crowd sourcing platforms to solve challenging problems in human health and performance related to the future of spaceflight. The follow-up to this success was an internal crowd sourcing pilot program entitled NASA@work, which was supported by the InnoCentive@work software platform. The objective of the NASA@work pilot was to connect the collective knowledge of individuals from all areas within the NASA organization via a private web based environment. The platform provided a venue for NASA Challenge Owners, those looking for solutions or new ideas, to pose challenges to internal solvers, those within NASA with the skill and desire to create solutions. The pilot was launched in 57 days, a record for InnoCentive and NASA, and ran for three months with a total of 20 challenges posted Agency wide. The NASA@work pilot attracted over 6000 participants throughout NASA with a total of 183 contributing solvers for the 20 challenges posted. At the time of the pilot?s closure, solvers provided viable solutions and ideas for 17 of the 20 posted challenges. The solver community provided feedback on the pilot describing it as a barrier breaking activity, conveying that there was a satisfaction associated with helping co-workers, that it was "fun" to think about problems outside normal work boundaries, and it was nice to learn what challenges others were facing across the agency. The results and the feedback from the solver community have demonstrated the power and utility of an internal collaboration tool, such as NASA@work.

Rando, Cynthia M.↗

DOE OSTI2021

Crowdsourcing Global Perspectives in Ecology Using Social Media

Transparent, open, and reproducible research is still far from routine, and the full potential of open science has not yet been realized. Crowdsourcing–defined as the usage of a flexible open call to a heterogeneous group of individuals to recruit volunteers for a task –is an emerging scientific model that encourages larger and more outwardly transparent collaborations. While crowdsourcing, particularly through citizen- or community-based science, has been increasing over the last decade in ecological research, it remains infrequently used as a means of generating scientific knowledge in comparison to more traditional approaches. We explored a new implementation of crowdsourcing by using an open call on social media to assess its utility to address fundamental ecological questions. We specifically focused on pervasive challenges in predicting, mitigating, and understanding the consequences of disturbances. In this paper, we briefly review open science concepts and their benefits, and then focus on the new methods we used to generate a scientific publication. We share our approach, lessons learned, and potential pathways forward for expanding open science. Our model is based on the beliefs that social media can be a powerful tool for idea generation and that open collaborative writing processes can enhance scientific outcomes. We structured the project in five phases: (1) draft idea generation, (2) leadership team recruitment and project development, (3) open collaborator recruitment via social media, (4) iterative paper development, and (5) final editing, authorship assignment, and submission by the leadership team. We observed benefits including: facilitating connections between unusual networks of scientists, providing opportunities for early career and underrepresented groups of scientists, and rapid knowledge exchange that generated multidisciplinary ideas. We also identified areas for improvement, highlighting biases in the individuals that self-selected participation and acknowledging remaining barriers to contributing new or incompletely formed ideas into a public document. While shifting scientific paradigms to completely open science is a long-term process, our hope in publishing this work is to encourage others to build upon and improve our efforts in new and creative ways.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume III – Stakeholder ecosystem management challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility program stakeholder ecosystem management strategies, which provide information on value delivery and describe how program implementers leverage partner capabilities and collaborate to deliver customer and grid benefits. This report discusses the role of stakeholder ecosystem management in demand flexibility programs, identifies existing challenges to effective stakeholder management, and describes lessons learned. This report is part of a series that includes reports on value propositions, customer relationship management strategies, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Combining chemistry and protein engineering for new-to-nature biocatalysis

Biocatalysis, the application of enzymes to solve synthetic problems of human import, has blossomed into a powerful technology for chemical innovation. In the past decade, a threefold partnership, where nature provides blueprints for enzymatic catalysis, chemists introduce innovative activity modes with abiological substrates, and protein engineers develop new tools and algorithms to tune and improve enzymatic function, has unveiled the frontier of new-to-nature enzyme catalysis. In this Perspective, we highlight examples of interdisciplinary studies, which have helped to expand the scope of biocatalysis, including concepts of enzymatic versatility explored through the lens of biomimicry, to achieve activities and selectivities beyond those currently possible with chemocatalysis. We indicate how modern tools, such as directed evolution, computational protein design and machine learning-based protein engineering methods, have already impacted and will continue to influence enzyme engineering for new abiological transformations. As a result, a sustained collaborative effort across disciplines is anticipated to spur further advances in biocatalysis in the coming years.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Final Report for CRADA SC16/01880.00

In this project, Sandia National Laboratories (SNL) and Rigetti Quantum Computing (RQC) collaborated to test and evaluate (T&E) an 8-qubit quantum information processor developed by RQC. SNL provided quantum circuits and data analysis protocols to benchmark the performance of the device. These protocols included gate-set tomography (GST) on 1- and 2-qubit subsystems, as well as more advanced protocols for characterizing crosstalk and drift. RQC provided high- and low-level access to the 8-qubit device, via direct collaboration: SNL was able to specify T&E experiments as lists of quantum circuits, delivered to RQC via email, and RQC then ran these experiments and delivered the resulting data back to SNL for analysis. The collaboration characterized the performance of all 1-qubit gates on all 8 qubits, and a sample 2-qubit gate on one pair of qubits. Extensive investigation of crosstalk produced nondefinitive results, and revealed significant drift that interfered with crosstalk detection. Drift was analyzed. As a result of this collaboration, SNL was able to test protocols for crosstalk and drift, and improve them in light of experimental data, while RQC was able to learn about the performance of their device and improve it by debugging.

Blume-Kohout, Robin↗

DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

A New Framework for Interstellar Medium Emission Line Models: Connecting Multiscale Simulations across Cosmological Volumes

The James Webb Space Telescope (JWST) and Atacama Large Millimeter/submillimeter Array have detected emission lines from the ionized interstellar medium (ISM) in some of the first galaxies at z ≳ 6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context. In order to meet this challenge, we introduce a novel subgrid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from H II regions within each simulated FIRE galaxy are modeled using the semianalytic HIIL INES code. A machine learning approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the H II regions around each simulated stellar particle. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower-resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the IllustrisTNG simulations at z = 6. The resulting predictions for the [O II ], [O III ], and Balmer line luminosities as a function of star formation rate agree well with current observations. Our predictions differ, however, from related works in the literature, which lack detailed subgrid ISM models. This highlights the importance of our multiscale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys.

(ISM:) H II regions↗

NASA NTRS2002

Research on Intelligent Synthesis Environments

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Noor, Ahmed K.↗

NASA NTRS2014

Space Shuttle and Hypersonic Entry

Fifty years of human spaceflight have been characterized by the aerospace operations of the Soyuz, of the Space Shuttle and, more recently, of the Shenzhou. The lessons learned of this past half decade are important and very significant. Particularly interesting is the scenario that is downstream from the retiring of the Space Shuttle. A number of initiatives are, in fact, emerging from in the aftermath of the decision to terminate the Shuttle program. What is more and more evident is that a new era is approaching: the era of the commercial usage and of the commercial exploitation of space. It is probably fair to say, that this is the likely one of the new frontiers of expansion of the world economy. To make a comparison, in the last 30 years our economies have been characterized by the digital technologies, with examples ranging from computers, to cellular phones, to the satellites themselves. Similarly, the next 30 years are likely to be characterized by an exponential increase of usage of extra atmospheric resources, as a result of more economic and efficient way to access space, with aerospace transportation becoming accessible to commercial investments. We are witnessing the first steps of the transportation of future generation that will drastically decrease travel time on our Planet, and significantly enlarge travel envelope including at least the low Earth orbits. The Steve Jobs or the Bill Gates of the past few decades are being replaced by the aggressive and enthusiastic energy of new entrepreneurs. It is also interesting to note that we are now focusing on the aerospace band, that lies on top of the aeronautical shell, and below the low Earth orbits. It would be a mistake to consider this as a known envelope based on the evidences of the flights of Soyuz, Shuttle and Shenzhou. Actually, our comprehension of the possible hypersonic flight regimes is bounded within really limited envelopes. The achievement of a full understanding of the hypersonic flight regimes will be a key enabler to facilitate the consolidation of the new emerging scenarios. The objective of this symposium is therefore to focus on lesson learned, to then analyze the main elements of those new scenarios, both from Institutional and Private sectors; and finally provide the leads for future collaboration opportunities between Italy, the United States and international partners, so to join profitably the opportunities offered by this new era of the aerospace technologies.

Campbell, Charles H.↗

NASA NTRS2014

Design and Preliminary Performance Testing of Electronegative Gas Plasma Thruster

In classical gridded electrostatic ion thrusters, positively charged ions are generated from a plasma discharge of noble gas propellant and accelerated to provide thrust. To maintain overall charge balance on the propulsion system, a separate electron source is required to neutralize the ion beam as it exits the thruster. However, if high-electronegativity propellant gases (e.g., sulfur hexafluoride) are instead used, a plasma discharge can result consisting of both positively and negatively charged ions. Extracting such electronegative plasma species for thrust generation (e.g., with time-varying, bipolar ion optics) would eliminate the need for a separate neutralizer cathode subsystem. In addition for thrusters utilizing a RF plasma discharge, further simplification of the ion thruster power system may be possible by also using the RF power supply to bias the ion optics. Recently, the PEGASES (Plasma propulsion with Electronegative gases) thruster prototype successfully demonstrated proof-of-concept operations in alternatively accelerating positively and negatively charged ions from a RF discharge of a mixture of argon and sulfur hexafluoride.i In collaboration with NASA Marshall Space Flight Center (MSFC), the Georgia Institute of Technology High-Power Electric Propulsion Laboratory (HPEPL) is applying the lessons learned from PEGASES design and testing to develop a new thruster prototype. This prototype will incorporate design improvements and undergo gridless operational testing and diagnostics checkout at HPEPL in April 2014. Performance mapping with ion optics will be conducted at NASA MSFC starting in May 2014. The proposed paper discusses the design and preliminary performance testing of this electronegative gas plasma thruster prototype.

Liu, Thomas M.↗