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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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At least 163 records · Page 9

Quantifying Capital Cost Reduction Pathways for Advanced Nuclear Reactors

The framework developed in this study is provided both as an excel sheet (https://inl.gov/content/uploads/2023/11/Nuclear-Reactor-Cost-Reduction-Pathway-Spreadsheet-Tool.xlsx) and a Python (Jupyter) Notebook (link: https://github.com/accert-dev/ACCERT/tree/main/Cost%20Reduction). Capital cost considerations are one of the primary inhibitors to the large-scale deployment of nuclear power plants. While it is widely accepted that first units will likely be expensive and relatively uncompetitive, it is reasonable to expect that subsequent units, built in relative quick succession, will be cheaper as they benefit from the so-called “learning effects”. However, the large degree of uncertainty associated with this parameter renders it challenging for first movers to invest in the first few expensive units. To resolve this impasse, the U.S. Department of Energy’s Advanced Nuclear Liftoff study advocated for the formation of large, committed order books of plants of the same technology to spread the costs across several units and kickstart the nuclear supply chain. The study also advocated best practices for avoiding overruns and keeping reactors on budget. This report builds on these key recommendations by attempting to quantify specific pathways toward cost reduction for nuclear energy. A capital cost estimation framework was built to untangle the effect of learning into a subset of key cost drivers, referred to as “levers”. Collectively, the choice of these levers is intended to reflect the decision-making of high-level stakeholders like plant owners and the government. In addition to the size of the firm orderbook, these levers included (a) cost drivers that are most often attributed to cost overruns such as architect/engineering (A/E) proficiency, construction proficiency, procurement service proficiency, design completion prior to the start of construction, and design maturity, and (b) cost reduction strategies such as modular construction, cross-site standardization, safety classification of the reactor building, and of the balance of plant. Two advanced reactor designs were leveraged as use cases and bottom-up cost estimates made with assumptions consistent with a well-executed first-of-a-kind project (WE-FOAK, i.e., almost no overruns) were used as baselines for the models. Cost correlations were surveyed from the literature to determine the impact of important variables on projected timelines and costs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Occluded Object Reconstruction for First Responders with Augmented Reality Glasses Using Conditional Generative Adversarial Networks

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.

Chow, Edward↗

Inspiring the Next Generation in Space Life Sciences

Competitive summer internships in space life sciences at NASA are awarded to college students every summer. Each student is aligned with a NASA mentor and project that match his or her skills and interests, working on individual projects in ongoing research activities. The interns consist of undergraduate, graduate, and medical students in various majors and disciplines from across the United States. To augment their internship experience, students participate in the Space Life Sciences Summer Institute (SLSSI). The purpose of the Institute is to offer a unique learning environment that focuses on the current biomedical issues associated with human spaceflight; providing an introduction of the paradigms, problems, and technologies of modern spaceflight cast within the framework of life sciences. The Institute faculty includes NASA scientists, physicians, flight controllers, engineers, managers, and astronauts; and fosters a multi-disciplinary science approach to learning with a particular emphasis on stimulating experimental creativity and innovation within an operational environment. This program brings together scientists and students to discuss cutting-edge solutions to problems in space physiology, environmental health, and medicine; and provides a familiarization of the various aspects of space physiology and environments. In addition to the lecture series, behind-the-scenes tours are offered that include the Neutral Buoyancy Laboratory, Mission Control Center, space vehicle training mockups, and a hands-on demonstration of the Space Shuttle Advanced Crew Escape Suit. While the SLSSI is managed and operated at the Johnson Space Center in Texas, student interns from the other NASA centers (Glenn and Ames Research Centers, in Ohio and California) also participate through webcast distance learning capabilities.

Hayes, Judith↗

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

machine learning↗

Lessons Learned from MARVEL Initial Fabrication and Testing

The Microreactor Applications Research Validation and Evaluation (MARVEL) project is intended to be amongst the first U.S. advanced reactor demonstrations in four decades. By virtue of being sponsored directly by the U.S. Department of Energy, the reactor is intended to benefit the broader nuclear community by exercising design processes, safety reviews, and supply chains. This project is intent on publicly documenting key lessons learned along the way toward demonstration. Building on a 2024 report that focused on lessons learned from the design and project management phase, this 2025 edition focuses on findings from the MARVEL guard vessel fabrication and primary coolant apparatus test (PCAT) testing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CHP-PRA: Sensorimotor Countermeasures Proof of Concept

The capabilities included in Crew Health and Performance (CHP) systems are designed to keep the crew healthy, happy, and productive. In doing so, the CHP system allows reductions in human related risks to be realized. All human missions, though particularly future Artemis and Mars missions, have constraints on the mass and volume allocated to the CHP system. Thus, trades must be made on how to best buy down risk while still meeting other requirements. Understanding how different CHP capabilities influence medical, performance, and long-term health risks is key to making informed choices among these trades. To address this, an integrated CHP Probabilistic Risk Assessment (PRA) model is being developed. Much like how IMPACT is designed to allow medical resource trades informed by medical risks, CHP PRA will enable analogous trades in human system risks across all CHP functions and capabilities. There are 29 Human System Risk Board (HSRB) risk areas to consider for model implementation. This effort focused solely on the implementation of countermeasures associated with sensorimotor risk. The framework and lessons learned from this proof of concept will benefit the implementation of other risks and countermeasures. Astronauts experience sensorimotor changes when entering or exiting a microgravity environment. While most sensorimotor issues are resolved within a few days, they pose a serious risk to crew health and performance during the adaptation period. This adaptation period aligns with gravity transitions and key mission phases where the crew members may be required to complete challenging tasks ideally with an undisturbed sensorimotor system. Countermeasures such as training or pharmaceuticals can be used to mitigate risk. This effort began by identifying physiological changes to the sensorimotor system that could lead to functional performance decrements or medical conditions and potential countermeasures, so that the overall effect of sensorimotor disturbance on human risk could be captured. We then selected example countermeasures, mapped relationships between countermeasures and outcomes, and used results from existing sensorimotor investigations to define the relationship between a sensorimotor countermeasure and subsequent performance of a sensorimotor-affected task. Specifically, using shuttle landing performance data, we compared the use or absence of inflight training capabilities to yield a relative performance change that can be applied to the prediction of the risk associated with manual control performance in future missions, as depicted in the figure. This sensorimotor proof of concept demonstrates how HRP research information can be transformed into quantifiable relationships to describe changes in HSRB medical and performance risks.

Caroline R Austin↗

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗

The measurement and analysis of leaf spectral reflectance of two stands of loblolly pine populations

My research was conducted under the mentorship of Dr. Jeff Luvall. I worked at Marshall from June 1 through August 6, 1993. My proposal is titled 'The Measurement and Analysis of Leaf Spectral Reflectance of Two Stands of Loblolly Pine Populations.' The populations for this study were chosen from a larger population of 31 families managed by the International Forest Seed Company, Odenville, Alabama. The technology for mobile ground base spectral detecting is new and therefore the majority of time, June 2 through July 9, was spent on learning the techniques of the Spectrometer 2 spectroradiometer used in the gathering of spectra information. The activities included in the learning process were as follows: calibration of the equipment, programming the associated computer for data management, operation of the spectral devices, and input and output of data. From July 12 through August 3 the time was spent on learning the 'STATGRAP' computer software. This software will be used in the analysis of the data retrieved by the Spectrometer 2 spectroradiometer. Dr. Greg Carter, at Stennis, a colleague of Dr. Luvall, has been conducting similar work with different instruments and procedures and has agreed to host us for a training session on data gathering and analysis. This visit, which has previously planned for July 9, 1993, but had to be postponed because of schedule conflicts, is now confirmed for August 18-22, 1993. This trip to Stennis will provide the knowledge for conducting the field operations in my study, i.e., gathering of data and file conversions.

Paul, Anthony D.↗

Towards Automated Assessment of Vulnerability Exposures in Security Operations

Current approaches for risk analysis of software vulnerabilities using manual assessment and numeric scoring do not complete fast enough to keep pace with the maintenance work rate to patch and mitigate the vulnerabilities. This paper proposes a new approach to modeling software vulnerability risk in the context of the network environment and firewall configuration. In the approach, vulnerability features are automatically matched up with networking, target asset, and adversary features to determine whether adversaries can exploit a vulnerability. The ability of adversaries to reach a vulnerability is modeled by automatically identifying the network services associated with vulnerabilities through a pipeline of machine learning and natural language processing and automatically analyzing network reachability. Our results show that the pipeline can identify network services accurately. We also find that only a small number of vulnerabilities pose real risks to a system. However, if left unmitigated, adversarial reach to vulnerabilities may extend to nullify the effect of firewall countermeasures.

Huff, Philip↗

Neurocomputing

The present work is intended to give technologists, research scientists, and mathematicians a graduate-level overview of the field of neurocomputing. After exploring the relationship of this field to general neuroscience, attention is given to neural network building blocks, the self-adaptation equations of learning laws, the data-transformation structures of associative networks, and the multilayer data-transformation structures of mapping networks. Also treated are the neurocomputing frontiers of spatiotemporal, stochastic, and hierarchical networks, 'neurosoftware', the creation of neural network-based computers, and neurocomputing applications in sensor processing, control, and data analysis.

Hecht-Nielsen, Robert↗

Developing a space network interface simulator: The NTS approach

This paper describes the approach used to redevelop the Network Control Center (NCC) Test System (NTS), a hardware and software facility designed to make testing of the NCC Data System (NCCDS) software efficient, effective, and as rigorous as possible prior to operational use. The NTS transmits and receives network message traffic in real-time. Data transfer rates and message content are strictly controlled and are identical to that of the operational systems. NTS minimizes the need for costly and time-consuming testing with the actual external entities (e.g., the Hubble Space Telescope (HST) Payload Operations Control Center (POCC) and the White Sands Ground Terminal). Discussed are activities associated with the development of the NTS, lessons learned throughout the project's lifecycle, and resulting productivity and quality increases.

Hendrzak, Gary E.↗

X-29 flight control system: Lessons learned

Two X-29A aircraft were flown at the NASA Dryden Flight Research Center over a period of eight years. The airplanes' unique features are the forward-swept wing, variable incidence close-coupled canard and highly relaxed longitudinal static stability (up to 35-percent negative static margin at subsonic conditions). This paper describes the primary flight control system and significant modifications made to this system, flight test techniques used during envelope expansion, and results for the low- and high-angle-of-attack programs. Through out the paper, lessons learned will be discussed to illustrate the problems associated with the implementation of complex flight control systems.

Clarke, Robert↗

Classification of asteroid spectra using a neural network

The 52-color asteroid survey (Bell et al., 1988) together with the 8-color asteroid survey (Zellner et al., 1985) provide a data set of asteroid spectra spanning 0.3-2.5 micrometers. An artificial neural network clusters these asteroid spectra based on their similarity to each other. We have also trained the neural network with a categorization learning output layer in a supervised mode to associate the established clusters with taxonomic classes. Results of our classification agree with Tholen's classification based on the 8-color data alone. When extending the spectral range using the 52-color survey data, we find that some modification of the Tholen classes is indicated to produce a cleaner, self-consistent set of taxonomic classes. After supervised training using our modified classes, the network correctly classifies both the training examples, and additional spectra into the correct class with an average of 90% accuracy. Our classification supports the separation of the K class from the S class, as suggested by Bell et al. (1987), based on the near-infrared spectrum. We define two end-member subclasses which seem to have compositional significance within the S class: the So class, which is olivine-rich and red, and the Sp class, which is pyroxene-rich and less red. The remaining S-class asteroids have intermediate compositions of both olivine and pyroxene and moderately red continua. The network clustering suggests some additional structure within the E-, M-, and P-class asteroids, even in the absence of albedo information, which is the only discriminant between these in the Tholen classification. New relationships are seen between the C class and related G, B, and F classes. However, in both cases, the number of spectra is too small to interpret or determine the significance of these separations.

Howell, E. S.↗

Single-stage-to-orbit: Meeting the challenge

There has been and continues to be significant discussion about the viability of fully reusable, single-stage-to-orbit (SSTO) concepts for delivery of payloads to orbit. Often, these discussions have focused in detail on performance and technology requirements relating to the technical feasibility of the concept, with only broad generalizations on how the SSTO will achieve its economic goals of greatly reduced vehicle ground and flight operations costs. With the current industry and NASA Reusable Launch Vehicle Technology Program efforts underway to mature and demonstrate technologies leading to a viable commercial launch system that also satisfies national needs, achieving acceptable recurring costs becomes a significant challenge. This paper reviews the current status of the Reusable Launch Vehicle Technology Program including the DC-XA, X-33, and X-34 flight systems and associated technology programs. The paper also examines lessons learned from the recently completed DC-X reusable rocket demonstrator program. It examines how these technologies and flight systems address the technical and operability challenges of SSTO whose solutions are necessary to reduce costs. The paper also discusses the management and operational approaches that address the challenge of a new cost-effective, reusable launch vehicle system.

Freeman, Delma C., Jr.↗

On the nature and evolution of the neural bases of human language

The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on the brains of human beings and other species provides insight into the evolution of the brain bases of human language. The neural substrate that regulated motor control in the common ancestor of apes and humans most likely was modified to enhance cognitive and linguistic ability. Speech communication played a central role in this process. However, the process that ultimately resulted in the human brain may have started when our earliest hominid ancestors began to walk.

Review, Tutorial↗

Lunar Surface Operations: Surface Duration - Part 2

The objectives of this slide presentation are to review the activities on the lunar surface during the stay. The objectives include (1) Summarize Lunar Module Basics emphasizing module layout and storage. (2) Identify the primary activities occurring during each of the lunar s urface timelines, (3) List the EVA Prep tasks, (4) Identify the EVA Objectives, (5) Identify the activities associated with Post EVA (6) Describe the lessons learned during both EVA and Non EVA activities. Included are overview drawings of the Lunar Roving Vehicle, pictures of the tools, and sample return containers. There are also time lines for the Apollo 11, and Apollo 12 through 14, Apollo 15, Apollo 16 and Apollo 17. Diagrams of the EVA suits are shown, including the Liquid Cooling Garment, and the Pressure Garment Assembly. The activity prior to the EVA are reviewed. The science mission assignments of each mission are viewed. The activities after the EVA are reviewed

Interbartolo, Michael↗

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Ambrose, Robert↗