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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

BioNutrients-3: Precision Fermentation, Pasteurization, and Pathogen Detection - Towards Safe Fermentation and Production of Nutrients in Space

The BioNutrients (BN) project is developing a microbial manufacturing approach to supplement the NASA food system to address known nutrient degradation associated with long-term storage. BN uses synthetic biology to deliver high-value nutrients and therapeutics through genetic engineering of microbes and production of fermented food products like yogurt and kefir, in a fully dehydrated system. On-demand production of nutrients for human consumption requires rigorous safety protocols to ensure contaminants are not introduced during the fermentation process. The third iteration of the BN flight project, BN-3, further develops the BN project by investigating strategies for pathogen detection and pasteurization in microgravity. BN-3 will test the limits of pathogen detection using whole genome sequencing, standard microbial assays and the NASA Ames E-Nose, a volatile carbon nano tube-based sensor array, to detect unwanted microbes. BN-3 also expands on the number of nutrients produced in a single bioreactor to enhance efficiency of the system by combining production of B vitamins in conjunction with the carotenoids, beta-carotene and zeaxanthin. Serial production of food products through yogurt passaging, new updates to the fluorinated ethylene propylene bags to allow crew access via a straw, as well as use of a food safe pH indicator dye to indicate readiness of the food product, will further enhance the useability of this system. This presentation will provide status of the BN-3 flight project with the aim of advancing in-space biomanufacturing for on-demand microbially based food production for future space exploration.

Biomanufacturing↗
NASA NTRSDate not supplied

High Resolution Terrain Sensing Lidar for Precision Navigation and Safe Landing of Space and Aerial Vehicles

A Flash Lidar utilizing a novel Super-Resolution (SR) technique has been developed for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard landing vehicles. Processing algorithms for precision navigation and safe landing location identification take advantage of the uniform fixed pixels property of generated high resolution Digital Elevation Maps (DEMs) to achieve high reliability operation in near real-time. This paper describes the current and next generation breadboard units, report the results of recent dynamic tests, and explain the operational concept as envisioned for future landing missions.

Precision Landing↗
DOE OSTI2024

Safe Operations at Roadway Junctions: Intelligent Roadway Infrastructure as Functional Interlocking

Automated vehicle (AV) technology is quickly maturing, and the corresponding infrastructure systems that evaluate traffic and communicate to vehicles requires sophisticated sensing and perception technologies, referred to as intelligent roadway infrastructure (IRI), to complement emerging AV capabilities. IRI provides signals to vehicles, indicating right-of-way for vehicles and communicating to approaching AVs that no other vehicle is failing to yield. This capability, denoted as safety-affirmative signaling, provides a green light or a green arrow as appropriate and affirms through communication links to connected vehicles when it is safe to proceed. About 36% of collisions occur at intersections, with most occurring upon left turns (22.2%) or crossing over (12.6%), and only a small percentage (1.2%) while turning right at an intersection. Of all intersection crashes about half (52.5%) of those vehicles were traveling through a signalized intersection 2. Safety-affirmative signaling would guarantee safety of AV fleet vehicles, by providing the interlocking principle, a term from automated train control that only allows progression through a railway intersection after affirming no opportunity for a crash exists. IRI through safety-affirmative signaling would bring performance and safety to complex roadway intersections where AV transit fleet service is most needed, as well as safety benefits to traditional, non-automated vehicles and vulnerable road users. The implementation of IRI has functional, programmatic, and technical challenges. Research work performed at the National Renewable Energy Laboratory (NREL) in an integrative approach encapsulating these themes, and termed infrastructure perception and control (IPC) is motivated by improved performance (travel time), improved safety (reduced collisions), and improved energy efficiency (less fuel burned and minimized production of greenhouse gases). IPC is intended not only for roadway and intersection applications but also in extension to inform complementary buildings and grid systems to enable better co-management, as vehicles and their charging needs become increasingly integrated into the built environment. The NREL IPC project presents an open-source framework, architecture, and supporting technology to implement IRI, addressing critical issues such as fusion of data, reliability, standardization of data interfaces, and confidence of detection. The framework is informed by previous experience in U.S. Department of Defense research technology, specifically in the use of radar to detect, identify, and track aerial threats. These principles combined with multi-sensor fusion provides for a complete digital twin with known and measurable confidence and accuracy from which safety-affirmative signaling can be developed and deployed.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2024

Digital Twinning and Predictive Modeling of Traffic for Safe, Efficient, and Reliable Intersections

Over the last decade, the advances in connected and autonomous vehicles (CAVs) have far surpassed the technological realm of transportation infrastructure. There is a growing need to have a technologically commensurate transportation infrastructure to enable safe and reliable movement of goods and people. The recent creation of Advanced Research Projects Agency - Infrastructure (ARPA-I) through the Infrastructure Investment and Jobs Act by the U.S. Department of Transportation (USDOT) has further amplified the need to revolutionize the transportation infrastructure system in the US. This need is perhaps felt most at traffic intersections, as more than 50 percent of the combined total of fatal and injury crashes occur at or near intersections. The proposed concept of Infrastructure Perception and Control (IPC) is aimed at bridging this technological gap by building a real-time digital twin of traffic by fusing detections from sensors installed at the intersection. This digital twin can then empower a wide variety of applications such as smart traffic signals or infrastructure-to-everything (I2X) communications. Smart signaling can help avoid crashes through early-prediction, while I2X can augment the CAV sensors under uncertain driving conditions and provide connected vehicles (CVs) with traffic information they can use to optimize their travel.

connected vehicles↗
DOE OSTI2025

Ensuring Safe, Effective, and Reliable Use of Artificial Intelligence-Based Applications for Nuclear Electricity Generation through a Systems Approach

There is a significant potential to reduce operating and maintenance cost at nuclear power plants using artificial intelligence (AI) and machine learning (ML). For instance, AI/ML has the potential to significant improve work management processes, condition reporting, and plant surveillance activities. However, the nuclear industry has been slow in adopting AI/ML due to several multifaceted barriers discussed in this paper. This work presents such multidisciplinary approach intended to 1) accelerate industry adoption of AI/ML-based applications at nuclear power plants and 2) ensure their safe, reliable, and effective use. This approach is discussed further in this work and will be used to address overarching challenges associated with AI deployment at scale to provide industry guidance that support accelerated adoption of AI/ML technologies throughout the industry.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

A safe reinforcement learning algorithm for supervisory control of power plants

Traditional control theory-based methods require tailored engineering for each system and constant fine-tuning. In power plant control, one often needs to obtain a precise representation of the system dynamics and carefully design the control scheme accordingly. Model-free Reinforcement learning (RL) has emerged as a promising solution for control tasks due to its ability to learn from trial-and-error interactions with the environment. It eliminates the need for explicitly modeling the environment’s dynamics, which is potentially inaccurate. However, the direct imposition of state constraints in power plant control raises challenges for standard RL methods. To address this, we propose a chance-constrained RL algorithm based on Proximal Policy Optimization for supervisory control. Our method employs Lagrangian relaxation to convert the constrained optimization problem into an unconstrained objective, where trainable Lagrange multipliers enforce the state constraints. In conclusion, our approach achieves the smallest distance of violation and violation rate in a load-follow maneuver for an advanced Nuclear Power Plant design.

constrained optimization↗
DOE OSTI2025

Levelized cost and carbon intensity of solar hydrogen production via water splitting using a scalable and intrinsically safe photocatalytic Z-scheme raceway system

Generating hydrogen from local energy resources such as solar or wind would unlock a low-carbon energy carrier that could be used to reduce greenhouse gas emissions in sectors such as industry and transportation. Yet, the allocation of new or existing power generation solely to hydrogen production remains contentious due to disputes regarding emissions accounting. Photocatalytic (PC) hydrogen production technologies offer a unique solution, as hydrogen is produced directly from solar energy and water, without the need for electricity generation. However, cost projections for all photocatalytic designs to date have suggested that they are not cost competitive compared to conventional electrolysis systems manufactured at scale. Herein, we offer the first illustrative benchmark of cost and carbon intensity of hydrogen produced in a type 2 “Z-scheme” photocatalytic reactor design, which employs suspended semiconducting nanoconductor particles organized into two stacked volumes in a raceway design. The “Z-scheme” system utilizes two separate photoabsorber particles, tuned to drive either the hydrogen evolution reaction or the oxygen evolution reaction individually, connected via a reversible, charge transfer redox couple in solution. Furthermore, the results suggest a highly competitive and scalable technology, that justifies further experimental validation and prototyping in the field.

Carbon↗
NASA NTRS2001

Lidar-based hazard avoidance for safe landing on Mars

This paper describes the algorithms and the models that comprise a scanning lidar-based hazard avoidance simulation including a terrain generator, a lidar model, hazard avoidance algorithms and powered landing guidance algorithms.

hazard↗