Search NASA⌕ Search

SEARCH · Search NASA

Results for “STEAM GENERATORS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

722 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗
NASA NTRS1963

The Development of A Heated-Hybrid Generated Gas Pressurization System for Propellant Tanks

One of the most important considerations in the design of liquid fueled rockets is the method utilized to transfer the propellants from the propellant tanks to the rocket engine. Use of storable liquid propellant propulsion systems, particularly those employing hydrazine as a fuel, facilitates the attractive possibility of employing the monopropellant virtues of the fuel in order to generate gases for pressurization of the propellant tanks.

GAS PRESSURE↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
NASA NTRS1965

Computation of Optimal Interplanetary Low-Thrust Trajectories With Bounded Thrust Magnitude By Means of the Generalized Newton-Raphson Method

The generalized Newton-Raphson method, an iterative procedure for solving nonlinear operator equations, has been extended in application to variational problems with bounded control variables. A minimum fuel interplanetary low thrust orbital transfer problem is worked out in detail to demonstrate the practical aspects of the algorithm as well as its computational effectiveness. The control variables are the thrust magnitude, limited from zero to some prescribed maximum value, and the thrust steering angle.

Computation↗
DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗
NASA NTRS1963

Propulsion and Power Generation

This document comprises material presented during one session of the Manned Planetary Mission Technology Conference, Lewis Research Center, May 21, 22, and 23, 1963. In order to expedite release to the conferees, the papers are being published with minimum editing and retyping of the original manuscripts. Thus the usual NASA format and style have been compromised. The purpose of the conference was to explore the possibilities and problems of manned planetary space flight. The results and contemplations of the individual papers should in no sense be regarded as a part of NASA plans and programs.

F L Williams↗
DOE OSTI2026

Justification that the Thermo-Fisher Scientific 241 Am Residues Were Generated by Atomic Energy Defense Activities

The Waste Isolation Pilot Plant (WIPP) Land Withdrawal Act (LWA) as amended by the National Defense Authorization Act for Fiscal Year 1997 (1) requires that for Transuranic (TRU) waste to be eligible for disposal at WIPP, it must have been generated by atomic energy defense activities. The definition of “atomic energy defense activity” is defined in the Nuclear Waste Policy Act of 1982 (NWPA) (2).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Advancing the Oxygen Generation Assembly Design to Increase Reliability and Reduce Costs for a Future Long Duration Mission

The state-of-the-art Oxygen Generation Assembly (OGA) has been reliably producing breathing oxygen for the crew aboard the International Space Station (ISS) for over eight years. Lessons learned from operating the ISS OGA have led to proposing incremental improvements to advance the baseline design for use in a future long duration mission. These improvements are intended to reduce system weight, crew maintenance time and resupply mass from Earth while increasing reliability. The proposed improvements include replacing the cell stack membrane material, deleting the nitrogen purge equipment, replacing the hydrogen sensors, deleting the wastewater interface, replacing the hydrogen dome and redesigning the cell stack power supply. The development work to date will be discussed and forward work will be outlined. Additionally, a redesigned system architecture will be proposed.

Kevin C Takada↗
DOE OSTI2026

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗
DOE OSTI2024

Gyromagnetic nonlinear transmission line for radio frequency signal generation and pulse compression

Disclosed are non-linear transmission lines using ferromagnetic materials to generate ferromagnetic resonance oscillations. In one aspect, a non-linear transmission line apparatus is disclosed. The apparatus includes an outer conductor having a first side and a second internally facing side, and an inner conductor positioned internal to the non-linear transmission line apparatus. The apparatus further includes a ferromagnetic material surrounding the inner conductor, wherein the ferromagnetic material comprises nanoparticles of an ε-polymorph of iron oxide expressed as ε-Fe2O3. The apparatus also includes a first dielectric material positioned between the outer conductor and the inner conductor, the dielectric material in contact with both the ferromagnetic material and with the second internally facing side of the outer conductor, wherein the outer conductor, the inner conductor, the dielectric material and the ferromagnetic material form the nonlinear transmission line.

Schneider, Joseph Devin↗
DOE OSTI2024

Integrated optical frequency division for microwave and mmWave generation

Abstract The generation of ultra-low-noise microwave and mmWave in miniaturized, chip-based platforms can transform communication, radar and sensing systems 1–3 . Optical frequency division that leverages optical references and optical frequency combs has emerged as a powerful technique to generate microwaves with superior spectral purity than any other approaches 4–7 . Here we demonstrate a miniaturized optical frequency division system that can potentially transfer the approach to a complementary metal-oxide-semiconductor-compatible integrated photonic platform. Phase stability is provided by a large mode volume, planar-waveguide-based optical reference coil cavity 8,9 and is divided down from optical to mmWave frequency by using soliton microcombs generated in a waveguide-coupled microresonator 10–12 . Besides achieving record-low phase noise for integrated photonic mmWave oscillators, these devices can be heterogeneously integrated with semiconductor lasers, amplifiers and photodiodes, holding the potential of large-volume, low-cost manufacturing for fundamental and mass-market applications 13 .

Science & Technology - Other Topics↗
DOE OSTI2026

Fire Protection Design

The purpose of this project is to design the demolition and installation of a deluge valve swap from a DV-5 to a DV-5A valve.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

Control of an Axisymmetric Jet Using Vortex Generators

The results of an experimental investigation on the effect of vortex generators, in the form of small tabs at the nozzle exit on the evolution of a jet, are reported in this paper. Primarily tabs of triangular shape are considered, and the effect is studied up to a jet Mach number of 1.8. Each tab is found to produce a dominant pair of counter-rotating streamwise vortices having a sense of rotation opposite to that expected from the wrapping of the boundary layer. This results in an inward indentation of the mixing layer into the core of the jet. A triangular-shaped tab with its apex leaning downstream, referred to as a delta tab, is found to be the most effective in producing such vortices, with a consequential large influence on the overall jet evolution. Two delta tabs, spaced 180 deg apart, completely bifurcate the jet. Four delta tabs stretch the mixing layer into four 'fingers,' resulting in a significant increase in the jet mixing downstream. For six delta tabs the mixing layer distortion settles back to a three finger configuration through an interaction of the streamwise vortices. The tabs are found to be equally effective in jets with turbulent or laminar initial boundary layers. Two sources of streamwise vorticity are postulated for the flow under consideration. One is the upstream 'pressure hill,' generated by the tab, which constitutes the main contributor of vorticity to the dominant pair. Another is due to vortex filaments shed from the sides of the tab and reoriented downstream by the mean shear of the mixing layer. Depending on the orientation of the tab, the latter source can produce a vortex pair having a sense of rotation opposite to that of the dominant pair. In the case of the delta tab, vorticity from the two sources add, explaining the strong effect in that configuration.

Streamwise Vorticity↗
DOE OSTI2026

Nitrene generation and transfer for unnatural biosynthesis in living cells

Abstract Synthetic biology has enabled the production of natural and unnatural products from inexpensive sustainable feedstocks. Yet, the scope of available products has been limited largely to compounds accessible from nature’s chemical reactions. Evolved enzymes can catalyse reactions of unnatural substrates or reactions not found in nature but often require the addition of synthetic reagents to purified enzymes or to resting cells containing those enzymes. Here we show that chemical reactions of metabolic intermediates produced intracellularly in living cells can include intermolecular nitrene transfers. The biosynthesis of N -acetoxyanilines, in combination with the generation and transfer of N -aryl nitrene intermediates from them catalysed by a cytochrome P450, generates amino alcohols, diamines, diarylamines and aminoalkyl arenes from simple carbon feedstocks. These products—common substructures of pharmaceuticals and agrochemicals—are challenging to synthesize by standard organic chemistry and were produced from inexpensive, renewable feedstocks. Evolution of the enzymes in this pathway showed that titres can be increased by engineering and that the products can be synthesized with high enantioselectivity.

Donnell, Isaac↗
NASA NTRS1984

Electrodynamic Tethers. 1: Power Generator in LEO. 2: Thrust for Propulsion and Power Storage

An electrodynamic tether consists of a long insulated wire in space whose orbital motion cuts across lines of magnetic flux to produce an induce voltage that in typical low orbits averages about 200 v/km. Such a system should be capable of generating substantial electrical power, at the expense of IXB drag acting on its orbital energy. If a reverse current is driven against the induced voltage, the system should act as a motor producing IXB thrust. A reference system was designed, capable of generating 20 KW of power into an electrical load located anywhere along the wire at the expense of 2.6N (20,000 J/sec) drag on the wire. In an ideal system, the conversion between mechanical and electrical energy would reach 100% efficiency. In the actual system part of the 20 KW is lost to internal resistance of the wire, plasma and ionosphere, while the drag force is increased by residual air drag. The 20 KW PMG system as designed is estimated to provide 18.7 KW net power to the load at total drag loss of 20.4 KJ/sec, or an overall efficiency of 92%. Similar systems using heavier wire appear capable of producing power levels in excess of 1 Megawatt at voltages of 2-4 KV, with conversion efficiency between mechanical and electrical power better than 95%. The hollow cathode based system should be readily reversible from generator to motor operation by driving a reverse current using onboard power.

James E Mccoy↗
NASA NTRSDate not supplied

Americium-Fuelled Radioisotope Stirling Generator Elegant Breadboard

High power solutions for spacecraft are becoming increasingly sought after in the new era of space exploration, with energy intensive in-situ lunar surface exploration becoming a key part of the roadmap for major space agencies, as well as commercial companies. Nuclear power provides the most feasible solution to achieve continued operation through the long lunar night, and in extended periods in Permanently Shadowed Regions (PSRs). Americium-241 (241Am) is used as the fuel of choice in European Radioisotope Power Systems (RPS). The University of Leicester have developed a number of systems using this fuel type, including a 200 Wth heat source. Building on existing international partnerships, the University of Leicester is continuing to work with NASA Glenn Research Center (GRC) to maximise the electrical output that can be generated from the heat source by progressing the radioisotope-Stirling generator concept to elegant breadboard level, building on the long heritage of dynamic power conversion developments at NASA Glenn. Presented in the following conference paper is the next iteration of the Americium-fuelled Radioisotope Stirling Generator (Am-RSG) Elegant Breadboard, following on from a successful technology demonstration design conducted at NASA Glenn in early 2025. The design laid-out in this paper is a more flight-like version of the technology demonstrator, and is intended to pair with the next generation of Stirling convertor technology, the SunPower Robust Stirling Converter (SRSC). The SRSC is able to operate more efficiently at lower thermal power levels than the previous Advanced Stirling Convertor (ASC), making it more suitable for the 241Am system.

Lunar↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗