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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 NTRS1983

Array processor architecture

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

Barnes, George H.↗

NASA NTRS2017

Cryogenic Fluid Management Technology Development Roadmaps

Advancement in Cryogenic Fluid Management (CFM) Technologies is essential for achieving NASA's future long duration missions. Propulsion systems utilizing cryogens are necessary to achieve mission success. Current State Of the Art (SOA) CFM technologies enable cryogenic propellants to be stored for several hours. However, some envisioned mission architectures require cryogens to be stored for two years or longer. The fundamental roles of CFM technologies are long term storage of cryogens, propellant tank pressure control and propellant delivery. In the presence of heat, the cryogens will "boil-off" over time resulting in excessive pressure buildup, off-nominal propellant conditions, and propellant loss. To achieve long term storage and tank pressure control, the CFM elements will intercept and/or remove any heat from the propulsion system. All functions are required to perform both with and without the presence of a gravitational field. Which CFM technologies are required is a function of the cryogens used, mission architecture, vehicle design and propellant tank size. To enable NASA's crewed mission to the Martian surface, a total of seventeen CFM technologies have been identified to support an In-Space Stage and a Lander/Ascent Vehicle. Recognizing that FY2020 includes a Decision Point regarding the In-Space Stage Architecture, a set of CFM Technology Development Roadmaps have been created identifying the current Technology Readiness Level (TRL) of each element, current technology "gaps", and existing technology development efforts. The roadmaps include a methodical approach and schedule to achieve a flight demonstration in FY2023, hence maturing CFM technologies to TRL 7 for infusion into the In-Space Stage Preliminary Design.

Stephens, J. R.↗

DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for UAM Environments

Urban Air Mobility (UAM) has become a focus for the next generation of aerial passenger transportation. UAM operations will be leveraging a service-based architecture for airspace solutions. The UAM environment will leverage diverse communications and system access approaches. These approaches include independent Providers of Services for UAM and supplemental data service providers that exchange data between themselves and UAM operators. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment.

Urban Air Mobility↗

DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗

NASA NTRS1972

Data storage technology: Hardware and software, Appendix B

This project involves the development of more economical ways of integrating and interfacing new storage devices and data processing programs into a computer system. It involves developing interface standards and a software/hardware architecture which will make it possible to develop machine independent devices and programs. These will interface with the machine dependent operating systems of particular computers. The development project will not be to develop the software which would ordinarily be the responsibility of the manufacturer to supply, but to develop the standards with which that software is expected to confirm in providing an interface with the user or storage system.

Sable, J. D.↗

DOE OSTI2024

Hybrid Storage Solution

With the rise of artificial intelligence and machine learning, data sets used to train models have become increasingly large. The availability, accessibility and integrity of large data sets has become important to the research conducted at Los Alamos National Laboratory. Ceph is a storage solution suitable for use with critical data because of its distributed nature and ability to keep multiple copies of a file in different locations. The amount of data means that bandwidth, latency, and cost are important factors and the reason most storage solutions are on-premises. However, there are distinct advantages to hosting services in the cloud, namely scalability and ease-of-use. In this paper, we explore the possibility of provisioning a hybrid Ceph cluster that leverages the benefits of both cloud architectures and on-premise performance.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2000

Ultra-High Density Holographic Memory Module with Solid-State Architecture

NASA's terrestrial. space, and deep-space missions require technology that allows storing. retrieving, and processing a large volume of information. Holographic memory offers high-density data storage with parallel access and high throughput. Several methods exist for data multiplexing based on the fundamental principles of volume hologram selectivity. We recently demonstrated that a spatial (amplitude-phase) encoding of the reference wave (SERW) looks promising as a way to increase the storage density. The SERW hologram offers a method other than traditional methods of selectivity, such as spatial de-correlation between recorded and reconstruction fields, In this report we present the experimental results of the SERW-hologram memory module with solid-state architecture, which is of particular interest for space operations.

Markov, Vladimir B.↗

DOE OSTI2023

Electrical Energy Storage Data Submission Guidelines, Version 3

The knowledge of long-term health and reliability of energy storage systems is still unknown, yet these systems are proliferating and are expected increasingly to assist in the maintenance of grid reliability. Understanding long-term reliability and performance characteristics to the degree of knowledge similar to that of traditional utility assets requires operational data. This guideline is intended to inform numerous stakeholders on what data are needed for given functions, how to prescribe access to those data and the considerations impacting data architecture design, as well as provide these stakeholders insight into the data and data systems necessary to ensure storage can meet growing expectations in a safe and cost-efficient manner. Understanding data needs, the systems required, relevant standards, and user needs early in a project conception aids greatly in ensuring that a project ultimately performs to expectations.

25 ENERGY STORAGE↗

DOE OSTI2020

CO 2 geological storage: Critical insights on plume dynamics and storage efficiency during long-term injection and post-injection periods

In the quest for net-zero greenhouse gas emission, CO 2 capture and storage technologies play a prominent role. Estimates suggest a potential of sequestering up to several thousand metric gigatons of CO 2 . However, some of the main challenges in its development are an assessment of reservoir-specific storage capacities due to variabilities and heterogeneities in the underlying properties (structure, formations, facies, petrophysics, reservoir architecture, and others) and understanding the migration of CO 2 in the subsurface. How much CO 2 can be stored in a reservoir, and how quickly can it be injected? What will be the dominant storing (trapping) mechanisms? These questions, among others, remain as challenges to the commercial deployment of this technology. This article critically investigates CO 2 plume characteristics and determines the evolving contributions of different trapping mechanisms during a 100-year injection period. Here, simulation results on the CO 2 plume dynamics indicate that lateral propagation is much larger than vertical propagation. The ratio of average lateral to vertical dispersion ranged between 6.3 and 18.8 for the cases investigated. On average, for all the scenarios investigated, the free phase (mobile supercritical CO 2 ) is the dominant trapping mechanism (in terms of the amount of CO 2 stored) during the injection period, accounting up to 45% of the CO 2 injected. Both residual (30%) and solubility (25%) trapping storage ratios decline with time during injection, and no significant mineral trapping appeared during the 100-year injection period. However, the behavior of CaCO 3 suggests a predominant dissolution of CaCO 3 , especially in the vicinity of the injection well.

03 NATURAL GAS↗

NASA NTRSDate not supplied

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗

NASA NTRS2018

NASA's Cryogenic Fluid Management Technology Development Roadmaps

The maturation of Cryogenic Fluid Management (CFM) Technologies is essential for achieving NASA's future long duration missions. Propulsion systems utilizing cryogens are necessary to achieve NASA's exploration missions to the moon, Mars, and beyond. Current State Of the Art (SOA) CFM technologies enable cryogenic propellants to be stored for several hours prior to their use. However, some envisioned mission architectures require that cryogens to be stored for two years or longer. The fundamental roles of CFM technologies are long term storage of cryogens, propellant tank pressure control and propellant delivery. In the presence of heat, the cryogens will "boil-off" over time resulting in excessive pressure buildup, off-nominal propellant conditions for engine consumption, and propellant loss. To achieve long term storage and tank pressure control, the CFM elements will intercept and/or remove any heat from the propulsion system. All functions are required to be performed both with and without the presence of a gravitational field. Which CFM technologies are required is a function of the cryogens used, mission architecture, vehicle design and propellant tank size. To enable NASA's crewed missions beyond Low Earth Orbit, a total of twenty-seven CFM technologies have been identified to support various In-Space Stages and Lander/Ascent Vehicles. A set of CFM Technology Development Roadmaps have been created identifying the current Technology Readiness Level (TRL) of each element, current technology "gaps", and existing technology development efforts. The roadmaps include a methodical approach and schedule to achieve a flight demonstration, hence maturing CFM technologies to TRL 6/7 for infusion into the NASA's exploration elements. Additionally, a survey of the aerospace industry was completed to understand their views on the various technologies and how they would be infused. This does not cover all possible technologies, but rather those that are of interest to NASA specifically.

Cryogenic fluid management↗

NASA NTRS2001

Solid-State Power Generating Microdevices for Distributed Space System Architectures

Deep space missions have a strong need for compact, high power density, reliable and long life electrical power generation and storage under extreme temperature conditions. Conventional power generating devices become inefficient at very low temperatures (temperatures lower than 200 K encountered during Mars missions for example) and rechargeable energy storage devices cannot be operated thereby limiting mission duration. At elevated temperatures (for example for planned solar probe or Venus lander missions), thin film interdiffusion destroys electronic devices used for generating and storing power. Solar power generation strongly depends upon the light intensity, which falls rapidly in deep interplanetary missions (beyond 5 AU), and in planetary missions in the sun shadow or in dusty environments (Mars, for example). Radioisotope thermoelectric generators (RTGs) have been successfully used for a number of deep space missions RTGs. However, their energy conversion efficiency and specific power characteristics are quite low, and this technology has been limited to relatively large systems (more than 100 W). The National Aeronautics and Space Administration (NASA) and the Jet Propulsion Laboratory (JPL) have been planning the use of much smaller spacecrafts that will incorporate a variety of microdevices and miniature vehicles such as microdetectors, microsensors, and microrovers. Except for electrochemical batteries and solar cells, there are currently no available miniaturized power sources. Novel technologies that will function reliably over a long duration mission (ten years and over), in harsh environments (temperature, pressure, and atmosphere) must be developed to enable the success of future space missions. It is also expected that such micropower sources could have a wide range of terrestrial applications, in particular when the limited lifetime and environmental limitations of batteries are key factors. Additional information is contained in the original extended abstract.

Fleurial, J.-P.↗

DOE OSTI2021

Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications

Optimization of materials’ performance for specific applications often requires balancing multiple aspects of materials’ functionality. Even for the cases where a generative physical model of material behavior is known and reliable, this often requires search over multidimensional function space to identify low-dimensional manifold corresponding to the required Pareto front. In this work, we introduce the multi-objective Bayesian optimization (MOBO) workflow for the ferroelectric/antiferroelectric performance optimization for memory and energy storage applications based on the numerical solution of the Ginzburg–Landau equation with electrochemical or semiconducting boundary conditions. MOBO is a low computational cost optimization tool for expensive multi-objective functions, where we update posterior surrogate Gaussian process models from prior evaluations and then select future evaluations from maximizing an acquisition function. Using the parameters for a prototype bulk antiferroelectric (PbZrO 3 ), we first develop a physics-driven decision tree of target functions from the loop structures. We further develop a physics-driven MOBO architecture to explore multidimensional parameter space and build Pareto-frontiers by maximizing two target functions jointly—energy storage and loss. This approach allows for rapid initial materials and device parameter selection for a given application and can be further expanded toward the active experiment setting. The associated notebooks provide both the tutorial on MOBO and allow us to reproduce the reported analyses and apply them to other systems (https://github.com/arpanbiswas52/MOBO_AFI_Supplements).

36 MATERIALS SCIENCE↗

NASA NTRS2001

Development of a PMAD System for Flywheel Based Energy Storage System

We will discuss the following: (1) the Flywheel Energy Storage System (FESS) program objective; (2) benefits of flywheels for the International Space Station; (3) the FESS development team; (4) FESS electrical requirements; (5) FESS electrical architecture; and (6) electrical subsystem functionality. The objective of the FESS program is to demonstrate flywheel technologies operating together as a system and having improved performance characteristics over batteries in a low earth orbit energy storage application (such as the ISS).

Wolff, Fred↗

NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

Electrified aircraft propulsion (EAP) research is a priority of the National Aeronautics and Space Administration (NASA) for its potential to increase propulsion system efficiency, performance, and operability at the subsystem and vehicle levels while decreasing emissions. These EAP systems demand more advanced control algorithms due to increased complexity. NASA has developed a reconfigurable, hardware-in-the-loop rig to verify control algorithm performance using a sub-scale electro-mechanical system. A novel capability of this rig is the ability to test full scale EAP control algorithms on a sub-scale representation of the electro-mechanical system without turbomachinery/rotors. A novel feature is the use of a physical energy storage device within the electro-mechanical system. A dual spool, parallel hybrid-electric turbofan architecture and energy management control system is tested with the goal of verifying the ability to obtain turbomachinery model operability benefits while controlling sub-scale electro-mechanical hardware. Pre-test predictions of the turbofan model, control, and rig performance were obtained through simulation using a software model of the rig. Theoretical results showing the true performance of the turbofan model were obtained through a software simulation using full-scale mechanical shaft models. The paper compares theoretical, predicted, and actual test results from the turbofan model, energy management control and rig perspectives. The results show that the presence of sub-scale electro-mechanical hardware did not inhibit the energy management algorithm from achieving turbomachinery operability benefits.

hybrid↗

NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

hybrid↗

NASA NTRS2017

Comparison of Oxygen Liquefaction Methods for Use on the Martian Surface

In order to use oxygen that is produced on the surface of Mars from In-Situ production processes in a chemical propulsion system, the oxygen must first be converted from vapor phase to liquid phase and then stored within the propellant tanks of the propulsions system. There are multiple ways that this can be accomplished, from simply attaching a liquefaction system onto the propellant tanks to carrying separate tanks for liquefaction and storage of the propellant and loading just prior to launch (the way that traditional rocket launches occur on earth). A study was done into these various methods by which the oxygen (and methane) could be liquefied and stored on the Martian surface. Five different architectures or cycles were considered: Tube-on-Tank (also known as Broad Area Cooling or Distributed Refrigeration), Tube-in-Tank (also known as Integrated Refrigeration and Storage), a modified Linde open liquefaction/refrigeration cycle, the direct mounting of a pulse tube cryocooler onto the tank, and an in-line liquefier at ambient pressure. Models of each architecture were developed to give insight into the performance and losses of each of the options. The results were then compared across eight categories: Mass, Power (both input and heat rejection), Operability, Cost, Manufacturability, Reliability, Volumility, and Scalability. The result was that, given the current state of technology maturity, Tube-on-Tank architectures were the most attractive solution, closely followed by Tube-in-Tank. As a result of this technical analysis and other factors, NASA has determined to focus its Martian surface liquefaction activities and technology development on Tube-on-Tank liquefaction cycles.

Cryogenic propellants↗