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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 NTRSDate not supplied

Biosynthesized Thermoplastic/Regolith Composites for Closed-Loop In-Space Manufacturing

In-Space Manufacturing (ISM) is vital to supporting a sustained human presence on the Moon or Mars. With payload launch prices ranging from $4,000 to more than $1 million per kg, reducing payload mass is of critical interest. Using in-situ resources for ISM is particularly attractive as it allows for a system of Earth-independent manufacturing for the Lunar surface, reducing the initial payload mass that is required for current ISM systems that rely on terrestrially synthesized materials. This talk presents new composite materials made from Lunar and Martian regolith and Poly(3-hydroxybutyrate) (PHB), a thermoplastic that offers the ability to be biosynthesized in space using various in-situ resources like organic waste or atmospheric CO2 as feedstock. The addition of regolith provides a route to creating materials with a diverse set of properties which will be discussed. The development of these materials represents the first step in creating a system of closed-loop ISM, which is critical to establishing a lasting human presence in space.

In situ resource utilization↗

NASA NTRS2026

Development of a One-Domain Volume-Averaged Navier–Stokes Solver

The interaction between a high-enthalpy flow and a thermal protection material is inherently multiscale and multiphysics. In conventional aerothermal analyses, the external flow and material response are generally modeled using separate computational domains coupled through boundary conditions at the material surface. Although this approach has supported many practical applications, it requires assumptions about the location and behavior of the interface and may become difficult to apply when material decomposition, internal reactions, and surface recession substantially alter the porous structure. This report presents the development of a one-domain formulation in which the free-fluid and porous-material regions are represented within a single computational domain. The formulation is based on the volume-averaged Navier–Stokes (VANS) equations, derived from the governing equations for reacting, compressible flow and condensed material. Volume averaging transfers the influence of the unresolved material microstructure to the macroscale equations through effective transport properties, interfacial source terms, and dispersion fluxes. Particular attention is given to regions in which porosity and permeability vary rapidly, including the diffuse transition between a porous material and the surrounding fluid. The resulting equations are implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO). The report describes the pressure–velocity coupling strategy used by the solver, examines spatial filtering techniques for deriving effective properties, and evaluates the influence of a smoothly varying interface permeability. Numerical demonstrations include canonical porous-flow configurations, a flow-tube configuration representative of FiberForm® permeability experiments, and the oxidation of a porous carbon material. The purpose of this work is to establish a mathematical and computational foundation for a unified treatment of flow and thermal protection material response. The present formulation is intended to support the progressive inclusion of additional physical processes, including multicomponent transport, finite-rate gas–surface chemistry, pyrolysis, internal oxidation, and material recession. It also provides a framework for connecting pore-scale simulations and microstructural characterization with macroscale aerothermal-response calculations. This report is intended for researchers and engineers working in computational fluid dynamics, porous-media transport, material response, and thermal protection system modeling. It documents both the theoretical development and the initial numerical assessment of the one-domain approach, while identifying the closure of effective and dispersion terms as an important subject for continued investigation.

Ablation↗

NASA NTRSDate not supplied

Polymer/Regolith Composites for In-Space Manufacturing on the Moon and Mars

In-situ resource utilization↗

NASA NTRS1992

Proper battery system design for GAS experiments

The purpose of this paper is to help the GAS experimenter to design a battery system that meets mission success requirements while at the same time reducing the hazards associated with the battery system. Lead-acid, silver-zinc and alkaline chemistry batteries will be discussed. Lithium batteries will be briefly discussed with emphasis on back-up power supply capabilities. The hazards associated with different battery configurations will be discussed along with the controls necessary to make the battery system two-fault tolerant.

Calogero, Stephen A.↗

NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗

NASA NTRS2026

Computational Materials for Qualification and Certification (CM4QC) Strategy Document: Maturation of Computational Materials Methods for Aviation-Focused Qualification and Certification of Metal Additive Manufacturing (as an Example of Process-Intensive Materials)

Although considerable scientific and technological advances have been made in recent years in additive manufacturing (AM) processes, these advances have not translated into significant market penetration of AM parts within the aviation industry. It is broadly acknowledged that using traditional qualification and certification (Q&C) approaches for AM components is one of the most significant barriers to broader adoption of AM, resulting in high costs, long product development and certification timelines, and complex design iterations during the product development cycle. A new approach is urgently needed. This document lays out a vision for a new Q&C paradigm with increased use of computational materials (CM) methods aimed at decreasing the time and cost of Q&C of process-intensive material (PIM) approaches in the aviation industry, with AM as the immediate use case. This vision was developed with substantial input from industry, regulatory agencies, government research organizations, and academia.

Edward H Glaessgen↗

NASA NTRS1991

The 1990 NASA Aerospace Battery Workshop

This document contains the proceedings of the 21st annual NASA Aerospace Battery Workshop, hosted by the Marshall Space Flight Center on December 4-6, 1990. The workshop was attended by scientists and engineers from various agencies of the U.S. Government, aerospace contractors, and battery manufacturers as well as participation in like kind from the European Space Agency member nations. The subjects covered included nickel-cadmium, nickel-hydrogen, silver-zinc, lithium based chemistries, and advanced technologies as they relate to high reliability operations in aerospace applications.

Lewis M Kennedy↗

NASA NTRSDate not supplied

Evaluating Crystallinity in Thermoplastic Composites for Aerospace Applications

Polymer matrix composites (PMCs) offer many benefits for the aerospace industry due to their potential for weight reduction when compared to metal or ceramic based materials. Most PMCs currently in flight use thermoset matrices, however, thermoplastic resins are being explored as alternatives due to their ability to be remelted, which is of particular interest due to the potential for in-situ repair and faster production. Most thermoplastic resins are semicrystalline polymers. The properties of semicrystalline thermoplastics are directly influenced by their crystallinity, which can vary due to many factors including thermal treatments, environmental conditions, and mechanical deformation. Within thermoplastic PMC parts, crystallinity gradients can arise due to variations in part geometry, across part thicknesses, and along bonded joints. Monitoring the crystallinity of thermoplastic composites is key to ensuring these materials meet the high demands required for aerospace. Several different analytical techniques exist that can be used to characterize the bulk crystallinity of thermoplastic materials. However, many existing methods lack the specificity required to identify the subtle variations in crystallinity that may play a significant role in the performance and durability of PMC parts. Because of this, a significant amount of work is still required to fully characterize and understand the crystallinity profiles of thermoplastic PMCs and the resulting impact to material properties. This talk discusses the use of multiple techniques such as Differential Scanning Calorimetry, Polarized Light Optical Microscopy, and Fourier-Transform Infrared Spectroscopy to characterize the crystallinity in carbon fiber/thermoplastic composites. Samples of different crystallinity profiles were manufactured using various cooling procedures. This work aims to provide the fundamental data necessary to understand the effects of crystallinity on thermoplastic PMCs, which is key to advancing their use in aerospace applications.

Thermoplastics↗

NASA NTRSDate not supplied

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗

NASA NTRS2022

Exploration of an Adaptive Routine for Battery Modeling

The purpose of this document is to explore the use of adaptive routines in battery modeling. The adaptive routines consist of real-time state estimators combined with battery parameter model components that are adjusted in real-time as battery data becomes available. Several aspects are explored. It is shown that model parameter identification is possible for simple battery models using available input/output data measurements. The online system identification used is recursive least squares. Model identification may be combined with a state observer such as the extended Kalman filter or the unscented Kalman filter to form an adaptive model combined with state estimation. However, such a combination is found to be problematic due to uncertainty, observability and stability issues. This paper is organized as follows. Section 1 introduces adaptive routines and possible roles they play in battery modeling. In Section 2 real-time parameter identification is described with results based on battery data. Section 3 reviews various state estimators and results using a simple battery model. In Section 4 parameter identification and state estimation are combined to form an adaptive routine. Finally, in Section 5 conclusions are drawn and future work is suggested.

Adaptive↗

NASA NTRS1991

Bipolar lead acid battery development

A modular bipolar battery configuration is under development at Johnson Control, Inc. (JCI) and the Jet Propulsion Laboratory (JPL). The battery design, incorporating proven lead acid electrochemistry, yields a rechargeable, high-power source that is light weight and compact. This configuration offers advantages in power capability, weight, and volume over conventional monopolar batteries and other battery chemistries. The lead acid bipolar battery operates in a sealed, maintenance-free mode allowing for maximum application flexibility. It is ideal for high-voltage and high-power applications.

Eskra, Michael↗

NASA NTRS2014

Crewed Space Vehicle Battery Safety Requirements

This requirements document is applicable to all batteries on crewed spacecraft, including vehicle, payload, and crew equipment batteries. It defines the specific provisions required to design a battery that is safe for ground personnel and crew members to handle and/or operate during all applicable phases of crewed missions, safe for use in the enclosed environment of a crewed space vehicle, and safe for use in launch vehicles, as well as in unpressurized spaces adjacent to the habitable portion of a space vehicle. The required provisions encompass hazard controls, design evaluation, and verification. The extent of the hazard controls and verification required depends on the applicability and credibility of the hazard to the specific battery design and applicable missions under review. Evaluation of the design and verification program results shall be completed prior to certification for flight and ground operations. This requirements document is geared toward the designers of battery systems to be used in crewed vehicles, crew equipment, crew suits, or batteries to be used in crewed vehicle systems and payloads (or experiments). This requirements document also applies to ground handling and testing of flight batteries. Specific design and verification requirements for a battery are dependent upon the battery chemistry, capacity, complexity, charging, environment, and application. The variety of battery chemistries available, combined with the variety of battery-powered applications, results in each battery application having specific, unique requirements pertinent to the specific battery application. However, there are basic requirements for all battery designs and applications, which are listed in section 4. Section 5 includes a description of hazards and controls and also includes requirements.

Jeevarajan, Judith A.↗

NASA NTRS1975

Planets and Satellites of the Outer Solar System, Asteroids, and Comets

The cosmogenic significance of outer solar system objects is evaluated with emphasis on planets and larger satellites of greatest biological interest; comets, asteroids, and the smaller satellites are also discussed. Principal physical and rudimentary photometric data for the five outer planets are presented in tables. Sufficient information on planetary motions is included for most calculations in physical planetology.

Ray L Newburn, Jr↗

NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗

NASA NTRS1999

1998 Research and Technology

This report selectively summarizes the NASA Lewis Research Center's research and technology accomplishments for the fiscal year 1998. It comprises 134 short articles submitted by the staff scientists and engineers. The report is organized into five major sections: Aeronautics, Research and Technology, Space, Engineering and Technical Services, and Commercial Technology. A table of contents and an author index have been developed to assist readers in finding articles of special interest. This report is not intended to he a comprehensive summary of all the research and technology work done over the past fiscal year. Most of the work is reported in Lewis-published technical reports, journal articles, and presentations prepared by Lewis staff and contractors. In addition, university grants have enabled faculty members and graduate students to engage in sponsored research that is reported at technical meetings or in journal articles. For each article in this report, a Lewis contact person has been identified, and where possible, reference documents are listed so that additional information can be easily obtained. The diversity of topics attests to the breadth of research and technology being pursued and to the skill mix of the staff that makes it possible. At the time of publication, NASA Lewis was undergoing a name change to the NASA John H. Glenn Research Center at Lewis Field.

Donald J Campbell↗

NASA NTRS2020

Evidence for Multiple Diagenetic Episodes in Ancient Fluvial‐Lacustrine Sedimentary Rocks in Gale Crater, Mars

The Curiosity rover's exploration of rocks and soils in Gale crater has provided diverse geochemical and mineralogical data sets, underscoring the complex geological history of the region. We report the crystalline, clay mineral, and amorphous phase distributions of four Gale crater rocks from an 80‐m stratigraphic interval. The mineralogy of the four samples is strongly influenced by aqueous alteration processes, including variations in water chemistries, redox, pH, and temperature. Localized hydrothermal events are evidenced by gray hematite and maturation of amorphous SiO 2 to opal‐CT. Low‐temperature diagenetic events are associated with fluctuating lake levels, evaporative events, and ground water infiltration. Among all mudstones analyzed in Gale crater, the diversity in diagenetic processes is primarily captured by the mineralogy and X‐ray amorphous chemistry of the drilled rocks. Variations indicate a transition from magnetite to hematite and an increase in matrix‐associated sulfates suggesting intensifying influence from oxic, diagenetic fluids up section. Furthermore, diagenetic fluid pathways are shown to be strongly affected by unconformities and sedimentary transitions, as evidenced by the intensity of alteration inferred from the mineralogy of sediments sampled adjacent to stratigraphic contacts.

C N Achilles↗

NASA NTRS2003

Dissociation and Recombination Effects on the Performance of Pulse Detonation Engines

This paper summarizes major theoretical results for pulse detonation engine performance taking into account real gas chemistry, as well as significant performance differences resulting from the presence of ram and compression heating. An unsteady CFD analysis, as well as a thermodynamic cycle analysis, was conducted in order to determine the actual and the ideal performance for an air-breathing pulse detonation engine (PDE) using either a hydrogen-air or ethylene-air mixture over a flight Mach number range from 0 to 4. The results clearly elucidate the competitive regime of PDE application relative to ramjets and gas turbines.

Povinelli, Louis A.↗

NASA NTRS1983

Modeling a Li/SOCl2 battery for design purposes

A generalized code applicable to many different electrochemical systems and geometric designs is discussed. The code is to be set up so that physical property data such as thermal conductivity, viscosity, density, and configuration (e.g. physical dimensions) are the input data. Thus, by changing these parameters many different battery configurations can be handled. The outputs, as a function of time and space, are voltage, current, temperature, pressure, velocity, and species concentration.

Ernst, D. W.↗