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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Life-Limiting Factors of the CMTS for Precision Pointing Observatory Missions

Development of the next generation Colloid Micronewton Thruster System (CMTS) has focused on incorporation of complete redundancy, and extension of life beyond the 3,458 hrs previously demonstrated to the >40,000 hrs necessary for future missions. The present life- limiting factor of the CMTS is impingement of the electrospray beam onto the electrostatic grids, which is mitigated by the use of porous grid structures to adsorb and trap the small fraction (typically <0.5%) of the beam that intercepts the grids. A detailed alignment survey using a single emitter electrospray source has been performed in order to establish thruster production requirements and produce data necessary for lifetime model validation. Capillary emitter tilt (Θ), lateral displacement (X), and source spacing (Z), where independently assessed for their impact on changes in grid interception, as well as combined lateral and tilt displacement. Throughout testing, incremental improvements were made to reduce facility effects that impacted measured results. The data validate the alignment tolerances used in design and fabrication of the CMTS. Increased interception was not observed until emitter tilt exceeded 3X, lateral misalignment exceeded 5X, and emitter spacing >1.5X tolerance requirements. Results also indicate that, at target grid impingement levels <0.5%, facility effects begin to dominate measured grid currents and must be mitigated for more accurate assessments of thruster life.

Ziemer, John K.↗
NASA NTRS2012

Experimental Behavior of Sulfur Under Primitive Planetary Differentiation Processes, the Sulfide Formations in Enstatite Meteorites and Implications for Mercury.

Enstatite meteorites are the most reduced naturally-occuring materials of the solar system. The cubic monosulfide series with the general formula (Mg,Mn,Ca,Fe)S are common phases in these meteorite groups. The importance of such minerals, their formation, composition and textural relationships for understanding the genesis of enstatite chondrites (EC) and aubrites, has long been recognized (e.g. [1]). However, the mechanisms of formation of these sulfides is still not well constrained certainly because of possible multiple ways to produce them. We propose to simulate different models of formation in order to check their mineralogical, chemical and textural relevancies. The solubility of sulfur in silicate melts is of primary interest for planetary mantles, particularly for the Earth and Mercury. Indeed, these two planets could have formed, at least partly, from EC materials (e.g. [2, 3, 4]). The sulfur content in silicate melts depends on the melt composition but also on pressure (P), temperature (T) and oxygen fugacity fO2. Unfortunately, there is no model of general validity in a wide range of P-T-fO2-composition which describes precisely the evolution of sulfur content in silicate melts, even if the main trends are now known. The second goal of this study is to constrain the sulfur content in silicate melts under reducing conditions and different temperatures.

Malavergne, V.↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
NASA NTRS2020

Building a standardized Observing System Simulation Experiment (OSSE) framework for Mars

We advocate that the Decadal Survey recommends the NASA Science Mission Directorate to develop a rigorous Observing System Simulation Experiment (OSSE) framework for Mars, to optimize future atmospheric observations. Atmospheric conditions on Mars are a potential hazard source for landing missions. Errors in the estimates of atmospheric density profiles, inadequate knowledge of wind vertical structure and dust concentration as a function of height are likely causes of uncertainty at the landing site on the order of kilometers. An operational real-time weather forecasting capability for Mars would reduce such uncertainties, carrying enormous benefits to future robotic missions, and would be an invaluable prerequisite for human missions.A real-time forecasting capability relies upon three fundamental components: a critical mass of observing systems, a data assimilation system (DAS), and a global forecast model. The DAS allows the model to ingest the data effectively, optimizing the observational information content,and transforming them into a gridded representation of the atmosphere at a given time, called an ‘analysis’. The analysis is the best estimate of the atmospheric state for that time, and also represents a set of ‘initial conditions’ from which a global model can be initialized, to predict a future state of the atmosphere. The connection between analysis and forecast represents the foundation of modern weather forecasting. However, from the point of view of a forecast system,not all observations are equally impactful, partially because of the problem of “observational error correlation”, one important research topic in data assimilation development. For the Earth, partly due to the spontaneous and deregulated development of observations and forecast capabilities worldwide for more than half a century,the use of observations in contemporary operational forecast systems is suboptimal, with many potentially useful data being underutilized. On the contrary, Mars atmospheric scientists are in the unique situation of designing the next-generation observing systems by learning from the experience gathered on the Earth, so as to assure that the future instruments are specifically optimized to give the maximum benefit to a future weather forecast capability.An immensely powerful tool that has been firmly established by atmospheric scientists on the Earth is represented by a properly designed OSSE framework. A realistic OSSE framework cannot only quantify the benefit of future data types, be them surface based or space borne, but can also help design and optimize an entire observational network. Furthermore, OSSEs can provide deep insights into an atmosphere’s behavior, by addressing conceptual problems of its intrinsic predictability and delineating the regions or features of the atmosphere which are more sensitive to additional data and would benefit from a denser sampling. The difficulties posed by OSSEs are fundamentally different for Earth and Mars. For Earth, the enormous data volume imposes a tremendous constraint on any innovation in the observing systems: it is very hard for a single sensor to impact the skill. For Mars, the problem is the opposite: almost any additional instrument will exert some impact. However, OSSEs can help to evaluate the cost/benefit for every sensor and suggest optimal data configuration and density.The purpose of this white paper is to provide an introduction to a rigorously designed OSSE framework, explain the underlying problems and challenges, and engage the Mars community to collaborate with Earth Atmospheric scientists in order to develop a joint-OSSE framework for Mars with the largest consensual basis possible. An OSSE infrastructure would increase the understanding of the Martian atmosphere, would help NASA to optimize instrument specifications and orbit choice, providing the maximium benefit for a given expenditure of resources, and could even help establishing a roadmap for a future real-time weather forecasting capability.

Oreste Reale↗
DOE OSTI2026

Trisodium Phosphate Phases and Solubility in Alkaline Solutions Relevant to Radioactive Waste Processing

The U.S. Department of Energy’s Hanford Site faces significant challenges in managing millions of gallons of legacy radioactive waste, where phosphate precipitation can obstruct pipelines during retrieval and processing. To resolve long-standing inconsistencies in reported solubility and clarify factors governing trisodium phosphate hydrates, we examined the Na3PO4:NaOH:H2O system. Powder and single-crystal X-ray diffraction revealed that commercial precursors undergo transformations that produce multiple hydrates, including three previously unreported phases comprising an ordered polymorph of Na3(PO4)·12H2O·1/6NaOH, Na3PO4·5H2O, and Na3PO4·9H2O. Computational modeling indicated that the ordered dodecahydrate is more stable than its disordered counterpart, suggesting kinetic persistence of structural disorder. Solubility measurements were conducted with solutions prepared either from anhydrous Na3PO4 or from Na3(PO4)·12H2O·1/6NaOH and revealed that release of interstitial NaOH from the hydrate precursor elevated solution alkalinity, thereby significantly reducing phosphate solubility relative to solutions prepared with anhydrous Na3PO4 across 20–44 °C. These results begin to reconcile inconsistencies in prior solubility data and clarify how phase composition dictates phosphate precipitation under alkaline conditions.

Graham, Trenton R. (ORCID:0000000189078004)↗
DOE OSTI2025

Overview of the SCEC/USGS Community Stress Drop Validation Study Using the 2019 Ridgecrest Earthquake Sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. Here, in this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values.

58 GEOSCIENCES↗
DOE OSTI2025

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis Data and Application to Ukraine

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind).

17 WIND ENERGY↗
NASA NTRS1982

Precision of spiral-bevel gears

The kinematic errors in spiral bevel gear trains caused by the generation of nonconjugate surfaces, by axial displacements of the gears during assembly, and by eccentricity of the assembled gears were determined. One mathematical model corresponds to the motion of the contact ellipse across the tooth surface, (geometry I) and the other along the tooth surface (geometry II). The following results were obtained: (1) kinematic errors induced by errors of manufacture may be minimized by applying special machine settings, the original error may be reduced by order of magnitude, the procedure is most effective for geometry 2 gears, (2) when trying to adjust the bearing contact pattern between the gear teeth for geometry 1 gears, it is more desirable to shim the gear axially; for geometry II gears, shim the pinion axially; (3) the kinematic accuracy of spiral bevel drives are most sensitive to eccentricities of the gear and less sensitive to eccentricities of the pinion. The precision of mounting accuracy and manufacture are most crucial for the gear, and less so for the pinion.

Litvin, F. L.↗
NASA NTRS1983

Precision of spiral-bevel gears

The kinematic errors in spiral bevel gear trains caused by the generation of nonconjugate surfaces, by axial displacements of the gears during assembly, and by eccentricity of the assembled gears were determined. One mathematical model corresponds to the motion of the contact ellipse across the tooth surface, (geometry I) and the other along the tooth surface (geometry II). The following results were obtained: (1) kinematic errors induced by errors of manufacture may be minimized by applying special machine settings, the original error may be reduced by order of magnitude, the procedure is most effective for geometry 2 gears, (2) when trying to adjust the bearing contact pattern between the gear teeth for geometry I gears, it is more desirable to shim the gear axially; for geometry II gears, shim the pinion axially; (3) the kinematic accuracy of spiral bevel drives are most sensitive to eccentricities of the gear and less sensitive to eccentricities of the pinion. The precision of mounting accuracy and manufacture are most crucial for the gear, and less so for the pinion. Previously announced in STAR as N82-30552

Litvin, F. L.↗
NASA NTRS1983

Image processing in remote sensing data analysis - The state of the art

Image analysis techniques applicable to remote sensing data and covering image models, feature detection, segmentation and classification, texture analysis, and matching are studied. Model types for characterizing images examined include random-field, mosaic, and facet models. Edge and corner detection as well as global extraction of linear features are discussed. Pixel clustering and classification are covered in addition to the regional approach to segmentation. Autocorrelation, second-order gray level probability density, and the use of primitive element statistics are discussed in relation to texture analysis. Finally, reducing the cost of (sub)imaging matching methods (e.g., pixelwise comparison of gray levels and normalized cross-correlation between two images) as well as improving match sharpness is considered.

Rosenfeld, A.↗
NASA NTRS1992

Reduced basis technique for evaluating the sensitivity coefficients of the nonlinear tire response

An efficient reduced-basis technique is proposed for calculating the sensitivity of nonlinear tire response to variations in the design variables. The tire is modeled using a 2-D, moderate rotation, laminated anisotropic shell theory, including the effects of variation in material and geometric parameters. The vector of structural response and its first-order and second-order sensitivity coefficients are each expressed as a linear combination of a small number of basis vectors. The effectiveness of the basis vectors used in approximating the sensitivity coefficients is demonstrated by a numerical example involving the Space Shuttle nose-gear tire, which is subjected to uniform inflation pressure.

Noor, Ahmed K.↗
NASA NTRS1992

Development of the quasi-procedural method for use in aircraft configuration optimization

The performance of the quasi-procedural analysis system in optimization tasks is investigated. In particular, the quasi-procedural method is applied to the complete mission optimization of a medium-sized transport aircraft using a vortex-lattice aerodynamic model and finite element structural analysis of the wing and the tail. Some modifications and improvements to the system, required in order to complete this task, are described. The performance of the system is compared with that of the standard procedural system, and it is shown that the quasi-procedural approach reduces the analysis required to reach the optimum. The overall cost is shown to be strongly dependent on the analysis architecture and data structure.

Gage, P.↗
NASA NTRS1993

Characteristics of products generated by selective sintering and stereolithography rapid prototyping processes

The trend in the modern global economy towards free market policies has motivated companies to use rapid prototyping technologies to not only reduce product development cycle time but also to maintain their competitive edge. A rapid prototyping technology is one which combines computer aided design with computer controlled tracking of focussed high energy source (eg. lasers, heat) on modern ceramic powders, metallic powders, plastics or photosensitive liquid resins in order to produce prototypes or models. At present, except for the process of shape melting, most rapid prototyping processes generate products that are only dimensionally similar to those of the desired end product. There is an urgent need, therefore, to enhance the understanding of the characteristics of these processes in order to realize their potential for production. Currently, the commercial market is dominated by four rapid prototyping processes, namely selective laser sintering, stereolithography, fused deposition modelling and laminated object manufacturing. This phase of the research has focussed on the selective laser sintering and stereolithography rapid prototyping processes. A theoretical model for these processes is under development. Different rapid prototyping sites supplied test specimens (based on ASTM 638-84, Type I) that have been measured and tested to provide a data base on surface finish, dimensional variation and ultimate tensile strength. Further plans call for developing and verifying the theoretical models by carefully designed experiments. This will be a joint effort between NASA and other prototyping centers to generate a larger database, thus encouraging more widespread usage by product designers.

Cariapa, Vikram↗
NASA NTRS2009

Towards Verification of Operational Procedures Using Auto-Generated Diagnostic Trees

The design, development, and operation of complex space, lunar and planetary exploration systems require the development of general procedures that describe a detailed set of instructions capturing how mission tasks are performed. For both crewed and uncrewed NASA systems, mission safety and the accomplishment of the scientific mission objectives are highly dependent on the correctness of procedures. In this paper, we describe how to use the auto-generated diagnostic trees from existing diagnostic models to improve the verification of standard operating procedures. Specifically, we introduce a systematic method, namely the Diagnostic Tree for Verification (DTV), developed with the goal of leveraging the information contained within auto-generated diagnostic trees in order to check the correctness of procedures, to streamline the procedures in terms of reducing the number of steps or use of resources in them, and to propose alternative procedural steps adaptive to changing operational conditions. The application of the DTV method to a spacecraft electrical power system shows the feasibility of the approach and its range of capabilities

Kurtoglu, Tolga↗
NASA NTRS2011

Orion Parachute Riser Cutter Development

This paper presents the tests and analytical approach used on the development of a steel riser cutter for the CEV Parachute Assembly System (CPAS) used on the Orion crew module. Figure 1 shows the riser cutter and the steel riser bundle which consists of six individual cables. Due to the highly compressed schedule, initial unavailability of the riser material and the Orion Forward Bay mechanical constraints, JSC primarily relied on a combination of internal ballistics analysis and LS-DYNA simulation for this project. Various one dimensional internal ballistics codes that use standard equation of state and conservation of energy have commonly used in the development of CAD devices for initial first order estimates and as an enhancement to the test program. While these codes are very accurate for propellant performance prediction, they usually lack a fully defined kinematic model for dynamic predictions. A simple piston device can easily and accurately be modeled using an equation of motion. However, the accuracy of analytical models is greatly reduced on more complicated devices with complex external loads, nonlinear trajectories or unique unlocking features. A 3D finite element model of CAD device with all critical features included can vastly improve the analytical ballistic predictions when it is used as a supplement to the ballistic code. During this project, LS-DYNA structural 3D model was used to predict the riser resisting load that was needed for the ballistic code. A Lagrangian model with eroding elements shown in Figure 2 was used for the blade, steel riser and the anvil. The riser material failure strain was fine tuned by matching the dent depth on the anvil with the actual test data. LS-DYNA model was also utilized to optimize the blade tip design for the most efficient cut. In parallel, the propellant type and the amount were determined by using CADPROG internal ballistics code. Initial test results showed a good match with LS-DYNA and CADPROG simulations. Final paper will present a detailed roadmap from initial ballistic modeling and LS-DYNA simulation to the performance testing. Blade shape optimization study will also be presented.

Oguz, Sirri↗
NASA NTRS2015

BioSentinel: Mission Development of a Radiation Biosensor to Gauge DNA Damage and Repair Beyond Low Earth Orbit on a 6U Nanosatellite

We are designing and developing a 6U (10 x 22 x 34 cm; 14 kg) nanosatellite as a secondary payload to fly aboard NASAs Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinels 12- to 18-month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. In order to understand the relative contributions of the space environments two dominant biological perturbations, reduced gravity and ionizing radiation, results from deep space will be directly compared to data obtained in LEO (on ISS) and on Earth. These data points will be available for validation of existing biological radiation damage and repair models, and for extrapolation to humans, to assist in mitigating risks during future long-term exploration missions beyond LEO. The BioSentinel Payload occupies 4U of the spacecraft and will utilize the monocellular eukaryotic organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from ambient space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. Yeast was selected because of 1) its similarity to cells in higher organisms, 2) the well-established history of strains engineered to measure DSB repair, 3) its spaceflight heritage, and 4) the wealth of available ground and flight reference data. The S. cerevisiae flight strain will include engineered genetic defects to prevent growth and division until a radiation-induced DSB activates the yeasts DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its successful repair. The yeast will be carried in the dry state within the 1-atm PL container in 18 separate fluidics cards with each card having 16 independent culture microwells, with integral microchannels and filters to supply nutrients and reagents, confine the yeast to the wells, and enable optical measurement. The measurement subsystem will monitor each subgroup of culture wells continuously for several weeks, optically tracking DSB-triggered cell growth and metabolism. BioSentinel will also include physical radiation sensors based on the TimePix sensor, as implemented by JSCs RadWorks group, which record individual radiation events including estimates of their linear-energy-transfer (LET) values. Radiation-dose and LET data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels.

Radiation Biosensor↗
NASA NTRS2016

Thermal Cycling for Development of Hybrid Fuel for a Notional Mars Ascent Vehicle

A Mars Ascent Vehicle (MAV) would be a critical part of a potential Mars sample return campaign. As currently envisioned, the MAV would launch samples from Mars into Mars orbit. Challenging requirements would be placed on a MAV as it would need to be able to survive in the harsh Martian environment which can get as cold as -120°C in the winter. At these cold temperatures, survival heating could be necessary to keep the MAV within the allowable flight temperature range. Estimates for survival heating power show that a fuel capable of operating at low temperature would significantly reduce the total required energy of the MAV. This has led to consideration of a hybrid propulsion system due to its anticipated low temperature capability. A new wax-based fuel, SP7, has been developed for a notional MAV mission. Thermal modeling of the fuel in the Mars environment was completed in order to estimate the temperature response of the fuel during Mars diurnal temperature cycling. Preliminary thermal testing was conducted to determine the max temperature range, radial gradient, and ramp rate the fuel could tolerate without cracking. The modeling and preliminary testing was used to develop a comprehensive, 100-day thermal cycling campaign. A total of 200 cycles are planned that are representative of 200 Martian diurnal cycles, roughly one-third of a Martian year. After 150 cycles, the fuel samples show no signs of cracking that would jeopardize the rocket’s performance. Though not yet complete, this testing is showing that SP7 has the potential to successfully be used on a MAV mission.

Farias, Edgardo↗
NASA NTRS1995

Nonlinear vibrations of thin-walled composite frames

A reduced basis technique and a computational procedure are presented for generating the nonlinear vibrational response, and evaluating the first-order sensitivity coefficients of thin-walled composite frames. The sensitivity coefficients are the derivatives of the nonlinear frequency with respect to the material and lamination parameters of the frame. A mixed formulation is used with the fundamental unknowns consisting of both the generalized displacements and stress resultants in the frame. The flanges and webs of the frames are modeled by using geometrically nonlinear two-dimensional shell and plate finite elements. The computational procedure can be conveniently divided into three distinct steps. The first step involves the generation of various-order perturbation vectors, and their derivatives with respect to the material and lamination parameters of the frame, using the Linstedt-Poincare perturbation technique. The second step consists of using the perturbation vectors as basis vectors, computing the amplitudes of these vectors and the nonlinear frequency of vibration, via a direct variational procedure. The third step consists of using the perturbation vectors, and their derivatives, as basis vectors and computing the sensitivity coefficients of the nonlinear frequency via a second application of the direct variational procedure. Numerical results are presented for semicircular thin-walled frames with I and J section, showing the convergence of the nonlinear frequency and the sensitivity coefficients obtained by both the reduced-basis and perturbation techniques.

Noor, Ahmed K.↗