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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 307 records · Page 17

FRESIP: A Discovery Mission Concept To Find Earth-Sized Planets Around Solar Like Stars

The current nebular theory postulates that planets are. a consequence of the formation of stars from viscous accretion disks. Condensation from the accretion disk favors the formation of small rocky planets in the hot inner region, and the formation of gas giants in the cool outer region. Consequently, terrestrial-type planet in inner orbits should be commonplace. From geometrical considerations , Borucki and Summers have shown that 1% of planetary systems resembling our solar system should show transits for Earth-sized (or larger) planets. Thus a photometric satellite that uses a wide field of view telescope and a large detector array to simultaneously monitor 5000 target stars should detect 50 planetary systems. To differentiate regularly recurring transits from statistical fluctuations of the stellar flux, one must observe over several orbital periods so that the false positive rate can be reduced to one event or less. A one-meter aperture telescope placed in a halo orbit about either the L1 or L2 Lagrange points and viewing perpendicular to both the orbital and ecliptic planes can view continuously for the required period because neither the Sun, Earth, or Moon would enter the field of view. Model calculations show that the observations should provide statistically significant estimates of the distributions of planetary size, orbital radius, coplanarity, and the frequency of planetary systems that have Earth-sized planets in inner orbits. Because approximately one half of the star systems observed will be binary systems, the frequency of planetary systems orbiting either one or both of the stars can also be determined.

Borucki, William↗

Computational Control of Flexible Aerospace Systems

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years of the project. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed. A theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modelling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide a embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

Sharpe, Lonnie, Jr.↗

A Statistical Simulation Approach to Safe Life Fatigue Analysis of Redundant Metallic Components

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Matthews, William T.↗

Comparative Study of Data-Driven Area Inertia Estimation Approaches on WECC Power Systems

With the increasing integration of inverter-based resources into the power grid, there has been a notable reduction in system inertia, potentially compromising frequency stability. To assess the suitability of existing area inertia estimation techniques for real-world power systems, this paper presents a rigorous comparative analysis of system identification, measurement reconstruction, and electromechanical oscillation-based area inertia estimation methodologies, specifically applied to the large-scale and multi-area WECC 240-bus power system. Comprehensive results show that the system identification-based approach exhibits superior robustness and accuracy relative to its counterparts.

area inertia estimation↗

Detection of "noisy" chaos in a time series

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Non-NASA Center↗

Military markets for solar thermal electric power systems

The Department of Defense maintains an inventory of over 1,800 MW of engine-generators 15 KW and larger, with an estimated procurement rate of over 140 MW/year. Nearly the entire requirement could be met by advanced heat engines of the types being developed as point-focussing, distributed receiver power plants. A conceptual system consisting of a heat engine which efficiently burns liquid fossil or synthetic fuels, with a 'solarization kit' for conversion to hybrid solar operation could meet existing DOD requirements for new systems which are quieter, lighter, and multi-fueled. An estimated 24 percent (33 MW/year) or more could operationally benefit from the solar option. Baseline cost projections indicate levelized energy cost goals of 210 to 120 mills/KWh (15 to 1000 KW systems). Fuel cost escalation is the major factor affecting the value of the solar option. A baseline calculation for fuel at $0.59/gal in spring, 1979, escalating at 8 percent above general inflation indicates a value of $2700/KWe for a solarization kit.

Hauger, J. S.↗

The globular cluster system of M31

Previous data on globular cluster candidates in M31 have been studied in order to identify a large sample of clusters with reliable UBV photometry and independent reddening estimates. The distribution of the intrinsic colors of the M31 globular clusters is similar to that of the Galactic globulars. While the flattening and kinematics of the system of metal-rich clusters suggest a disk, the more metal-poor clusters reveal little evidence for rotation. It is noted that the flattening of the system of metal-poor and intermediate clusters resembles that of the M31 spheroid, and that the effective radius of the intermediate system also resembles that of the spheroid.

Elson, Rebecca A.↗

Development of a Weibull posterior distribution by combining a Weibull prior with an actual failure distribution using Bayesian inference

A Bayesian inference process for system logistical planning is presented which provides a method for incorporating actual failures with prediction data for an ongoing and improving reliability estimates. The process uses the Weibull distribution, and provides a means for examining and updating logistical and maintenance support needs.

Giuntini, Michael E.↗

Sizing Considerations for EV Dynamic Wireless Charging Systems with Integrated Energy Storage

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.

Lewis, Donovin D.↗

Design, scaling and cost evaluations of circulating fluidized-bed systems for biomass pyrolysis

To generate updated and transparent capital cost estimates for biomass fast pyrolysis equipment, refinery fluidized catalytic cracking design and sizing principles are examined and extended to pyrolysis of woody biomass. Capital costs for the sized equipment are estimated with process-industry software. A one-dimensional flow simulation with pyrolysis kinetics is leveraged to validate the fluidization conditions and thermal energy balance. After successful sizing and a system cost estimate of $\$$2.8 M (in 2016 US$\$$) at the biorefinery scale of 1000 metric tons per day (MTD), these methods were exercised for even smaller equipment at the distributed pyrolysis scale with modifications to the process design constraints, and not directly comparable with the 1000 MTD case, arriving at capital cost estimates of $\$$1.2 M for a 500 ton/day system and $\$$0.9 M for a 200 ton/day system. Here in this work, It is noted that this work only estimates purchased equipment costs at the ±50% accuracy level; there are significant other custom factors applicable to each installation based on location, maturity, scale, complexities during installation, engineering and licensing costs, etc. that need to be added on to these estimates to derive investment costs.

09 BIOMASS FUELS↗

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗

SPS Energy Conversion Power Management Workshop

Energy technology concerning photovoltaic conversion, solar thermal conversion systems, and electrical power distribution processing is discussed. The manufacturing processes involving solar cells and solar array production are summarized. Resource issues concerning gallium arsenides and silicon alternatives are reported. Collector structures for solar construction are described and estimates in their service life, failure rates, and capabilities are presented. Theories of advanced thermal power cycles are summarized. Power distribution system configurations and processing components are presented.

Source record↗

Entanglement swapping systems toward a quantum internet

We demonstrate conditional entanglement swapping, i.e. teleportation of entanglement, between time-bin qubits at the telecommunication wavelength of 1536.4 nm with high fidelity of 87%. Our system is deployable, utilizing modular, off-the-shelf, fiber-coupled, and electrically controlled components such as electro-optic modulators. It leverages the precise timing resolution of superconducting nanowire detectors, which are controlled and read out via a custom developed graphical user interface. The swapping process is described, interpreted, and guided using characteristic function-based analytical modeling that accounts for realistic imperfections. Our system supports quantum networking protocols, including source-independent quantum key distribution, with an estimated secret key rate of approximately 0.5 bits per sifted bit.

Davis, Samantha I. [Caltech] (ORCID:00000001999481↗

Application of optical distributed sensing and computation to control of a large flexible spacecraft

Advances in real-time holography make possible the development of new distributed optical sensors and processors that may have application to the control of flexible structures. This paper presents the analytic evaluation of control system concepts utilizing this new technology on realistic spacecraft. The design of a distributed estimator based on this new optical sensing technique is targeted to vibration control of a complex spacecraft with multiple optical sensors, each of which views a portion of the spacecraft. A simulation of a complex truss structure that was flown in the Solar Array Flight Experiment is utilized to evaluate the performance of the estimator. It is shown that good performance can be obtained from a distributed estimator even in the presence of significant sensor noise.

Montgomery, R. C.↗

Recent advances in radar remote sensing of forest

On a global scale, forests represent most of the terrestrial standing biomass (80 to 90 percent). Thus, natural and anthropogenic change in forest covers can have major impacts not only on local ecosystems but also on global hydrologic, climatic, and biogeochemical cycles that involve exchange of energy, water, carbon, and other elements between the earth and atmosphere. Quantitative information on the state and dynamics of forest ecosystems and their interactions with the global cycles appear necessary to understand how the earth works as a natural system. The information required includes the lateral and vertical distribution of forest cover, the estimates of standing biomass (woody and foliar volume), the phenological and environmental variations and disturbances (clearcutting, fires, flood), and the longer term variations following deforestation (regeneration, successional stages). To this end, seasonal, annual, and decadal information is necessary in order to separate the long term effects in the global ecosystem from short term seasonal and interannual variations. Optical remote sensing has been used until now to study the forest cover at local, regional, and global scales. Radar remote sensing, which provides recent SAR data from space on a regular basis, represents an unique means of consistently monitoring different time scales, at all latitudes and in any atmospheric conditions. Also, SAR data have shown the potential to detect several forest parameters that cannot be inferred from optical data. The differences--and complementarity--lie in the penetration capabilities of SAR data and their sensitivity to dielectric and geometric properties of the canopy volume, whereas optical data are sensitive to the chemical composition of the external foliar layer of the vegetation canopy.

Letoan, Thuy↗

A Summary of Large Raindrop Observations from GPM GV Field Campaigns

NASA's Global Precipitation Measurement Mission (GPM) has conducted as series of Ground Validation (GV) studies to assist algorithm development for the GPM core satellite. Characterizing the drop size distribution (DSD) for different types of precipitation systems is critical in order to accurately estimate precipitation across the majority of the planet. Thus far, GV efforts have sampled DSDs in a variety of precipitation systems from Finland to Oklahoma. This dataset consists of over 33 million raindrops sampled by GPM GV's two‐dimensional video disdrometers (2DVD) and includes RSD observations from the LPVEx, MC3E, GCPEx, HyMEx and IFloodS campaigns as well as from GV sites in Huntsville, AL and Wallops Island, VA. This study focuses on the larger end of the raindrop size spectrum, which greatly influences radar reflectivity and has implications for moment estimation. Thus knowledge of the maximum diameter is critical to GPM algorithm development. There are over 24,000 raindrops exceeding 5 mm in diameter contained within this disdrometer dataset. The largest raindrops in the 2DVD dataset (>7‐8 mm in diameter) are found within intense convective thunderstorms, and their origins are believed to be hailstones. In stratiform rainfall, large raindrops have also been found to fall from lower and thicker melting layers. The 2DVD dataset will be combined with that collected by dual‐polarimetric radar and aircraft particle imaging probes to "follow" the vertical evolution of the DSD tail (i.e., retrace the large drops from the surface to their origins aloft).

Gatlin, Patrick N.↗

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Artyukhin, Eugene A.↗

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗