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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Methods and apparatuses using filter banks for multi-carrier spread-spectrum signals

A transmitter includes a synthesis filter bank to spread a data symbol to a plurality of frequencies by encoding the data symbol on each frequency, apply a common pulse-shaping filter, and apply gains to the frequencies such that a power level of each frequency is less than a noise level of other communication signals within the spectrum. Each frequency is modulated onto a different evenly spaced subcarrier. A demodulator in a receiver converts a radio frequency input to a spread-spectrum signal in a baseband. A matched filter filters the spread-spectrum signal with a common filter having characteristics matched to the synthesis filter bank in the transmitter by filtering each frequency to generate a sequence of narrow pulses. A carrier recovery unit generates control signals responsive to the sequence of narrow pulses suitable for generating a phase-locked loop between the demodulator, the matched filter, and the carrier recovery unit.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Methods and apparatuses for self-generating fault-tolerant keys in spread-spectrum systems

Self-generating fault-tolerant keys for use in spread-spectrum systems are disclosed. At a communication device, beacon signals are received from another communication device and impulse responses are determined from the beacon signals. The impulse responses are circularly shifted to place a largest sample at a predefined position. The impulse responses are converted to a set of frequency responses in a frequency domain. The frequency responses are shuffled with a predetermined shuffle scheme to develop a set of shuffled frequency responses. A set of phase differences is determined as a difference between an angle of the frequency response and an angle of the shuffled frequency response at each element of the corresponding sets. Each phase difference is quantized to develop a set of secret-key quantized phases and a set of spreading codes is developed wherein each spreading code includes a corresponding phase of the set of secret-key quantized phases.

42 ENGINEERING↗
DOE OSTI2016

Methods and apparatuses using filter banks for multi-carrier spread spectrum signals

A transmitter includes a synthesis filter bank to spread a data symbol to a plurality of frequencies by encoding the data symbol on each frequency, apply a common pulse-shaping filter, and apply gains to the frequencies such that a power level of each frequency is less than a noise level of other communication signals within the spectrum. Each frequency is modulated onto a different evenly spaced subcarrier. A demodulator in a receiver converts a radio frequency input to a spread-spectrum signal in a baseband. A matched filter filters the spread-spectrum signal with a common filter having characteristics matched to the synthesis filter bank in the transmitter by filtering each frequency to generate a sequence of narrow pulses. A carrier recovery unit generates control signals responsive to the sequence of narrow pulses suitable for generating a phase-locked loop between the demodulator, the matched filter, and the carrier recovery unit.

42 ENGINEERING↗
DOE OSTI2017

Online Measurement of the Energy Spread of Multi-Turn Beam in the Fermilab Booster at Injection

We have developed a computer program interfaced with the ACNET environment of Fermilab accelerators to measure energy spread of the proton beam from the LINAC at an injection into the Booster. It uses a digitizing oscilloscope and provides users an ability to configure the scope settings for optimal data acquisition from a resistive wall current monitor. When the program is launched, a) a one shot timeline is generated to initiate beam injection into the Booster, b) a gap of about 40 ns is produced in the injected beam using a set of fast kickers, c) collects line charge distribution data from the wall current monitor for the first 200 μs from the injection and d) performs complete data analysis to extract full beam energy spread of the beam. The program also gives the option to store the data for offline analyses. We illustrate a case with an example. We also present results on beam energy spread as a function of beam intensity from recent measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Methods and apparatuses using filter banks for multi-carrier spread spectrum signals

A transmitter includes a synthesis filter bank to spread a data symbol to a plurality of frequencies by encoding the data symbol on each frequency, apply a common pulse-shaping filter, and apply gains to the frequencies such that a power level of each frequency is less than a noise level of other communication signals within the spectrum. Each frequency is modulated onto a different evenly spaced subcarrier. A demodulator in a receiver converts a radio frequency input to a spread-spectrum signal in a baseband. A matched filter filters the spread-spectrum signal with a common filter having characteristics matched to the synthesis filter bank in the transmitter by filtering each frequency to generate a sequence of narrow pulses. A carrier recovery unit generates control signals responsive to the sequence of narrow pulses suitable for generating a phase-locked loop between the demodulator, the matched filter, and the carrier recovery unit.

42 ENGINEERING↗
DOE OSTI2015

Effects of Potential Energy Spread on Particle Dynamics in Magnetic Bending Systems

Understanding CSR effects for the generation and transport of high brightness electron beams is crucial for designs of modern FELs. Most studies of CSR effects focus on the impacts of the longitudinal CSR wakefield. In this study, we investigate the impact of the initial retarded potential energy of particles, due to bunch collective interaction, on the transverse dynamics of particles on a curved orbit. It is shown that as part of the remnants of the CSR cancellation effect when both the longitudinal and transverse CSR fores are taken into account, this initial potential energy at the entrance of a bending system acts as a pseudo kinetic energy, or pseudo energy in short, because its effect on particle optics through dispersion and momentum compaction is indistinguishable from effect of the usual kinetic energy offset from the design energy. Our estimation indicates that the resulting effect of pseudo energy spread can be measurable only when the peak current of the bunch is high enough such that the slice pseudo energy spread is appreciable compared to the slice kinetic energy spread. The implication of this study on simulations and experiments of CSR effects will be discussed.

Li, R.↗
DOE OSTI2024

Learning of networked spreading models from noisy and incomplete data

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the number of samples required for an accurate learning. Here, in this work, we introduce a universal learning method based on a scalable dynamic message-passing technique that addresses these challenges often encountered in real data. The algorithm leverages available prior knowledge on the model and on the data, and reconstructs both network structure and parameters of a spreading model. We show that a linear computational complexity of the method with the key model parameters makes the algorithm scalable to large network instances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Modeling and Experimental Demonstration of Flux Spreading in Light Trapping Planar-Cavity Solar Enclosed Particle Receivers

This study experimentally validates and numerically models the flux-spreading effect in a light-trapping planar-cavity solar receiver) for particle-based concentrating solar power systems. The receiver's shallow cavity with vertical planar walls redistributes concentrated solar flux, reducing peak intensity and achieving uniform heat flux. On-sun tests at National Renewable Energy Laboratory's High-Flux Solar Furnace under flux up to 1500 kW/m2 measured cavity wall temperatures, which were compared with Monte Carlo ray-tracing (SolTrace) and computational numerical simulations. Three angular absorptance models were evaluated: constant absorptance, a Pyromark-based directional model, and a Fresnel-based Cr2O3 model. The Fresnel-derived model showed the best agreement with experiments, achieving high correlation (PC > 0.85), structural similarity (SSIM > 0.98), and signal-to-noise ratios (PSNR > 40 dB), with temperature prediction errors of 1-11%. Results confirm that flux spreading mitigates local overheating and validate the integrated modeling approach, supporting the solar receiver scalability for high-efficiency, high-temperature concentrating solar power applications.

14 SOLAR ENERGY↗
DOE OSTI2024

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. Here we focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Density fluctuation statistics and turbulence spreading at the edge of L–mode plasmas

Long-wavelength density fluctuations ($k{\rho _i}$ <1) are studied using beam emission spectroscopy (BES) at the edge of DIII-D L-mode plasmas (ρ = 0.88–1.1) in scenarios with electron cyclotron heating (ECH) power ramp (P ECH up to 1.5 MW), neutral beam injection (NBI) power ramp (P NBI up to 2.5 MW), and injected torque scan (-1 < T inj <0.6 Nm). We find that broadband turbulent density fluctuations (ƒ ~ 20–120 kHz) have a non-Gaussian distribution. The skewness of $\delta n/n$ changes sign from negative at ρ < 0.95–0.97 to positive at ρ > 0.97, indicating the prevalence of density 'voids' at inner radii and density 'blobs' at outer radii and outside of the separatrix. The turbulence intensity flux $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is calculated to characterize turbulence spreading at the plasma edge. During ECH/NBI power ramps and at counter-I p injected torque, $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is directed inward inside the separatrix, which is evidence of inward spreading of turbulence intensity from the edge gradient region caused by the inner propagation of density 'voids'. Significantly weaker $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is observed with co-I p torque. A correlation between co-I p torque, turbulence intensity $\delta n/n$ at ρ = 0.97, and increased srape-off layer (SOL) heat flux decay length ${\lambda _q}$ is found in the torque scan scenario, showing that edge turbulence plays a material role in determining the SOL conditions and heat flux width.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Fault Tolerant Key Generation and Secure Spread Spectrum Communication

This study presents a secure information transmission system compromised of two main parts. The first component makes use of the principle of reciprocity in frequency-selective wireless channels to derive a pair of keys for two legitimate parties. The proposed key generation algorithm allows for two asynchronous transceivers to derive a pair of similar keys. Moreover, we apply a unique augmentation - called strongest path cancellation (SPC) - to the keys and have validated through simulation and real-world measurements that this technique significantly boosts the security level of the overall design. In the second part of the secure information transmission system, we introduce the concept of artificial noise to multi-carrier spread-spectrum (MC-SS) systems. The keys generated in the first part are used as spreading code sequences for MC-SS and artificial noise is added to further enhance the security of this communication setup. Two different attacks on our proposed system are evaluated. First, a passive adversary who follows the exact same steps as the legitimate users to detect confidential information is considered. In the second attack, we evaluate the design in presence of an adversary with significant blind detection capabilities.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Materials and technologies for interstellar flights and intra-galactic spread of life

Small automated spaceships are capable to deliver seeds, frozen ova and gametes to other planetary systems. A spaceship can be equipped with a freezer containing reproductive cells, an artificial uterus, a robotic nursery and school, and a collection of instruments and equipment. The whole spaceship will be frozen during a long interstellar flight. Approaching another star, a spaceship will generate electricity from light, warm up, slow down and land on a suitable planet (if any), give birth to a human, provide care and education. After schooling, the human will vacate the spaceship and either build more space for living (using local materials) or die. A vacant spaceship will supply more people, one at a time. Hopefully, they will collectively create a sustainable colony on a remote planet. Our Milky Way galaxy has hundreds billion stars (i.e., more stars than humans on Earth). Mass production of spacecrafts for intragalactic spread of life will make each spaceship cheaper, will improve employment and purposeful production on Earth, and will spread human life beyond the Solar System. If any spaceship will miss its target stellar system, it will fly to the next one, retaining ability to bring life to another planet. Which materials and technologies are needed for the interstellar life propagation? Materials age during a long interstellar flight, which can last from 10^4 to 10^10 years. We evaluate the computational methods (such as C2NEB, available from https://lib.dr.iastate.edu/ameslab_software/1) that are suitable for addressing materials aging at low temperatures and high radiation levels during the appropriately long-time scales.

Technologies↗
DOE OSTI2015

The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations

Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.

Fueglistaler, S.↗
DOE OSTI2015

An alternate approach to ensemble ENSO forecast spread: Application to the 2014 forecast

Abstract Evaluating the 2014 El Niño forecast as a “bust” may be tapping into a bigger issue, namely that forecast “overconfidence” from single‐model ensembles could affect the retrospective assessment of El Niño–Southern Oscillation (ENSO) predictions. The present study proposes a new approach to quantifying an “expected” spread and uncertainty from noise‐driven processes and supplementing these measures with actual ENSO forecasts. Expanding on a previously developed coupled model framework that isolates noise‐driven ENSO‐like errors, an experimental design is implemented to generate an expected December Niño‐3.4 spread from March initial condition sea surface temperature errors that have similar structure to the 2014 and 2015 observed. Results reveal that the 2014 ENSO forecast falls within the expected uncertainty generated by ENSO‐independent, forecast‐independent, noise‐driven errors.

Larson, Sarah M.↗
DOE OSTI2024

Probabilistic Discrete‐Time Models for Spreading Processes in Complex Networks: A Review

Abstract Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread.

Granell, Clara↗
DOE OSTI2023

Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior

The increasing incidence and severity of wildfires underscores the necessity of accurately predicting their behavior. While high-fidelity models derived from first principles offer physical accuracy, they are too computationally expensive for use in real-time fire response. Low-fidelity models sacrifice some physical accuracy and generalizability via the integration of empirical measurements, but enable real-time simulations for operational use in fire response. Machine learning techniques have demonstrated the ability to bridge these objectives by learning first-principles physics while achieving computational speedups. While deep learning approaches have demonstrated the ability to predict wildfire propagation over large time periods, time-resolved fire-spread predictions are needed for active fire management. Here, in this work, we evaluate the ability of deep learning approaches in accurately modeling the time-resolved dynamics of wildfires. We use an autoregressive process in which a convolutional recurrent deep learning model makes predictions that propagate a wildfire over 15 min increments. We apply the model to four simulated datasets of increasing complexity, containing both field fires with homogeneous fuel distribution as well as real-world topologies sampled from the California region of the United States. We show that even after 100 autoregressive predictions representing more than 24 h of simulated fire spread, the resulting models generate stable and realistic propagation dynamics, achieving a Jaccard score between 0.89 and 0.94 when predicting the resulting fire scar. The inference time of the deep learning models are examined and compared, and directions for future work are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization data of an (AlFeNiTiVZr) 1-x Cr x multi-principal element alloy continuous composition spread library

The data provided in this article is related to the research article entitled “Phase stabilization and oxidation of a continuous composition spread multi-principal element (AlFeNiTiVZr) 1-x Cr x alloy”. This data article describes the high-throughput synthesis and characterization processes of an (AlFeNiTiVZr) 1-x Cr x alloy system. Continuous composition spread (CCS) thin-film libraries were synthesized by co-depositing an AlFeNiTiVZr metal alloy target and Cr target via magnetron sputtering. Post-processing was performed on the sample libraries with a vacuum anneal at 873 K and an air anneal at 873 K. Compositional data was determined via WDS in order to verify parameters provided by an in-house sputter model. Crystallographic data was captured via synchrotron diffraction and diffractograms were compared as a function of the change in Cr concentration. These measurements were taken in order to observe phase behavior after oxidation throughout the composition library. Furthermore, vibrational spectrographic data is provided of the oxidized library to show surface speciation along the composition gradient of the alloy system. The structural and oxidative behavior of the (AlFeNiTiVZr) 1-x Cr x alloy can be analysed using the data provided in this article. Additionally, this characterization dataset can be utilized in machine learning algorithms for determining important features and parameters for future hypothesis generation of functional multi-principal element alloys (MPEAs).

36 MATERIALS SCIENCE↗
DOE OSTI2015

Spreading of lithium on a stainless steel surface at room temperature

Lithium conditioned plasma facing surfaces have lowered recycling and enhanced plasma performance on many fusion devices and liquid lithium plasma facing components are under consideration for future machines. A key factor in the performance of liquid lithium components is the wetting by lithium of its container. We have observed the surface spreading of lithium from a mm-scale particle to adjacent stainless steel surfaces using a scanning Auger microprobe that has elemental discrimination. Here, the spreading of lithium occurred at room temperature (when lithium is a solid) from one location at a speed of 0.62 μm/day under ultrahigh vacuum conditions. Separate experiments using temperature programmed desorption (TPD) investigated bonding energetics between monolayer-scale films of lithium and stainless steel. While multilayer lithium desorption from stainless steel begins to occur just above 500 K (E des = 1.54 eV), sub-monolayer Li desorption occurred in a TPD peak at 942 K (E des = 2.52 eV) indicating more energetically favorable lithium-stainless steel bonding (in the absence of an oxidation layer) than lithium lithium bonding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗