Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Spreading”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

How the Universe postpones the evaporation and curtails the quantum spreading of black holes

Black holes are expected to evaporate through the process of Hawking radiation. This process is expected to cause the uncertainty in a black hole’s position to grow to ~ $M^4/M^3_{pl}$ over the course of it’s lifetime, even as its momentum spreads only by ~ $M_{Pl}$ For the black holes that have been observed, which have M ≥ M ⊙ this greatly exceeds the Hubble volume. However, the decay of black holes and their quantum spreading, are delayed in the Universe while the influx of energy into the black holes exceeds their Hawking luminosity. We show that for these M ≥ M ⊙ black holes, their decay outside galaxies and clusters is prevented far longer than it takes the black holes to be dragged well beyond the Hubble horizon, where their eventual decay occurs away from the prying eyes of any observer who has not hitched a ride with them. Meanwhile, black holes in an observer’s galaxy or cluster are themselves prevented from decaying long past the extinction of the last stars, and at least until their galaxy/cluster is swept clean of dark matter, in $\gg$ 10 25 y. Even then, if the black holes become unbound, then they are dragged beyond the Hubble radius before undergoing significant decay; if not, they remain in bound orbits, spreading at most over a subvolume of the galaxy/cluster, and long localized by scatterings to much smaller volumes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Universal Spreading of Conditional Mutual Information in Noisy Random Circuits

For this work, we study the evolution of conditional mutual information (CMI) in generic open quantum systems, focusing on one-dimensional random circuits with interspersed local noise. Unlike in noiseless circuits, where CMI spreads linearly while being bounded by the light cone, we find that noisy random circuits with an error rate 𝑝 exhibit superlinear propagation of CMI, which diverges far beyond the light cone at a critical circuit depth 𝑡 𝑐 ∝ 𝑝 −1 . We demonstrate that the underlying mechanism for such rapid spreading is the combined effect of local noise and a scrambling unitary, which selectively removes short-range correlations while preserving long-range correlations. To analytically capture the dynamics of CMI in noisy random circuits, we introduce a coarse-graining method, and we validate our theoretical results through numerical simulations. Furthermore, we identify a universal scaling law governing the spreading of CMI.

decoherence↗
DOE OSTI2020

Chaos, percolation and the coronavirus spread: a two-step model

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, d 0 , grows exponentially to a saturation value, d ∞ . The typical growth time (aggressive spreading of the virus) is given by τ = 1/λ where λ is the Lyapunov exponent. After a time t crit determined by social distancing and/or other measures, the spread decreases exponentially analogous to nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy, are in this second stage while others including the USA are near the end of the growth stage. The model predicted 15,000 (±2250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10, 2020. Without the quarantine, the casualties would have been more than 50,000, one hundred days after the start of the pandemic. Here, the data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020, and more than 170,000 on August 21, 2020. S. Korea, notwithstanding the high population density (511/km 2 ) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6, 2020, and 301 on August 21, 2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Large-Eddy Simulation Study in WRF on Wind over Broadband Waves of Different Directions and Spreading Widths

We use the Weather Research and Forecasting (WRF) Model coupled with moving waves to conduct large-eddy simulations (LESs) of wind over broadband waves with different propagating directions and spreading widths. Our results show that wind-opposing waves can double the form drag, and the wave propagating direction affects the mean wind velocity, velocity variances, and pressure stress. On the other hand, waves with wider spread tend to reduce the form drag in the streamwise direction. Results further indicate that the wave direction can impact the bulk drag coefficient by as much as 25%, while the wave directional spreading width can change it by 5%. Based on our wave-phase-resolved simulations, we demonstrate that the parameterization of sea surface roughness is significantly influenced by the direction of wave propagation relative to the wind, a factor that the commonly used Charnock relation does not account for.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Space Charge Dominated Momentum Spread and Compensation Strategies in the Post-Linac Section of Proton Improvement Plan-II at Fermilab

The upcoming Proton Improvement Plan-II (PIP-II), designated for enhancements to the Fermilab accelerator complex, features a Beam Transfer Line (BTL) that channels the beam from the linac exit to the booster. In the absence of longitudinal focusing beyond the superconducting linac, the beam experiences an elevated momentum spread, primarily due to nonlinear space-charge forces, surpassing the allowable limit of 2.1e-4. This study presents a detailed examination of the space-charge-induced momentum spread and outlines mitigative strategies. The investigation includes the fine-tuning of a de-buncher cavity, analyzed in terms of operating frequency, longitudinal location, and gap voltage, under both standard and perturbed beam conditions—specifically accounting for momentum jitter and energy variation. The impact of buncher cavity misalignments on the beam's longitudinal phase space is also assessed. The paper concludes by recommending an optimized cavity configuration to effectively mitigate the observed increase in momentum spread along the BTL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Evaluation of Clamshell Current Coupler for Online Frequency Domain and Spread Spectrum Time Domain Reflectometry to Detect Anomalies in Energized Cables

This document describes adaptation and evaluation of a clamshell inductive current coupler for online reflectometry testing (both frequency domain reflectometry and spread spectrum time domain reflectometry) to evaluate cable insulation degradation and anomalies. Safety-critical nuclear power plant cables were initially qualified for 40 years. However, as plants extend their operating licenses to 60 and 80 years, justification for continued safe operation includes test and monitoring programs. These will become more important as the industry moves to condition based qualification programs. Cable test programs traditionally involve manual interventions to disconnect cables, perform one or several tests, then reconnect the systems, usually during refueling outages occurring only every 18 to 24 months. This poses an operational burden that can be minimized by online testing or periodic connection to a coupler that may remain on the cable of interest or be clamped onto the cable without de-termination. This work investigates the adaptation of a clamshell inductive current coupler for either frequency domain reflectometry or spread-spectrum time domain reflectometry. The reflectometry test instrument injects a broad-band chirp or pseudo-noise signal onto a cable conductor and monitors for a reflected signal indicative of an impedance change caused by a damage condition. The instrument maximum input signal levels are typically 10 to 30 volts or less and the instruments will be damaged if subjected to 60 Hz power line voltages of 110, 220, or 480 VAC. One commercial spread-spectrum time domain reflectometry system has circuitry suitable for voltages up to 1 kV, but typical reflectometry tests are performed on de-energized cables. The clamshell inductive coupler provides >60 dB of 60 Hz attenuation with less than 10 dB loss in the 1-500 MHz test bandwidth of interest. An energized cable was successfully tested up to 6.7 kVp-p and frequency response plots imply that the tests could be extended to 10 kV or higher energized levels.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Laser Frequency Transverse Modulation Might Compensate for the Spectral Broadening Due to Large Electron Energy Spread in Thomson Sources

Compact laser plasma accelerators generate high-energy electron beams with increasing quality. When used in inverse Compton backscattering, however, the relatively large electron energy spread jeopardizes potential applications requiring small bandwidths. We present here a novel interaction scheme that allows us to compensate for the negative effects of the electron energy spread on the spectrum, by introducing a transverse spatial frequency modulation in the laser pulse. Such a laser chirp, together with a properly dispersed electron beam, can substantially reduce the broadening of the Compton bandwidth due to the electron energy spread. We show theoretical analysis and numerical simulations for hard X-ray Thomson sources based on laser plasma accelerators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Scalable, High-Efficiency, Low-Energy-Spread Laser Wakefield Accelerator Using a Tri-Plateau Plasma Channel

The emergence of multi-petawatt laser facilities is expected to push forward the maximum energy gain that can be achieved in a single stage of a laser wakefield acceleration (LWFA) to tens of giga-electron volts, which begs the question—is it likely to impact particle physics by providing a truly compact particle collider? Colliders have very stringent requirements on beam energy, acceleration efficiency, and beam quality. In this article, we propose an LWFA scheme that can for the first time simultaneously achieve hitherto unrealized acceleration efficiency from the laser to the electron beam of >20% and a sub-1% energy spread using a stepwise plasma structure and a nonlinearly chirped laser pulse. Three-dimensional high-fidelity simulations show that the nonlinear chirp can effectively mitigate the laser waveform distortion and lengthen the acceleration distance. This, combined with an interstage rephasing process in the stepwise plasma, can triple the beam energy gain compared to that in a uniform plasma for a fixed laser energy, thereby dramatically increasing the efficiency. A dynamic beam loading effect can almost perfectly cancel the energy chirp that arises during the acceleration, leading to the sub-percent energy spread. This scheme is highly scalable and can be applied to petawatt LWFA scenarios. Scaling laws are obtained, which suggest that electron beams with parameters relevant for a Higgs factory could be reached with the proposed high-efficiency, low-energy-spread scheme.

43 PARTICLE ACCELERATORS↗
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 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 OSTI2020

High-Throughput Characterization of (Fe x Co 1–x ) 3 O 4 Thin-Film Composition Spreads

In this study, thin-film continuous composition spreads of Fe–Co–O were fabricated by reactive cosputtering from elemental Fe and Co targets in reactive Ar/O 2 atmosphere using deposition temperatures ranging from 300 to 700 °C. Fused silica and platinized Si/SiO 2 strips were used as substrates. Ti and Ta were investigated as adhesion layer for Pt and the fabrication of the Fe–Co–O films. The thin-film composition spreads were characterized by high-throughput electron-dispersive X-ray spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, atomic force microscopy, scanning electron microscopy, and optical transmission spectroscopy. The Fe-content ranged from 28 to 72 at. %. The spinel phases Fe 2 CoO 4 and FeCo 2 O 4 could be synthesized and stabilized at all deposition temperatures with a continuous variation in spinel composition in between. The dependence of the film surface microstructure on the deposition temperature and the composition was mapped. Moreover, the band gap values, ranging from 2.41 eV for FeCo 2 O 4 to 2.74 eV for Fe 2 CoO 4 , show a continuous variation with the composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

54 ENVIRONMENTAL SCIENCES↗