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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluating the Lagrangian Evolution of Subtropical Low Clouds in GCMs Using Observations: Mean Evolution, Time Scales, and Responses to Predictors

In this work, a Lagrangian framework is developed to show the daily-scale time evolution of low clouds over the eastern subtropical oceans. An identical framework is applied to two general circulation models (GCMs): the CAM5 and UKMET and a set of satellite observations. This approach follows thousands of parcels as they advect downwind in the subtropical trade winds, comparing cloud evolution in time and space. This study tracks cloud cover, in-cloud liquid water path (CLWP), droplet concentration $N_d$, planetary boundary layer (PBL) depth, and rain rate as clouds transition from regions with predominately stratiform clouds to regions containing mostly trade cumulus. The two models generate fewer clouds with greater $N_d$ relative to observations. Models show stronger Lagrangian cloud cover decline and greater PBL deepening when compared with observations. In comparing frequency distributions of cloud variables over time, it is seen that models generate increasing frequencies of nearly clear conditions at the expense of overcast conditions, whereas observations show transitions from overcast to cloud amounts between 50% and 90%. Lagrangian decorrelation time scales ($\mathcal{e}$-folding time $\tau$) of cloud cover and CLWP are between 11 and 19 h for models and observations, although they are a bit shorter for models. A Lagrangian framework applied here resolves and compares the time evolution of cloud systems as they adjust to environmental perturbations in models and observations. Increasing subsidence in the overlying troposphere leads to declining cloud cover, CLWP, PBL depth, and rain rates in models and observations. Modeled cloud responses to other meteorological variables are less consistent with observations, suggesting a need for continuing mechanical improvements in GCMs.

58 GEOSCIENCES↗
DOE OSTI2022

Quenching time-scales in the IllustrisTNG simulation

ABSTRACT The time-scales for galaxy quenching offer clues to its underlying physical drivers. We investigate central galaxy quenching time-scales in the IllustrisTNG 100-1 simulation, their evolution over time, and the pre-quenching properties of galaxies that predict their quenching time-scales. Defining quenching duration τq as the time between crossing specific star formation rate (sSFR) thresholds, we find that ${\sim} 40{{\ \rm per\ cent}}$ of galaxies quench rapidly with τq < 1 Gyr, but a substantial tail of galaxies can take up to 10 Gyr to quench. Furthermore, 29 per cent of galaxies that left the star-forming main sequence (SFMS) more than 2 Gyr ago never fully quench by z = 0. While the median τq is fairly constant with epoch, the rate of galaxies leaving the SFMS increases steadily over cosmic time, with the rate of slow quenchers being dominant around z ∼ 2–0.7. Compared to fast quenchers (τq < 1 Gyr), slow-quenching galaxies (τq > 1 Gyr) were more massive, had more massive black holes, had larger stellar radii, and accreted gas with higher specific angular momentum (AM) prior to quenching. These properties evolve little by z = 0, except for the accreting gas AM for fast quenchers, which reaches the same high AM as the gas in slow quenchers. By z = 0, slow quenchers also have residual star formation in extended gas rings. Using the expected relationship between stellar age gradient and τq for inside-out quenching we find agreement with Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) integral field unit (IFU) observations. Our results suggest the accreting gas AM and potential well depth determine the quenching time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Exploring the parameter space of MagLIF implosions using similarity scaling. III. Rise-time scaling

Magnetized liner inertial fusion (MagLIF) is a z-pinch magneto-inertial-fusion concept studied at the Z Pulsed Power Facility of Sandia National Laboratories. Two important metrics characterizing current delivery to a z-pinch load are the peak current and the current-rise time, which is roughly the time interval to reach the peak current. It is known that, when driving a z-pinch load with a longer current-rise time, the performance of the z-pinch decreases. However, a theory to understand and quantify this effect is still lacking. Here, in this paper, we utilize a framework based on similarity scaling to analytically investigate the variations in the performance of MagLIF loads when varying the current-rise time, or equivalently, the implosion timescale. To maintain similarity between the implosions, we provide scaling prescriptions of experimental input parameters defining a MagLIF load and derive the expected scaling laws for stagnation conditions and for various performance metrics. We compare predictions of the theory to 2D numerical simulations using the radiation, magneto-hydrodynamic code hydra. For several metrics, we find acceptable agreement between the theory and simulations. Our results show that the voltage φload near the MagLIF load follows a weak scaling law φload ∝$t_{φ}^{-0.12}$ with respect to the characteristic timescale t φ of the voltage source, instead of the ideal φload ∝$t_{φ}^{-1}$ scaling. This occurs because the imploding height of the MagLIF load must increase to preserve end losses. As a consequence of the longer imploding liners, the required total laser preheat energy and delivered electric energy increase. Overall, this study helps understand the trade-offs of the MagLIF design space when considering future pulsed-power generators with shorter and longer current-rise times.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗
DOE OSTI2022

Benchmarking Simulated Precipitation Variability Amplitude across Time Scales

Here, objective performance metrics that measure precipitation variability across time scales from subdaily to interannual are presented and applied to Historical simulations of Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. Three satellite-based precipitation estimates (IMERG, TRMM, and CMORPH) are used as reference data. We apply two independent methods to estimate temporal variability of precipitation and compare the consistency in their results. The first method is derived from power spectra analysis of 3-hourly precipitation, measuring forced variability by solar insolation (diurnal and annual cycles) and internal variability at different time scales (subdaily, synoptic, subseasonal, seasonal, and interannual). The second method is based on time averaging and facilitates estimating the seasonality of subdaily variability. Supporting the robustness of our metric, we find a near equivalence between the results obtained from the two methods when examining simulated-to-observed ratios over large domains (global, tropics, extratropics, land, or ocean). Additionally, we demonstrate that our model evaluation is not very sensitive to the discrepancies between observations. Our results reveal that CMIP5 and CMIP6 models in general overestimate the forced variability while they underestimate the internal variability, especially in the tropical ocean and higher-frequency variability. The underestimation of subdaily variability is consistent across different seasons. The internal variability is overall improved in CMIP6, but remains underestimated, and there is little evidence of improvement in forced variability. Increased horizontal resolution results in some improvement of internal variability at subdaily and synoptic time scales, but not at longer time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multi-Time Scale Coordinated Control and Scheduling of Inverter-Based TCLs With Variable Wind Generation

To address microgrid tie flow errors caused by wind generation variability, here we propose and develop a multi-time scale coordinated control and scheduling strategy for inverter-based thermostatically controlled loads (TCLs). First, in hour-time scale, inverter-based TCLs with adjusting temperature set-point are modeled as virtual generators to compensate tie flow deviations in the day-ahead plan. Next, in minute-time scale, virtual batteries representing operating behaviors of inverter-based TCLs with frequency control are scheduled determined by the control of virtual generators in hour-time scale. The virtual batteries are scheduled to smooth out tie flow errors corresponding to day-ahead plan and hour-time scale schedules. The multi-time scale control methods are coordinated to employ the response potential of inverter-based TCLs and response curve-based methods are proposed to control inverter-based TCLs considering the customer privacy. The multi-time scale stochastic schedules which are based on response curves of inverter-based TCLs are coordinated to accommodate wind generation variability. Simulation results demonstrate that the microgrid tie flow errors are effectively mitigated by the proposed multi-time scale coordinated control and scheduling of inverter-based TCLs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Time Scale Dependence of the Meridional Coherence of the Atlantic Meridional Overturning Circulation

The Atlantic Meridional Overturning Circulation (AMOC) variability is suggested to be incoherent between the subpolar and subtropical gyres in the Atlantic on interannual and even decadal time scales, questioning the representativeness of AMOC variability at a single latitude in modern observation and paleoreconstruction. Paleoreconstructions of the Florida Current transport suggest that Florida Current variability is associated with the AMOC on the millennial time scale, but the Rapid Climate Change (RAPID) mooring array suggests a weak correlation between the Florida Current and the AMOC. In this study, we investigate the meridional coherence of AMOC variability and the relationship between the Florida Current variability and the AMOC variability on different time scales in a transient 20,000-year simulation. We find that with the increase of time scales, the meridional coherence of the AMOC increases. On decadal and longer time scales, the coherent subtropical and subpolar AMOC is caused by the coherent buoyancy forcing in the subpolar gyre. Also, the Florida Current transport is highly correlated with AMOC variability on decadal and longer time scales, suggesting that observations of the Florida Current can be used to indicate AMOC variability on long time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Storm and Annual Time Scale Hydrological Data for the Russian River Watershed 1996-2022

These files contains observed and simulated hydrological data (discharge, precipitation) that have been aggregated to the storm-event scale and to the annual time scale for the Russian River Watershed (RRW), California. Observed data are obtained from 12 different USGS hydrological stations located throughout the watershed, and discharge is simulated using the GR5H hourly hydrological model. Precipitation data are obtained from the NASA NLDAS NOAH Community Land Surface Model. All simulated and observed discharge are aggregated to the storm and annual time scales. We investigated changes in watershed hydrological conditions in the Russian River Watershed, a Mediterranean, drought prone, wildfire-adapted ecosystem, following eleven wildfires that occurred from 2017-2020. We ask two research questions: 1) How do interacting wildfire events, drought, and atmospheric rivers impact hydrological conditions of the watershed and in particular streamflow?, and 2) What percentage of new and/or cumulative wildfire disturbance is required to initiate hydrological change? We hypothesize that sub-watersheds of the RRW Mediterranean ecoregion have not burned beyond an intrinsic, and still unknown, threshold required to initiate change. Using a series of paired burned/unburned catchments nested within the larger watershed, we examined temporal and spatial patterns of pre-and-post wildfire water hydrology using a rainfall runoff hydrological model compared with data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machine Learning-Based Model Predictive Control of Two-Time-Scale Systems

In this study, we present a general form of nonlinear two-time-scale systems, where singular perturbation analysis is used to separate the dynamics of the slow and fast subsystems. Machine learning techniques are utilized to approximate the dynamics of both subsystems. Specifically, a recurrent neural network (RNN) and a feedforward neural network (FNN) are used to predict the slow and fast state vectors, respectively. Moreover, we investigate the generalization error bounds for these machine learning models approximating the dynamics of two-time-scale systems. Next, under the assumption that the fast states are asymptotically stable, our focus shifts toward designing a Lyapunov-based model predictive control (LMPC) scheme that exclusively employs the RNN to predict the dynamics of the slow states. Additionally, we derive sufficient conditions to guarantee the closed-loop stability of the system under the sample-and-hold implementation of the controller. A nonlinear chemical process example is used to demonstrate the theory. In particular, two RNN models are constructed: one to model the full two-time-scale system and the other to predict solely the slow state vector. Both models are integrated within the LMPC scheme, and we compare their closed-loop performance while assessing the computational time required to execute the LMPC optimization problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The variability structure function of the highest luminosity quasars on short time-scales

ABSTRACT The stochastic photometric variability of quasars is known to follow a random-walk phenomenology on emission time-scales of months to years. Some high-cadence rest-frame optical monitoring in the past has hinted at a suppression of variability amplitudes on shorter time-scales of a few days or weeks, opening the question of what drives the suppression and how it might scale with quasar properties. Here, we study a few thousand of the highest luminosity quasars in the sky, mostly in the luminosity range of $L_{\rm bol}$$=[46.4, 47.3]$ and redshift range of $z=[0.7, 2.4]$. We use a data set from the NASA/Asteroid Terrestrial-impact Last Alert System facility with nightly cadence, weather permitting, which has been used before to quantify strong regularity in longer term rest-frame-UV variability. As we focus on a careful treatment of short time-scales across the sample, we find that a linear function is sufficient to describe the UV variability structure function. Although the result can not rule out the existence of breaks in some groups completely, a simpler model is usually favoured under this circumstance. In conclusion, the data are consistent with a single-slope random walk across rest-frame time-scales of $\Delta t=[10, 250]$ d.

Tang, Ji-Jia (ORCID:0000000218600886)↗
DOE OSTI2024

Spatially resolved microlensing time-scale distributions across the Galactic bulge with the VVV survey

ABSTRACT We analyse 1602 microlensing events found in the VISTA Variables in the Via Lactea (VVV) near-infrared (NIR) survey data. We obtain spatially resolved, efficiency-corrected time-scale distributions across the Galactic bulge (|ℓ| < 10°, |b| < 5°), using a Bayesian hierarchical model. Spatially resolved peaks and means of the time-scale distributions, along with their marginal distributions in strips of longitude and latitude, are in agreement at a 1σ level with predictions based on the Besançon model of the Galaxy. We find that the event time-scales in the central bulge fields (|ℓ| < 5°) are on average shorter than the non-central (|ℓ| > 5°) fields, with the average peak of the lognormal time-scale distribution at 23.6 ± 1.9 d for the central fields and 29.0 ± 3.0 d for the non-central fields. Our ability to probe the structure of the bulge with this sample of NIR microlensing events is limited by the VVV survey’s sparse cadence and relatively small number of detected microlensing events compared to dedicated optical surveys. Looking forward to future surveys, we investigate the capability of the Roman telescope to detect spatially resolved asymmetries in the time-scale distributions. We propose two pairs of Roman fields, centred on (ℓ = ±9, 5°, b = −0.125°) and (ℓ = −5°, b = ±1.375°) as good targets to measure the asymmetry in longitude and latitude, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Time scales for advection and (de)leptonization in a collapsar [Slides]

Characteristic time scales of leptonization (τ + ), deleptonization (τ – ), and fluid motion (τ a ) in a disk of hot gas accreting on to a black hole formed after a failed supernova. These time scales are set by neutrino emission, absorption, and magnetohydrodynamic turbulence, highlighting the complex interplay between the four forces of nature in these enigmatic systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Universal time scalings of sensitivity in Markovian quantum metrology

Assuming Markovian time evolution of a quantum sensing system, we study the general characterization of the optimal sensitivity scalings with time, under most general quantum control protocols. We allow the estimated parameter to influence both the Hamiltonian as well as the dissipative part of the quantum master equation and focus on the asymptotic-time along with the short-time sensitivity scalings. We find that via simple algebraic conditions (in terms of the Hamiltonian, the jump operators as well as their parameter derivatives), one can characterize the four classes of metrological models that represent: quadratic-linear, quadratic-quadratic, linear-linear, and linear-quadratic time scalings. We also investigate the relevant time scales on which the transition between the two regimes appears. Additionally, we provide universal numerical methods to obtain quantitative bounds on sensitivity that are the tightest that exist in the literature. Simplicity and universality of our results make it suitable for diverse applications in quantum metrology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Constraining quenching time-scales in galaxy clusters by forward-modelling stellar ages and quiescent fractions in projected phase space

We forward-model mass-weighted stellar ages (MWAs) and quiescent fractions (f Q ) in projected phase space (PPS), using data from the Sloan Digital Sky Survey, to jointly constrain an infall quenching model for galaxies in log (M vir /M ⊙ ) > 14 galaxy clusters at z ∼ 0. We find the average deviation in MWA from the MWA–M⋆ relation depends on position in PPS, with a maximum difference between the inner cluster and infalling interloper galaxies of ∼1 Gyr. Our model employs infall information from N-body simulations and stochastic star-formation histories from the universemachine model. We find total quenching times of t Q = 3.7 ± 0.4 Gyr and t Q = 4.0 ± 0.2 Gyr after first pericentre, for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively. By using MWAs, we break the degeneracy in time of quenching onset and time-scale of star formation rate (SFR) decline. We find that time of quenching onset relative to pericentre is $t_{\mathrm{delay}}=3.5^{+0.6}_{-0.9}$ Gyr and $t_{\mathrm{delay}}=-0.3^{+0.8}_{-1.0}$ Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively, and exponential SFR suppression time-scales are τenv ≤ 1.0 Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 galaxies and τenv ∼ 2.3 Gyr for 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies. Stochastic star formation histories remove the need for rapid infall quenching to maintain the bimodality in the SFR of cluster galaxies; the depth of the green valley prefers quenching onsets close to first pericentre and a longer quenching envelope, in slight tension with the MWA-driven results. Taken together these results suggest that quenching begins close to, or just after pericentre, but the time-scale for quenching to be fully complete is much longer and therefore ram-pressure stripping is not complete on first pericentric passage.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Guidance for Monitoring Passive Groundwater Remedies Over Extended Time Scales

Passive remediation can be appropriate where natural processes and actions such as institutional controls mitigate exposure to contaminated groundwater, achieving remedial action objectives and protectiveness of human health and the environment. Monitored natural attenuation (MNA) is a prevalent passive remediation strategy supported by a regulatory framework and monitoring design guidance. However, long-term passive remedies are usually selected in combination with at least one active remedy, such as source removal, in situ treatment, or pump-and-treat, functioning as a complementary method for achieving remediation objectives and meeting the applicable statutory and regulatory requirements. However, MNA and existing monitoring guidance primarily target situations where the remedial action objectives are met within a few decades. When time scales for passive remediation extend to many decades (50 years or more), a corresponding change in monitoring strategy is needed to adapt to the extended time scale. This document provides guidance for implementing an extended-scale monitoring (ESM) approach appropriate for long-duration passive remediation. Extended-scale is defined in this document with respect to time (i.e., a long duration of remediation) and a large enough physical scale such that downstream receptors will not be impacted within the remediation timeframe. ESM applies to slow-moving groundwater contaminant plumes and emphasizes monitoring primarily for potential exposure pathways. For this approach, the primary monitoring objective is to demonstrate that the plume diminishes before reaching the receptor zone or point of compliance and/or a receptor does not receive concentrations above the compliance limit. While the overall objectives of protecting human health and the environment are the same as for plumes where remediation can occur over a shorter time period, the time scales between decisions are longer and the dynamics of plume evolution are slower. To this end, a scenario-based strategy is described for different plume and source conditions, defining a containment and receptor zones. The containment zone is the area where the risk of exposure to groundwater contamination can be mitigated (e.g., through institutional controls) during the remediation time period. The receptor zone is defined as the area where exposure to groundwater contamination cannot be mitigated and compliance concentration standards must be met. Within the containment zone, slow plume migration may occur, leading to concentrations that exceed compliance standards. However, where distance to the receptor zone is large relative to plume migration and attenuation rate, this approach can be protective of the receptor zone. Selection of a long-duration passive remedy needs to be based on sufficient understanding of contaminant sources, hydrogeology, and contaminant plumes. A strong technical basis, supported by predictive analysis, is recommended to substantiate that contamination is expected to stay within the containment zone during the active remediation and attainment phase of the remedy, and diminish to meet compliance standards within the extended timeframe prior to reaching the receptor zone (e.g., many decades or even centuries). The ESM approach is based on verification of plume behavior and not on detailed plume dynamics. Monitoring is conducted to confirm expected behavior with an emphasis on exposure pathways to verify that plumes remain contained in areas where the protectiveness objectives can be met. ESM should not be adopted if there is significant risk of the plume extending beyond the containment zone. Given the slow movement within the containment zone, less frequent sampling is required relative to approaches used for conventional-scale remediation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Assessing the sequestration time scales of some ocean-based carbon dioxide reduction strategies

Abstract Ocean-based carbon dioxide (CO 2 ) removal (CDR) strategies are an important part of the portfolio of approaches needed to achieve negative greenhouse gas emissions. Many ocean-based CDR strategies rely on injecting CO 2 or organic carbon (that will eventually become CO 2 ) into the ocean interior, or enhancing the ocean’s biological pump. These approaches will not result in permanent sequestration, because ocean currents will eventually return the injected CO 2 back to the surface, where it will be brought into equilibrium with the atmosphere. Here, a model of steady state global ocean circulation and mixing is used to assess the time scales over which CO 2 injected in the ocean interior remains sequestered from the atmosphere. There will be a distribution of sequestration times for any single discharge location due to the infinite number of pathways connecting a location at depth with the sea surface. The resulting probability distribution is highly skewed with a long tail of very long transit times, making mean sequestration times much longer than typical time scales. Deeper discharge locations will sequester purposefully injected CO 2 much longer than shallower ones and median sequestration times are typically decades to centuries, and approach 1000 years in the deep North Pacific. Large differences in sequestration times occur both within and between the major ocean basins, with the Pacific and Indian basins generally having longer sequestration times than the Atlantic and Southern Oceans. Assessments made over a 50 year time horizon illustrates that most of the injected carbon will be retained for injection depths greater than 1000 m, with several geographic exceptions such as the Western North Atlantic. Ocean CDR strategies that increase upper ocean ecosystem productivity with the goal of exporting more carbon to depth will have mainly a short-term influence on atmospheric CO 2 levels because ∼70% will be transported back to the surface ocean within 50 years. The results presented here will help plan appropriate ocean CDR strategies that can help limit climate damage caused by fossil fuel CO 2 emissions.

54 ENVIRONMENTAL SCIENCES↗