SEARCH · Search NASA

Results for “timescale”

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.

SourceResearch connectionFrom yearThrough year

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

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Comparison of reduced model predictions for divertor detachment onset and reattachment timescales in ASDEX Upgrade and JET experiments

Building on prior analysis of ASDEX Upgrade (AUG) experiments (Henderson et al 2023 Nucl. Fusion63 086024), this study compares simple analytical formula predictions for divertor detachment onset and reattachment timescales in JET experiments. Detachment onset primarily scales with divertor neutral pressure, impurity concentration, power directed to the targets, machine size, and integral perpendicular power decay length. JET experiments, focusing on seeding mixtures of Ne and Ar, align with the detachment onset predictions. Radiation efficiencies among the impurities show good agreement with the model predictions, contrasting with AUG observations which suggested higher efficiency for Ar and lower efficiency for Ne. The time taken to re-ionise the neutral volume in front of the outer target in fully detached divertor conditions was measured following both abrupt increases in injected neutral beam power and, separately, cutting of the impurity gas flow. Re-ionisation of the neutrals occurs within approximately 1 s on JET, which aligns with the simple model prediction derived from AUG data. While the AUG results are not new, their comparison with the JET results enhances understanding, reinforcing confidence in using simple models to predict future reactor scenarios.

JET↗

DOE OSTI2021

Experimental study of extended timescale dynamics of a plasma wakefield driven by a self-modulated proton bunch

Plasma wakefield dynamics over timescales up to 800 ps, approximately 100 plasma periods, are studied experimentally at the Advanced Wakefield Experiment (AWAKE). The development of the longitudinal wakefield amplitude driven by a self-modulated proton bunch is measured using the external injection of witness electrons that sample the fields. In simulation, resonant excitation of the wakefield causes plasma electron trajectory crossing, resulting in the development of a potential outside the plasma boundary as electrons are transversely ejected. Trends consistent with the presence of this potential are experimentally measured and their dependence on wakefield amplitude are studied via seed laser timing scans and electron injection delay scans.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Relaxation timescales and electron-phonon coupling in optically pumped $\mathrm{YBa_2Cu_3O_{6+\mathcal{x}}}$ revealed by time-resolved Raman scattering

Time-resolved measurements provide a new way to disentangle complex interactions in quantum materials due to their different timescales. We used pump-probe Raman scattering to investigate the apical oxygen vibration in $\mathrm{YBa_2Cu_3O_{6+\mathcal{x}}}$ under nonequilibrium conditions. Time dependence of the phonon population demonstrated strong electron-phonon coupling. Most importantly, the phonon shifts to a higher energy due to transient smearing of the Fermi surface in a remarkable agreement with diagrammatic theory. Here we also discuss insights into photoinduced superconductivity reported at lower doping that follow from these results.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Millisecond timescale reactions observed via X-ray spectroscopy in a 3D microfabricated fused silica mixer

Determination of electronic structures during chemical reactions remains challenging in studies which involve reactions in the millisecond timescale, toxic chemicals, and/or anaerobic conditions. Here, a three-dimensionally (3D) microfabricated microfluidic mixer platform that is compatible with time-resolved X-ray absorption and emission spectroscopy (XAS and XES, respectively) is presented. This platform, to initiate reactions and study their progression, mixes a high flow rate (0.50–1.5 ml min –1 ) sheath stream with a low-flow-rate (5–90 µl min –1 ) sample stream within a monolithic fused silica chip. The chip geometry enables hydrodynamic focusing of the sample stream in 3D and sample widths as small as 5 µm. The chip is also connected to a polyimide capillary downstream to enable sample stream deceleration, expansion, and X-ray detection. In this capillary, sample widths of 50 µm are demonstrated. Further, convection–diffusion-reaction models of the mixer are presented. The models are experimentally validated using confocal epifluorescence microscopy and XAS/XES measurements of a ferricyanide and ascorbic acid reaction. The models additionally enable prediction of the residence time and residence time uncertainty of reactive species as well as mixing times. Residence times (from initiation of mixing to the point of X-ray detection) during sample stream expansion as small as 2.1 ± 0.3 ms are also demonstrated. Importantly, an exploration of the mixer operational space reveals a theoretical minimum mixing time of 0.91 ms. The proposed platform is applicable to the determination of the electronic structure of conventionally inaccessible reaction intermediates.

3D microfabrication↗

DOE OSTI2024

Multi-Timescale Optimal Operation Framework for Integrated Economic and Reliability Analysis of Hybrid Power Plants

This paper introduces a hierarchical modeling framework for hybrid power plants (HPP) to facilitate the operation of HPP in power systems similar to conventional generators (Congens) in the integrated multi-timescale optimal operation framework. To consider the uncertainties of HPP renewable power in the day-ahead scheduling, distributionally robust optimization (DRO) is used. To ensure that the state-of-charge (SOC) of energy storage systems in HPPs aligns closely with the planned value for long-term reliability, real-time SOC management is incorporated. In addition, an adjustable real-time control is designed for the robust delivery of HPP real-time services. Case studies performed on a revised IEEE 39-bus system demonstrate the effectiveness of the proposed framework for HPP operation. Simulation results highlight that the proposed framework not only can help operators schedule HPP similar to Congens in varying weather conditions but can also maintain the frequency reliability of the system.

frequency stability↗

DOE OSTI2020

Quantifying Solar PV Variability at Multiple Timescales for Power Systems Studies: Preprint

Increasing penetration of solar photovoltaics (PV) has concerned power system operators about their ability to balance load and generation over multiple timescales and maintain acceptable frequency profile because of the variability and uncertainty associated with solar PV. This paper focuses on developing metrics to quantify solar PV variability at multiple temporal scales ranging from seconds to an hour to help power system operators and planners better understand and account for solar PV variability under high solar PV penetration. Fourier coefficients of solar irradiation spectrum and average size of solar irradiation ramps over a day are the two metrics that are used to quantity the variability. It is shown that by using the two metrics the days with highest and lowest solar irradiation variability can be identified, which is useful information for operations planning or long-term power system planning studies. The key findings of the paper are (i) single sensor-based variability quantification can significantly exaggerate the variability of a solar PV plant, particularly at seconds to 1-min temporal resolution, (ii) at 1-minute or lower temporal resolutions, single sensor-based variability quantification of an entire plant can be fairly accurate, with the accuracy increasing as the temporal resolution reduces from 1-minute to 1-hour, (iii) at each 1-minute and lower temporal resolutions, maximum solar irradiation ramps appear to be independent of the geographical location of the sensor, and (iv) significant reduction in solar PV plant variability over a region with multiple plants is possible at all temporal scales, but more high quality, high temporal resolution data is needed to quantify the reduction with high confidence.

photovoltaics↗

DOE OSTI2022

Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

42 ENGINEERING↗

DOE OSTI2022

Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems

The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meters can be used for many applications, including distribution system state estimation (DSSE). However, these measurements are typically sampled at different rates and could be intermittent due to losses during the aggregation process. These multi timescale measurements should be reconciled in real-time to perform accurate grid monitoring. This paper tackles this problem by formulating a recursive multi-task Gaussian process (RGP-G) approach that sequentially aggregates sensor measurements. Specifically, we formulate a recursive multi-task GP with and without network connectivity information to reconcile the multi time-scale measurements in distribution systems. Here, the proposed framework is capable of aggregating the multi-time scale measurements batch-wise or in real-time. Following the aggregation of the multi time-scale measurements, the spatial states of the consistent time-series are estimated using matrix completion based DSSE approach. Simulation results on IEEE 37 and IEEE 123 bus test systems illustrate the efficiency of the proposed methods from the standpoint of both multi time-scale data aggregation and DSSE.

42 ENGINEERING↗

DOE OSTI2021

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid

Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMGs are challenged with limited resource availability, absence of robust grid support, and heightened demand-supply uncertainty. Here, this paper proposes a secure and adaptive three-stage hierarchical multi-timescale framework for scheduling and real-time (RT) dispatch of CMGs with hybrid PV systems to address these challenges. The framework enables the CMG to dynamically expand its boundary to support the neighboring grid sections and is adaptive to the changing forecast error impacts. The first stage solves a stochastic extended duration scheduling (EDS) problem to obtain referral plans for optimal resource rationing. The intermediate near-real-time (NRT) scheduling stage updates the EDS schedule closer to the dispatch time using new obtained forecasts, followed by the RT dispatch stage. To make the decisions more secure and robust against forecast errors, a novel concept called delayed recourse is designed. The approach is evaluated via numerical simulations on a modified IEEE 123-bus system and validated using OpenDSS and hardware-in-loop simulations. The results show superior performance in maximizing load supply and continuous secure distribution network operation under different operating scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

The importance of long-timescale simulations for driven systems: An example of He bubble growth at a W GB

Accelerated Molecular Dynamics (AMD) is used to study complex systems under realistic conditions by extending the timescales accessible by Molecular Dynamics. However, some studies rely instead on driving atomic systems harder with higher temperature, faster growth, etc. Here, we study He bubble growth at a W grain boundary as an illustration of harnessing AMD methods to avoid consequences of over-driving the system. The growth mechanisms observed for a He bubble grown under realistic conditions are compared to bubbles-grown orders of magnitude faster, at rates typical of conventional molecular dynamics simulations. We find that progressive growth mechanisms and bubble structures depend on the rate at which the bubble is grown providing further evidence that care must be taken when simulating the dynamics of driven systems such as this one.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Machine learning to extend and understand the sources and limits of water cycle predictability on subseasonal-to-decadal timescales in the Earth system

This white paper provides initial insight on how artificial intelligence (AI) and machine learning (ML), including interpretability and explainable AI (XAI) methods, can be leveraged to glean insight from complex data for a paradigm-changing improvement in Earth system predictability on subseasonal-to-seasonal (S2S) and seasonal-to-decadal (S2D) timescales. The application of AI to extend and improve predictability, in combination with causal inference and uncertainty quantification, could lead to a transformative understanding of the integrative water cycle and associated extremes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Why Is the Range of Timescale So Wide in Glass-Forming Liquid?

The viscosity and the relaxation time of a glass-forming liquid vary over 15 orders of magnitude before the liquid freezes into a glass. The rate of the change with temperature is characterized by liquid fragility. The mechanism of such a spectacular behavior and the origin of fragility have long been discussed, but it remains unresolved because of the difficulty of carrying out experiments and constructing theories that bridge over a wide timescale from atomic (ps) to bulk (minutes). Through the x-ray diffraction measurement and molecular dynamics simulation for metallic liquids we suggest that large changes in viscosity can be caused by relatively small changes in the structural coherence which characterizes the medium-range order. Here the structural coherence does not imply that of atomic-scale structure, but it relates to the coarse-grained density fluctuations represented by the peaks in the pair-distribution function (PDF) beyond the nearest neighbors. The coherence length is related to fragility and increases with decreasing temperature, and it diverges only at a negative temperature. This analysis is compared with several current theories which predict a phase transition near the glass transition temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

OGLE-2016-BLG-1227L: A Wide-separation Planet from a Very Short-timescale Microlensing Event

We present the analysis of the microlensing event OGLE-2016-BLG-1227. The light curve of this short-duration event appears to be a single-lens event affected by severe finite-source effects. Analysis of the light curve based on a single-lens single-source (1L1S) model yields very small values of the event timescale, t{sub E}∼3.5 days, and the angular Einstein radius, θ{sub E}∼0.009 mas, making the lens a candidate of a free-floating planet. Close inspection reveals that the 1L1S solution leaves small residuals with an amplitude of ΔI ≲ 0.03 mag. We find that the residuals are explained by the existence of an additional widely separated heavier lens component, indicating that the lens is a wide-separation planetary system rather than a free-floating planet. From Bayesian analysis, it is estimated that the planet has a mass of M{sub p}=0.79{sub −0.39}{sup +1.30} M{sub J} and it is orbiting a low-mass host star with a mass of M{sub host}=0.10{sub −0.05}{sup +0.17} M{sub ⊙} located with a projected separation of a{sub ⊥}=3.4{sub −1.0}{sup +2.1} au. The planetary system is located in the Galactic bulge with a line-of-sight separation from the source star of D{sub LS}=1.21{sub −0.63}{sup +0.96} kpc. The event shows that there is a range of deviations in the signatures of host stars for apparently isolated planetary lensing events and that it is possible to identify a host even when a deviation is subtle.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales $\textit{O}$ (10 0–6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions $\textit{O}$ (10 0–2 years) precisely within longer $\textit{O}$ (10 3–6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution $\textit{O}$ (10 0–2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution $\textit{O}$ (10 3–6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ~ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

Timescales for planetary accretion and the structure of the protoplanetary disk

No self-consistent scenario for all stages of planetary accretion which satisfies observational constraints currently exists. An attempt is accordingly made here to resolve the timescale problems and to outline a planet formation scenario consistent with current theories of star formation as well as related models of the protoplanetary disk. For accretion to have proceeded in the manner presently hypothesized, the surface mass density of planetessimals would have had to to be relatively uniform in the Venus-Jupiter region of the protoplanetary disk, consistent with viscous accretion disk models of the solar nebula. The outer regions of the nebula would still have contained enough solid matter to account for the growth of Uranus and Neptune in 5 to 500 million years.

Lissauer, Jack J.↗

NASA NTRS1990

Calibration of the C-14 timescale over the past 30,000 years using mass spectrometric U-Th ages from Barbados corals

Uranium-thorium ages obtained by mass spectrometry from corals raised off the island of Barbados confirm the high precision of this technique over at least the past 30,000 years. Comparison of the U-Th ages with C-14 ages obtained on the Holocene samples shows that the U-Th ages are accurate, because they accord with the dendrochronological calibration. Before 9,000 yr BP, the C-14 ages are systematically younger than the U-Th ages, with a maximum difference of about 3500 yr at about 20,000 yr BP. The U-Th technique thus provides a way of calibrating the radiocarbon timescale beyond the range of dendrochronological calibration.

Bard, Edouard↗