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DOE OSTI2026

Quark flavor equilibration of the quark-gluon plasma

The early stage of a heavy-ion collision is marked by rapid entropy production and the transition from a gluon saturated initial condition to a plasma of quarks and gluons that evolves hydrodynamically. However, during the early times of the hydrodynamic evolution, the chemical composition of the QCD medium is still largely unknown. We present a study of quark chemical equilibration in the (Q)GP using a novel model of viscous hydrodynamic evolution in partial chemical equilibrium. Motivated by the success of gluon saturated initial condition models, we initialize the QCD medium as a completely gluon dominated state. Local quark production during the hydrodynamic phase is then simulated through the evolution of time-dependent fugacities for each independent quark flavor, with the timescales set as free parameters to compare different rates of equilibration. We present the results of complete heavy-ion collision simulations using this partial chemical equilibrium model, and show the effects on hadronic and electromagnetic observables. In particular, we show that the development of flow is sensitive to the equilibration timescale, providing an empirical way to probe the chemical equilibration of the QCD medium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2023

Scalable Hybrid Classification-Regression Solution for High-Frequency Nonintrusive Load Monitoring

Residential buildings with the ability to monitor and control their net-load (sum of load and generation) can provide valuable flexibility to power grid operators. We present a novel multiclass nonintrusive load monitoring (NILM) approach that enables effective net-load monitoring capabilities at high-frequency with minimal additional equipment and cost. The proposed machine learning based solution provides accurate multiclass state predictions while operating at a faster timescale (able to provide a prediction for each 60- Hz ac cycle used in US power grid) without relying on event-detection techniques. We also introduce an innovative hybrid classification-regression method that allows for the prediction of not only load on/off states but also individual load operating power levels. A test bed with eight residential appliances is used for validating the NILM approach. Results show that the overall method has high accuracy, good scaling and generalization properties.

feature extraction↗

DOE OSTI2025

Free-Space Optical Channel Turbulence Prediction: A Machine Learning Approach

Channel turbulence is a formidable obstacle for freespace optical (FSO) communication. Anticipation of turbulence levels is highly important for mitigating disruptions but has not been demonstrated without dedicated, auxiliary hardware. We show that machine learning (ML) can be applied to raw FSO data streams to rapidly predict channel turbulence levels with no additional sensing hardware. FSO was conducted through a controlled channel in the lab under six distinct turbulence levels, and the efficacy of using ML to classify turbulence levels was examined. ML-based turbulence level classification was found to be > 98% accurate with multiple ML training parameters. Classification effectiveness was found to depend on the timescale of changes between turbulence levels but converges when turbulence stabilizes over about a one minute timescale.

Zobaer Islam, Md [School of Electrical and Compute↗

DOE OSTI2021

Island Power Systems With High Levels of Inverter-Based Resources: Stability and Reliability Challenges

As many island power systems seek to integrate high levels of renewable energy, they face new challenges on top of the existing difficulties of operating an isolated grid. With their drastically declining cost, variable renewables, such as wind and photovoltaics (PVs), are increasingly being integrated into island grids to reduce the use of imported fuels. These deployments of renewable energy are dominated by PV and wind generators, which bring unique challenges of their own. While the integration issues span numerous timescales (from microseconds to many months), this article focuses on reliability and stability challenges on short timescales (microseconds to seconds). In other words, we seek to answer (to the extent that it is currently known) how to ensure the frequency and voltage stability in an island power system with very high instantaneous levels of wind and PVs. And because island power systems are often among the first to reach these very high instantaneous levels of wind and PV generation, we note that they are forging a path for larger interconnected power systems to follow.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2024

FPGA-Accelerated Range-Limited Molecular Dynamics

Long timescale Molecular Dynamics (MD) simulation of small molecules is crucial in drug design and basic science. To accelerate a small data set that is executed for a large number of iterations, high-efficiency is required. Recent work in this domain has demonstrated that among COTS devices only FPGA-centric clusters can scale beyond a few processors. The problem addressed here is that, as the number of on-chip processors has increased from fewer than 10 into the hundreds, previous intra-chip routing solutions are no longer viable. We find, however, that through various design innovations, high efficiency can be maintained. These include replacing the previous broadcast networks with ring-routing and then augmenting the rings with out-of-order and caching mechanisms. Others are adding a level of hierarchical filtering and memory recycling. Two novel optimized architectures emerge, together with a number of variations. These are validated, analyzed, and evaluated. We find that in the domain of interest speed-ups over GPUs are achieved. Finally, the potential impact is that this system promises to be the basis for scalable long timescale MD with commodity clusters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Cybersecurity Enhancement for Multi-Infeed High-Voltage DC Systems

Composed of multiple two-terminal high-voltage DC (HVDC) transmission systems, a multi-infeed HVDC (MIDC) system exchanges massive power among multiple asynchronous AC systems. However, as an intrinsically cyber-physical system, an MIDC system could suffer from cyber-attacks, leading to massive power mismatches in multiple AC systems, and resulting in catastrophic consequences. Since the sequential responses of an MIDC system and interconnected AC systems are in different timescales, this paper first establishes a two-timescale model to evaluate the sequential impacts caused by cyber-attacks. Then, an event-triggered cyber-defense strategy is proposed to enhance the cybersecurity of an MIDC system by mitigating multiple non-simultaneous cyber-attacks. Whenever new cyber-attack events occur, the proposed cyber-defense strategy, which is mathematically modeled as a mixed-integer quadratic programming problem, is executed on-line and updated in an event-triggered manner. Here, simulation results on an MIDC system demonstrate that the low-cost and almost blind cyber-attacks can cause severe frequency deviations, and the proposed strategy can mitigate multi-cyber-attacks effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Co-scheduling Ensembles of In Situ Workflows

Molecular dynamics (MD) simulations are widely used to study large-scale molecular systems. HPC systems are ideal platforms to run these studies, however, reaching the necessary simulation timescale to detect rare processes is challenging, even with modern supercomputers. To overcome the timescale limitation, the simulation of a long MD trajectory is replaced by multiple short-range simulations that are executed simultaneously in an ensemble of simulations. Analyses are usually co-scheduled with these simulations to efficiently process large volumes of data generated by the simulations at runtime, thanks to in situ techniques. Executing a workflow ensemble of simulations and their in situ analyses requires efficient co- scheduling strategies and sophisticated management of computational resources so that they are not slowing down each other. In this paper, we propose an efficient method to co-schedule simulations and in situ analyses such that the makespan of the workflow ensemble is minimized. We present a novel approach to allocate resources for a workflow ensemble under resource constraints by using a theoretical framework modeling the workflow ensemble’s execution. We evaluate the proposed approach using an accurate simulator based on the WRENCH simulation framework on various workflow ensemble configurations. Results demonstrate the significance of co-scheduling simulations and in situ analyses that couple data together to benefit from data locality, in which inefficient scheduling decisions can lead to slowdown in makespan up to a factor of 30.

Do, Tu Mai Anh↗

DOE OSTI2020

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. Finally, the relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Microbiome assembly in thawing permafrost and its feedbacks to climate

Abstract The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost–climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post‐thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw‐mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well‐suited to thrive in changing environmental conditions. We predict that on a short timescale and following high‐disturbance thaw (e.g., thermokarst), stochasticity dominates post‐thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower‐intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post‐thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Nitrogen availability and summer drought, but not N:P imbalance, drive carbon use efficiency of a Mediterranean tree-grass ecosystem

All ecosystems contain both sources and sinks for atmospheric carbon (C). A change in their balance of net and gross ecosystem carbon uptake, ecosystem-scale carbon use efficiency (CUE ECO ), is a change in their ability to buffer climate change. However, anthropogenic nitrogen (N) deposition is increasing N availability, potentially shifting terrestrial ecosystem stoichiometry towards phosphorus (P) limitation. Depending on how gross primary production (GPP, plants alone) and ecosystem respiration (R ECO , plants and heterotrophs) are limited by N, P or associated changes in other biogeochemical cycles, CUE ECO may change. Seasonally, CUE ECO also varies as the multiple processes that control GPP and respiration and their limitations shift in time. We worked in a Mediterranean tree-grass ecosystem (locally called ‘dehesa’) characterized by mild, wet winters and summer droughts. We examined CUE ECO from eddy covariance fluxes over 6 years under control, +N and + NP fertilized treatments on three timescales: annual, seasonal (determined by vegetation phenological phases) and 14-day aggregations. Finer aggregation allowed consideration of responses to specific patterns in vegetation activity and meteorological conditions. We predicted that CUE ECO should be increased by wetter conditions, and successively by N and NP fertilization. Milder and wetter years with proportionally longer growing seasons increased CUE ECO , as did N fertilization, regardless of whether P was added. Using a generalized additive model, whole ecosystem phenological status and water deficit indicators, which both varied with treatment, were the main determinants of 14-day differences in CUE ECO . The direction of water effects depended on the timescale considered and occurred alongside treatment-dependent water depletion. Overall, future regional trends of longer dry summers may push these systems towards lower CUE ECO .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

New insights on carbon black suspension rheology—Anisotropic thixotropy and antithixotropy

We report a detailed experimental study of peculiar thixotropic dynamics of carbon black (CB, Vulcan XC-72) suspensions in mineral oil, specifically the observation of sequential stress increase then decrease at a fixed shear rate in a step-down test. We verify that such dynamics, though peculiar, come from a true material response rather than experimental artifacts. We also reveal how this long-time stress decay is associated with antithixotropic structural change rather than viscoelastic stress relaxation by using orthogonal superposition (OSP) rheometry to probe viscoelastic moduli during the step-down tests. The orthogonal storage and loss moduli are present, showing this two-timescale recovery then decay response, which demonstrates that this response is antithixotropic, and it involves shear-induced structuring. We further show a mechanical anisotropy in the CB suspension under shear using OSP. Based on the rheological results, a microstructural schematic is proposed, considering qualitatively thixotropic structure build-up, antithixotropic densification, and anisotropic structure evolution. Our observation for these CB suspensions is outside the standard paradigm of thixotropic structure-parameter models, and the elastic response provides us with new insight into the transient dynamics of CB suspensions.

Mechanics↗

DOE OSTI2024

Microsecond dynamics control the HIV-1 Envelope conformation

The HIV-1 Envelope (Env) glycoprotein facilitates host cell fusion through a complex series of receptor-induced structural changes. Although remarkable progress has been made in understanding the structures of various Env conformations, microsecond timescale dynamics have not been studied experimentally. Here, we used time-resolved, temperature-jump small-angle x-ray scattering to monitor structural rearrangements in an HIV-1 Env SOSIP ectodomain construct with microsecond precision. In two distinct Env variants, we detected a transition that correlated with known Env structure rearrangements with a time constant in the hundreds of microseconds range. A previously unknown structural transition was also observed, which occurred with a time constant below 10 μs, and involved an order-to-disorder transition in the trimer apex. Using this information, we engineered an Env SOSIP construct that locks the trimer in the prefusion closed state by connecting adjacent protomers via disulfides. Our findings show that the microsecond timescale structural dynamics play an essential role in controlling the Env conformation with impacts on vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Direct observation of strong momentum-dependent electron-phonon coupling in a metal

Phonon scattering in metals is one of the most fundamental processes in materials science. However, understanding such processes has remained challenging and requires detailed information on interactions between phonons and electrons. We use an ultrafast electron diffuse scattering technique to resolve the nonequilibrium phonon dynamics in femtosecond–laser-excited tungsten in both time and momentum. We determine transient populations of phonon modes which show strong momentum dependence initiated by electron-phonon coupling. For phonons near Brillouin zone border, we observe a transient rise in their population on a timescale of approximately 1 picosecond driven by the strong electron-phonon coupling, followed by a slow decay on a timescale of approximately 8 picosecond governed by the weaker phonon-phonon relaxation process. We find that the exceptional harmonicity of tungsten is needed for isolating the two processes, resulting in long-lived nonequilibrium phonons in a pure metal. Our finding highlights that electron-phonon scattering can be the determinant factor in the phonon thermal transport of metals.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Thermal acclimation of stem respiration implies a weaker carbon-climate feedback

The efflux of carbon dioxide (CO2) from woody stems, a proxy for stem respiration, is a critical carbon flux from ecosystems to the atmosphere, which increases with temperature on short timescales. However, plants acclimate their respiratory response to temperature on longer timescales, potentially weakening the carbon-climate feedback. The magnitude of this acclimation is uncertain despite its importance for predicting future climate change. We develop an optimality-based theory dynamically linking stem respiration with leaf water supply to predict its thermal acclimation. We show that the theory accurately reproduces observations of spatial and seasonal change. We estimate the global value for current annual stem CO2 efflux as 27.4 ± 5.9 PgC. By 2100, incorporating thermal acclimation reduces projected stem respiration without considering acclimation by 24 to 46%, thus reducing land ecosystem carbon emissions.

Zhang, Han↗

DOE OSTI2020

Alignment of the ATLAS Inner Detector in Run 2

The performance of the ATLAS Inner Detector alignment has been studied using pp collision data at s√=13TeV collected by the ATLAS experiment during Run 2 (2015–2018) of the Large Hadron Collider (LHC). The goal of the detector alignment is to determine the detector geometry as accurately as possible and correct for time-dependent movements. The Inner Detector alignment is based on the minimization of track-hit residuals in a sequence of hierarchical levels, from global mechanical assembly structures to local sensors. Subsequent levels have increasing numbers of degrees of freedom; in total there are almost 750,000. The alignment determines detector geometry on both short and long timescales, where short timescales describe movements within an LHC fill. The performance and possible track parameter biases originating from systematic detector deformations are evaluated. Momentum biases are studied using resonances decaying to muons or to electrons. The residual sagitta bias and momentum scale bias after alignment are reduced to less than ~0.1 TeV -1 and 0.9×10 -3 , respectively. Impact parameter biases are also evaluated using tracks within jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Modes and Mechanisms of Pacific Decadal-Scale Variability

The modes of Pacific decadal-scale variability (PDV), traditionally defined as statistical patterns of variance, reflect to first order the ocean's integration (i.e., reddening) of atmospheric forcing that arises from both a shift and a change in strength of the climatological (time-mean) atmospheric circulation. While these patterns concisely describe PDV, they do not distinguish among the key dynamical processes driving the evolution of PDV anomalies, including atmospheric and ocean teleconnections and coupled feedbacks with similar spatial structures that operate on different timescales. In this review, we synthesize past analysis using an empirical dynamical model constructed from monthly ocean surface anomalies drawn from several reanalysis products, showing that the PDV modes of variance result from two fundamental low-frequency dynamical eigenmodes: the North Pacific–central Pacific (NP-CP) and Kuroshio–Oyashio Extension (KOE) modes. Both eigenmodes highlight how two-way tropical–extratropical teleconnection dynamics are the primary mechanisms energizing and synchronizing the basin-scale footprint of PDV. While the NP-CP mode captures interannual- to decadal-scale variability, the KOE mode is linked to the basin-scale expression of PDV on decadal to multidecadal timescales, including contributions from the South Pacific.

54 ENVIRONMENTAL SCIENCES↗