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DOE OSTI2020

Dynamic Power Network State Estimation with Asynchronous Measurements

The operation of distribution networks is becoming increasingly volatile, due to fast variations of renewables and, hence, net-loading conditions. To perform a reliable state estimation under these conditions, this paper considers the case where measurements from meters, phasor measurement units, and distributed energy resources are collected and processed in real time to produce estimates of the state at a fast time scale. Streams of measurements collected in real time and at heterogenous rates render the underlying processing asynchronous, and poses severe strains on workhorse state estimation algorithms. In this work, a real-time state estimation algorithm is proposed, where data are processed on the fly. Starting from a regularized least-squares model, and leveraging appropriate linear models, the proposed scheme boils down to a linear dynamical system where the state is updated based on the previous estimate and on the measurement gathered from a few available sensors. The estimation error is shown to be always bounded under mild condition. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol

Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (SOM-TOMAS), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from ??- pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained (1-7 ×10-15 cm2 s-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass transition temperature, viscosity, and, ultimately, Db (~10-15 cm2 s-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size resolved SOA model to constrain the particle phase state of SOA by utilizing historical measurements of the evolution of the particle size distribution.

He, Yicong↗

DOE OSTI2025

CO 2 in Ionene–Ionic Liquid Composite Membranes

Abstract Ionene – ionic liquid (IL) composites are promising materials for CO 2 separation, yet a molecular‐level understanding of their structure and its impact on CO 2 speciation, solubility, rotation, and diffusivity remains unclear. Herein, using multimodal nuclear magnetic resonance (NMR), time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), atomic force microscopy (AFM), and molecular dynamics (MD) simulations, we reveal that the composites contain IL‐rich domains extending across hundreds of nanometres within the ionene matrix, and these bicontinuous domains span the entire membrane depth. CO 2 also absorbs into the ionene matrix, with the distribution between two CO 2 species varying with temperature and time. The rotational correlation times of these two species are on the timescale of 0.1 and 1 ns, respectively. As IL content increases, the ionic domains expand, resulting in higher CO 2 solubility due to enhanced molecular dynamics and increased free volume in both ionene backbones and IL‐rich regions. Although CO 2 diffusion in the membranes is an order of magnitude slower than in bulk IL, the activation energy for CO 2 diffusion remains comparable. Ionene‐IL composites represent a promising platform for designing CO 2 separation membranes, offering enhanced CO 2 diffusion and selectivity through IL‐rich domains, and increased CO 2 solubility and mechanical integrity from the ionene matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Driven electrostatic phase space vortices in a 1D weakly dissipative Vlasov–Poisson system

In this paper, the effect of collisions on driven electrostatic phase space vortices is analyzed by means of Eulerian simulation for two different collision models. It was demonstrated recently that in the absence of collisions, at late times, steady state phase space vortices manifest to form a plateau in the resonant region of the particle velocity distribution function, due to trapping of particles supporting multiextrema giant phase space vortices (PSVs). In the presence of collisions, over long time, this multiextrema plateau are found to smooth out, since collisions drive the velocity distribution toward Maxwellian, irrespective of how weak the collisions are as long as they are non-zero. In these conditions, kinetic processes and collisionality are found to be in competition, and the evolution of the plasma is found, therefore, to be a result of nontrivial combination of these two effects. An attempt has been made by means of numerical simulations to study the effect of weak collisionality on the electrostatic driven phase space vortices with two types of collision operators: (1) Bhatnagar–Gross–Krook (Krook) collision operator, where the colliding particles can be treated as isolated pairs and, (2) Fokker–Planck (FP) type collision operator (Zakharov–Karpman) in one dimension, where many weak collisions lead to particle diffusion in velocity space. It is shown that depending on the collision model used, the nature of smoothing in velocity space of giant PSVs results in qualitatively very different phase space structures. However, irrespective of the collision model used, excess density fractions over 10% are retained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Comparison of excitation temperature of a laser-produced plasma by combining emission and absorption spectroscopy

Measurement of the temporal evolution of laser-produced plasma temperature is very important for many of its applications, and several plasma diagnostic tools are routinely used by researchers. However, it is very challenging to measure the properties of the plasma at the early and late times of its evolution using a single diagnostic tool. In this study, we combined emission and laser absorption spectroscopy to compare the excitation temperatures of a laser-produced uranium plasma system. Several U I transitions in the near-infrared spectral range (775–800 nm) were considered, and the Boltzmann plot method was used to measure the excitation temperatures using both emission and absorption spectroscopy. Emission spectroscopy provided early-time temperature measurements of the plasma up to times 2–20 µs, while absorption spectroscopy provided temperature measurements at late times of plasma evolution (for times 5–80 µs). The emission and absorbance of U I transitions were found to follow the Boltzmann distribution, indicating the plasma is likely in the state of local thermodynamic equilibrium even at late times of its lifetime. The emission and absorption-based time-resolved excitation temperatures demonstrated good agreement at earlier times (≤15 µs) in the overlapped temporal region, while a deviation in the measured values was seen at times (≥15 µs), and potential reasons for such a disagreement are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Towards the design of a wideband reflective long period grating distributed sensor

Abstract In this paper, we computationally investigate the effects of metal coating length and coating coverage on the reflected spectrum of a long period grating (LPG) over a broad bandwidth. Simulation results indicate that coating the tail end of the fiber between the LPG and the end facet of the fiber provides a reflected spectrum that mimics the LPG transmission spectrum shape over a 400 nm bandwidth. Based on single LPG simulation results, we present the design of a distributed LPG structure containing a multiple number ( n ) of LPGs in reflection mode for the first time. Simulation results for n = 1, 2, and 3 are presented here to demonstrate the concept of a distributed reflective LPG design. It is expected that such a sensor will open a new window for distributed sensing using reflective LPGs.

Rana, Sohel (ORCID:0000000262813555)↗

DOE OSTI2021

Distribution function of nuclei from $\mathcal{e}^±$ scattering in the presence of a strong primordial magnetic field

The amplitude of the primordial magnetic field (PMF) is constrained from observational limits on primordial nuclear abundances. Within this constraint, it is possible that nuclear motion is regulated by Coulomb scattering with electrons and positrons (e ± s), while e ± s are affected by a PMF rather than collisions. For example, at a temperature of 10 9 K, thermal nuclei typically experience ~ 10 21 scatterings per second that are dominated by very small angle scattering leading to minuscule changes in the nuclear kinetic energy of order $\mathcal{O}$(1) eV. In this paper the upper limit on the effects of a possible discretization of the e ± momenta by the PMF on the nuclear momentum distribution is estimated under the extreme assumptions that the momentum of the e ± is relaxed before and after Coulomb scattering to Landau levels, and that during Coulomb scattering the PMF is neglected. This assumption explicitly breaks the time reversal invariance of Coulomb scattering, and the Maxwell-Boltzmann distribution is not a trivial steady state solution of the Boltzmann equation under these assumptions. Here we numerically evaluate the collision terms in the Boltzmann equation, and show that the introduction of a special direction in the e ± distribution by the PMF generates no directional dependence of the collisional destruction term of nuclei. Large anisotropies in the nuclear distribution function are then constrained from big bang nucleosynthesis. Ultimately, we conclude that a PMF does not significantly affect the isotropy or big bang nucleosynthesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗

DOE OSTI2021

Quantifying the time‐specific kinetic energy of simulated rainfall using a dynamic rain gauge system

Abstract Raindrop impact derives from the kinetic energy of falling raindrops. Determining the kinetic energy of rainfall requires the size distribution and terminal velocity of raindrops, which necessitates complex instrumentation. To avoid this, empirical relations have been developed that relate rainfall intensity and the rate of kinetic energy, i.e., time‐specific kinetic energy (KE time ). In this study, a dynamic rain gauge system (DRGS) was used to quantify the KE time generated by a rainfall simulator without need of measuring raindrop size distributions or impact velocities. In a series of 10 rainfall tests, the KE time and rainfall intensity were 860.9 (±88.6) J m 2 h −1 and 72.1 (±1.9) mm h −1 , respectively. Estimated KE time was found to agree well with the power‐law relation presented by Petrů and Kalibová for high‐intensity simulated rainfall, which are the conditions when higher deviations occur. The DRGS may be a useful tool in quantifying the KE time of rainfall simulators in hopes to better understand raindrop impact mechanisms.

Wacha, Kenneth M.↗

DOE OSTI2023

Energy-Resolved Femtosecond Hot Electron Dynamics in Single Plasmonic Nanoparticles

Efficient excitation and harvesting of hot carriers from nanoscale metals is central to many emerging photochemical, photovoltaic, and ultrafast optoelectronic applications. Nevertheless, direct experimental evidence of the energy-dependent femtosecond dynamics in ubiquitous tens-of-nanometer gold structures remains elusive, despite the potentially rich interplay between interfacial and internal plasmonic fields, excitation distributions, and scattering processes. To explore the effects of nanoscale structure on these dynamics, we employ simultaneous time-, angle-, and energy-resolved photoemission spectroscopy of single plasmonic nanoparticles. Photoelectron velocity and electric field distributions reveal bulk-like ballistic hot electron transport in different geometries, lacking any signatures of surface effects. Energy-resolved dynamics are measured in the 1–2 eV range and extrapolated to lower energies via Boltzmann theory, providing a detailed view of hot electron lifetimes within nanoscale gold. Here, we find that particles with relevant dimensions as small as 10 nm serve as exemplary platforms for studying intrinsic metal dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Power Distribution Designing For Resilience Application

The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.

Phillips, TylerB↗

DOE OSTI2020

A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet

We consider the scientifically challenging and policy-relevant task of understanding the past and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has shown a highly nonlinear threshold response to past climate forcings. Triggering such a threshold response through anthropogenic greenhouse gas emissions would drive drastic and potentially fast sea level rise with important implications for coastal flood risks. Previous studies have combined information from ice sheet models and observations to calibrate model parameters. These studies have broken important new ground but have either adopted simple ice sheet models or have limited the number of parameters to allow for the use of more complex models. These limitations are largely due to the computational challenges posed by calibration as models become more computationally intensive or when the number of parameters increases. Here, we propose a method to alleviate this problem: a fast sequential Monte Carlo method that takes advantage of the massive parallelization afforded by modern high-performance computing systems. We use simulated examples to demonstrate how our sample-based approach provides accurate approximations to the posterior distributions of the calibrated parameters. The drastic reduction in computational times enables us to provide new insights into important scientific questions, for example, the impact of Pliocene era data and prior parameter information on sea level projections. These studies would be computationally prohibitive with other computational approaches for calibration such as Markov chain Monte Carlo or emulation-based methods. We also find considerable differences in the distributions of sea level projections when we account for a larger number of uncertain parameters. For example, based on the same ice sheet model and data set, the 99th percentile of the Antarctic ice sheet contribution to sea level rise in 2300 increases from 6.5 m to 13.1 m when we increase the number of calibrated parameters from three to 11. With previous calibration methods, it would be challenging to go beyond five parameters. Here, this work provides an important next step toward improving the uncertainty quantification of complex, computationally intensive and decision-relevant models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Combined, time-resolved, in situ neutron reflectometry and X-ray diffraction analysis of dynamic SEI formation during electrochemical N 2 reduction

One means of improving performance for electrochemical ammonia production through the Li-mediated N 2 reduction reaction (Li-NRR) is by cycling the current driving the reaction between open-circuit conditions and periods of applied current density. Herein, we have investigated the dynamics of the electrode–electrolyte interface under Li-NRR conditions during current cycling using in situ time-resolved neutron reflectometry and grazing-incidence synchrotron X-ray diffraction. During cycling, measured neutron reflectivity curves indicated bilayer formation in which Li-containing species such as LiOH, Li 2 O, and small quantities of Li 3 N and metallic Li primarily appeared in a thin layer at the cathode surface, above which formed a much larger, porous, ‘solid–electrolyte interface’ (SEI) layer. Upon return to open-circuit conditions, Li-containing species quickly moved out of the thin layer, leaving a compact, stable layer of decomposition products underneath the SEI layer. This SEI layer concomitantly filled with electrolyte or dissolved, becoming indistinguishable from the electrolyte via contrast in scattering-length density (SLD). During the second current cycle, Li-containing species again preferentially deposited directly atop the cathode, with the thick SEI-like layer again appearing within a minute. This SEI layer exhibited a lower SLD more quickly than in the first cycle, which might suggest that Li-containing species become distributed within the porous SEI layer. Furthermore, these time-resolved observations of SEI and plated layers during current cycling suggest that benefits associated with return to open-circuit conditions between periods of applied current density may be related to the concomitant loss of Li-containing species from a thin layer at the cathode surface into a porous SEI layer that becomes filled with electrolyte or dissolves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX

Energetic neutral atom (ENA) measurements by IBEX reveal that the heliotail comprises an energy-dependent multilobe structure. We examine the heliotail evolution over 11 yr of IBEX observations covering a full solar cycle (SC). We find the following: (1) The heliotail structure persists over the entire SC, comprising three ENA-enhanced and two ENA-suppressed lobes. (2) Lobe sizes and locations are generally stable but exhibit variations in ENA fluxes driven by the SC. (3) Lobe centers follow a cyclic behavior over multiple SC phases, indicating direct signatures of slow and fast solar wind (SW) interactions in the inner heliosheath (IHS). (4) The tilted plane passing through the port–starboard lobes' centers oscillates in latitude but maintains its tilt from the ecliptic plane, likely a consequence of the interstellar magnetic field draping around the heliosphere. (5) The transition of the central heliotail from a single lobe at ~1.1 keV to two lobes above ~2 keV is SC-dependent and directly reflects the IHS plasma properties, i.e., when ENA fluxes from fast SW from the polar coronal holes change over time. (6) The central lobe exhibits a substructure that is enhanced and offset from the downwind direction, possibly indicating an asymmetric ENA emission or an asymmetry in the parent plasma distribution. These results reveal the general stability of the heliotail structure over time and distinct variations in individual lobes' properties in relation to the SC phases. Furthermore, results show the effects of multiple SC phases in the tail, reflecting different ENA travel times and source histories.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Experimental 3-dimensional tracking of the dynamics of a single electron in the Fermilab Integrable Optics Test Accelerator (IOTA)

We present the results of experimental studies on the transverse and longitudinal dynamics of a single electron in the IOTA storage ring. IOTA is a flexible machine dedicated to beam physics experiments with electrons and protons. A method was developed to reliably inject and circulate a controlled number of electrons in the ring. A key beam diagnostic system is the set of sensitive high-resolution digital cameras for the detection of synchrotron light emitted by the electrons. With 60–130 electrons in the machine, we measured beam lifetime and derived an absolute calibration of the optical system. At exposure times of 0.5 s, the cameras were sensitive to individual electrons. Camera images were used to reconstruct the time evolution of oscillation amplitudes of a single electron in all 3 degrees of freedom. The evolution of amplitudes directly showed the interplay between synchrotron-radiation damping, quantum excitations, and scattering with the residual gas. From the distribution of measured single-electron oscillation amplitudes, we deduced transverse emittances, momentum spread, damping times, and beam energy. Estimates of residual-gas density and composition were calculated from the measured distributions of vertical scattering angles. Combining scattering and lifetime data, we also provide an estimate of the aperture of the ring. To our knowledge, this is the first time that the dynamics of a single electron are tracked in all three dimensions with digital cameras in a storage ring.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil

Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.

58 GEOSCIENCES↗

DOE OSTI2024

Distributed optimization for multi-commodity urban traffic control

A distributed method for concurrent traffic signal and routing control of traffic networks is proposed. The method is based on the multi-commodity store-and-forward model, in which the destinations are the commodities. The system benefits from the communication between vehicles and infrastructure, providing optimal signal timings to intersections and routes to vehicles on a link-by-link basis. Using the augmented Lagrangian to model the constraints into the objective, the baseline centralized problem is decomposed into a set of objective-coupled subproblems, one for each intersection, enabling the solution to be computed by a distributed- gradient projection algorithm. Further, the intersection agents only need to communicate and coordinate with neighboring intersections to ensure convergence to the optimal solution while tolerating suboptimal iterations that offer more flexibility, unlike other distributed approaches. Through microsimulation, we demonstrate the effectiveness of the proposed algorithm in traffic networks with time-varying demand. Computational analysis shows that the distributed problem is suitable for real-time applications. A robustness analysis show that the distributed formulation enables a graceful degradation of the system in case of failure.

Augmented Lagrangian↗