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At least 271 records · Page 15

Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System

Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuations in a power distribution system. The impact of different level of DER/EV penetration on the voltages across the network is typically quantified through voltage sensitivity analyses. Existing methods of voltage sensitivity analysis are computationally expensive and prior efforts to develop analytical approximation lacks generality and have not been effectively validated. The objective of this work is to provide a new analytical method of voltage sensitivity analysis that has low computational cost and also allows for stochastic analysis of voltage change. This paper first derives an analytical approximation of change in voltage at a particular bus due to change in power consumption at other bus in a radial three phase unbalanced power distribution system. Then, the proposed method is shown to be valid for different load configurations, which demonstrates its generality. The results from our analytical approach is validated via classical load flow simulation of the test system based on IEEE 37 bus network. The proposed method is shown to have good accuracy, and computation complexity is of order O(1), compared to O(n3) in classical sensitivity analysis approaches.

Munikoti, Sai↗

Degradation Diagnostics from the Subsurface of Lithium-Ion Battery Electrodes

Despite the long-established rocking-chair theory of lithium-ion batteries (LIBs), developing novel characterization methodology with higher spatiotemporal resolution facilitates a better understanding of the solid electrolyte interphase studies to shape the reaction mechanisms. In this work, we develop a Xenon ion plasma focused ion beam (Xe + PFIB)-based characterization technique to probe the cross-sectional interface of both ternary cathode and graphite anode electrodes, with the focus on revealing the chemical composition and distribution underneath the electrode surface by in-depth analysis of secondary ions. Particularly, the lithium fluoride is detected in the pristine cathode prior to contact with the electrolyte, reflecting that the electrode degradation is in the form of the loss of lithium inventory during electrode preparation. This degradation is related to the hydrolysis of the cathode material and the decomposition of the PVDF binder. Here, through the quantitative analysis of the transition-metal degradation products, manganese is found to be the dominant element in the newly formed inactive fluoride deposition on the cathode, while no transition metal signal can be found inside the anode electrode. These insights at high resolution implemented via a PFIB-based characterization technique not only enrich the understanding of the degradation mechanism in the LIBs but also identify and enable a high-sensitivity methodology to obtain the chemical survey at the subsurface, which will help remove the capacity-fade observed in most LIBs.

25 ENERGY STORAGE↗

Control systems and data management for high-power laser facilities

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community

47 OTHER INSTRUMENTATION↗

High-dimensional maximum-entropy phase space tomography

Reconstructing 4D or 6D phase space distributions from 1D or 2D measurements is a challenging inverse problem encountered in particle accelerators. Entropy maximization is an established method to incorporate prior information in the reconstruction, but it is typically infeasible in high-dimensional spaces. In this paper, I review two recent approaches to high-dimensional entropy maximization. The first approach utilizes differentiable simulations and a class of generative models known as normalizing flows, whereas the second approach employs the method of Lagrange multipliers and Markov Chain Monte Carlo (MCMC) sampling. My aim is to provide a short explanation of each method using a common notation. I conclude by mentioning several unsolved problems in phase space tomography.

Hoover, Austin [ORNL] (ORCID:0000000153136962)↗

Light Relics of the Early Universe (Final Technical Report)

The research supported by this award invested two types of signals left over of the early universe that might be observed in maps of the universe: (i) particles produced (thermal relics) during the hot big bang and (ii) signals left in the seeds of structure left from from an inflationary epoch prior to the hot big bang (inflationary relics). The research into thermal relics exposed new signatures of the cosmic neutrino background in the distribution of galaxies, culminating in the first measurement of the neutrino induced phase shift of the baryon acoustic oscillations. Subsequent research explored implications of constraints on hot light particles from the cosmic microwave background and the large scale structure for the physics of dark matter. Green and collaborations also investigated cosmological signatures from the inflationary epoch, including the best constraint to date on oscillatory features in seeds of structure and the first viable proposal to test the quantum origin of structure in the universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

J-PLUS: Spectral evolution of white dwarfs by PDF analysis

We estimated the spectral evolution of white dwarfs with effective temperature using the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), which provides 12 photometric optical passbands over 2176 deg 2 . We analyzed 5926 white dwarfs with r ≤ 19.5 mag in common between a white dwarf catalog defined from Gaia EDR3 and J-PLUS DR2. We performed a Bayesian analysis by comparing the observed J-PLUS photometry with theoretical models of hydrogen- and helium-dominated atmospheres. We estimated the probability distribution functions for effective temperature (T eff ), surface gravity, parallax, and composition; and the probability of having a H-dominated atmosphere (p H ) for each source. We applied a prior in parallax, using Gaia EDR3 measurements as a reference, and derived a self-consistent prior for the atmospheric composition as a function of T eff . We described the fraction of white dwarfs with a He-dominated atmosphere (f He ) with a linear function of the effective temperature at 5000 < T eff < 30 000 K. We find f He = 0.24 ± 0.01 at T eff = 10 000 K, a change rate along the cooling sequence of 0.14 ± 0.02 per 10 kK, and a minimum He-dominated fraction of 0.08 ± 0.02 at the high-temperature end. We tested the obtained p H by comparison with spectroscopic classifications, finding that it is reliable. We estimated the mass distribution for the 351 sources with distance d < 100 pc, mass M > 0.45 M ⊙ , and T eff > 6000 K. The result for H-dominated white dwarfs agrees with previous studies, with a dominant M = 0.59 M ⊙ peak and the presence of an excess at M ~ 0.8 M ⊙ . This high-mass excess is absent in the He-dominated distribution, which presents a single peak. The J-PLUS optical data provide a reliable statistical classification of white dwarfs into H- and He-dominated atmospheres. We find a 21 ± 3% increase in the fraction of He-dominated white dwarfs from T eff = 20 000 K to T eff = 5000 K.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey

ABSTRACT The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$. For a $3{{\ \rm per\ cent}}$ prior on Alens we forecast precisions of $1.9{{\ \rm per\ cent}}$, $2.0{{\ \rm per\ cent}}$, and $1.9{{\ \rm per\ cent}}$ on Ωm, σ8, and $S_8 \equiv \sigma _8\Omega _m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $1{{\ \rm per\ cent}}$ further improves the S8 precision to $1.1{{\ \rm per\ cent}}$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.

79 ASTRONOMY AND ASTROPHYSICS↗

Potential Energy, Demand, Emissions, and Cost Savings Distributions for Buildings in a Utility’s Service Area

Several companies, universities, and national laboratories are developing urban-scale energy modeling that allows the creation of a digital twin of buildings for the simulation and optimization of real-world, city-sized areas. Prior to simulation-based assessment, a baseline of savings for a set of utility-defined use cases was established to clarify the initial business case for specific energy efficient building technologies. In partnership with a municipal utility, 178,337 OpenStudio and EnergyPlus models of buildings in the utility’s 1400 km 2 service area were created, simulated, and assessed with measures for quantifying energy, demand, cost, and emissions reductions of each building. The method of construction and assumptions behind these models is discussed, definitions of example measures are provided, and distribution of savings across the building stock is provided under a maximum technical adoption scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A parcel-level evaluation of distributed wind opportunity in the contiguous United States

This study examines the potential for distributed wind (DW) energy across the contiguous United States, leveraging advancements in the National Renewable Energy Laboratory's distributed wind model, dWind. The novel modeling approach described here utilizes a high-resolution dataset and analyzes over 150 million parcels, a significant improvement from prior methods that extrapolated results from a smaller random sample. This achievement is enabled through key model performance improvements, such as transitioning to multiprocessing, which reduces runtime by 97 %. This optimized, high-resolution approach allows the inspection of technology deployment potential and impact on a variety of scales tailored to individual properties and regions. The results here align with prior work showing substantial opportunity for energy generation using DW technologies. Key findings reveal a substantial increase from prior results in estimated technical and economic potential for DW. Metrics tuned to highlight economic potential also show increased incentives supporting rural adoption. Results are spatially aggregated for usability and published via the U.S. Department of Energy Wind Data Portal and a custom scenario visualization platform, aiding policymakers, industry, and property owners in assessing DW viability across various scenarios and spatial scales.

17 WIND ENERGY↗

Characterizing the pore-scale impacts of enhanced-solubilization solutions on organic-liquid morphology and fluid-fluid interfacial area with microtomography

Synchrotron X-ray microtomography was used to directly quantify the impact of enhanced-solubilization solutions on mobilization of a non-wetting fluid in a natural porous medium. Polyoxyethylene sorbitan monooleate (tween 80), hydroxypropyl-β-cyclodextrin (HPCD), sodium dodecyl sulfate (SDS), and ethanol were used as the solubilization reagents. Tetrachloroethene (PCE) was used as the entrapped organic immiscible liquid. Microtomography images were collected prior to and after successive floods with each reagent solution. The total trapping number was varied by more than three orders of magnitude by changing the velocity and viscosity of the aqueous phase as well as the interfacial tension between fluid phases. The results were compared to those obtained from equivalent experiments conducted with water flooding. Inspection of images indicated that mobilization caused a change in PCE morphology and distribution for all reagents with the exception of HPCD, for which a lower trapping number was determined compared to the other experiments. Mobilization of organic liquid was observed at total trapping numbers that were consistent with prior work. The enhanced-solubilization solutions had minimal impact on the configuration or magnitude of fluid-fluid interfacial area.

Interfacial area↗

Genetic underpinnings of arthropod community distributions in Populus trichocarpa

Community genetics seeks to understand the mechanisms by which natural genetic variation in heritable host phenotypes can encompass assemblages of organisms such as bacteria, fungi, and many animals including arthropods. Prior studies that focused on plant genotypes have been unable to identify genes controlling community composition, a necessary step to predict ecosystem structure and function as underlying genes shift within plant populations. Here, we surveyed arthropods within an association population of Populus trichocarpa in three common gardens to discover plant genes that contributed to arthropod community composition. We analyzed our surveys with traditional single-trait genome-wide association analysis (GWAS), multitrait GWAS, and functional networks built from a diverse set of plant phenotypes. Plant genotype was influential in structuring arthropod community composition among several garden sites. Candidate genes important for higher level organization of arthropod communities had broadly applicable functions, such as terpenoid biosynthesis and production of dsRNA binding proteins and protein kinases, which may be capable of targeting multiple arthropod species. We have demonstrated the ability to detect, in an uncontrolled environment, individual genes that are associated with the community assemblage of arthropods on a host plant, further enhancing our understanding of genetic mechanisms that impact ecosystem structure.

Community genetics↗

Scalable Synthesis of Pt/SrTiO 3 Hydrogenolysis Catalysts in Pursuit of Manufacturing-Relevant Waste Plastic Solutions

Here, an improved hydrothermal synthesis for shape-controlled, size-controlled 60 nm SrTiO 3 nanocuboid (STO NC) supports, which facilitates the scalable creation of platinum nanoparticles catalyst supported on STO (Pt/STO) for the chemical conversion of waste polyolefins, is reported herein. This synthetic method: 1) produces STO NC supports with average sizes ranging from 25 – 80 nm with narrow size distributions 2) demonstrates how SrCO 3 formation and variation in solution pH prevent the formation of STO NCs, and 3) establishes that STO nucleation prior to the hydrothermal treatment favors nanocuboid formation. The updated hydrothermal synthesis was scaled-up and conducted in a 4L batch reactor, resulting in STO NCs of comparable size and morphology (m = 22.5 g, d avg = 58.6 ± 16.2 nm) to those synthesized under standard hydrothermal conditions in a lab-scale 125 mL autoclave reactor. Size-controlled STO NCs, ranging in roughly 10 nm increments from the 25 nm to 80 nm, were used to support Pt deposited through strong electrostatic adsorption (SEA), a practical and scalable solution-based method. Using SEA techniques and a STO support with an average size of 39.3 ± 6.3 nm, a Pt/STO catalyst with 3.6 wt% Pt was produced and used for high-density polyethylene hydrogenolysis under previously-reported conditions (170 psi H 2 , 300°C, 96h; final product: M w = 2400, Ð = 1.03). As a well-established model system for studying the behavior of heterogeneous catalysts and their supports in reactions, the Pt/STO system detailed in this work presents a unique opportunity to simultaneously convert waste plastic into commercially-viable products while gaining fundamental insight into the mechanism of polyethylene hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping domain structures near a grain boundary in a lead zirconate titanate ferroelectric film using X-ray nanodiffraction

The effect of an electric field on local domain structure near a 24° tilt grain boundary in a 200 nm-thick Pb(Zr 0.2 Ti 0.8 )O 3 bi-crystal ferroelectric film was probed using synchrotron nanodiffraction. The bi-crystal film was grown epitaxially on SrRuO 3 -coated (001) SrTiO 3 24° tilt bi-crystal substrates. From the nanodiffraction data, real-space maps of the ferroelectric domain structure around the grain boundary prior to and during application of a 200 kV cm −1 electric field were reconstructed. In the vicinity of the tilt grain boundary, the distributions of densities of c -type tetragonal domains with the c axis aligned with the film normal were calculated on the basis of diffracted intensity ratios of c - and a -type domains and reference powder diffraction data. Diffracted intensity was averaged along the grain boundary, and it was shown that the density of c -type tetragonal domains dropped to ∼50% of that of the bulk of the film over a range ±150 nm from the grain boundary. This work complements previous results acquired by band excitation piezoresponse force microscopy, suggesting that reduced nonlinear piezoelectric response around grain boundaries may be related to the change in domain structure, as well as to the possibility of increased pinning of domain wall motion. The implications of the results and analysis in terms of understanding the role of grain boundaries in affecting the nonlinear piezoelectric and dielectric responses of ferroelectric materials are discussed.

36 MATERIALS SCIENCE↗

Probing Non-Standard Interactions in NOvA with Bayesian MCMC Methods

We present a search for non-standard neutrino interactions (NSI) using NOvA's joint $\nu_e$ appearance and $\nu_\mu$ disappearance samples in both neutrino and antineutrino beam modes. A Bayesian Markov Chain Monte Carlo approach is used to map the posterior distribution over NSI parameters $\varepsilon_{e\mu}$, $\varepsilon_{e\tau}$, and $\varepsilon_{\mu\tau}$, simultaneously with standard oscillation parameters. We investigate the effect of prior choice for the complex NSI parameters and present projected sensitivity to off-diagonal NSI.

Huang, Xiaoyan [Mississippi U.]↗

BEYONDPLANCK XIII. Intensity foreground sampling, degeneracies, and priors

We present the intensity foreground algorithms and model employed within the BEYONDPLANCK analysis framework. The BEYONDPLANCK analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the Planck Low Frequency Instrument (LFI) data analysis. Given the scope of the BEYONDPLANCK analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous Commander component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: (1) joint foreground spectral parameter and amplitude sampling, building on ideas from MIRAMARE; (2) component-based monopole determination; (3) joint spectral parameter and monopole sampling; and (4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BEYONDPLANCK data set is the peak frequency of the anomalous microwave emission component, for which we find $ν$ p = 25.3 ± 0.5 GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects. This work will be organized within the Open Science-based COSMOGLOBE community effort.

79 ASTRONOMY AND ASTROPHYSICS↗

Enhancing approximate modular Bayesian inference by emulating the conditional posterior

In modular Bayesian analyses, complex models are composed of distinct modules, each representing different aspects of the data or prior information. In this context, fully Bayesian approaches can sometimes lead to undesirable feedback between modules, compromising the integrity of the inference. The “cut-distribution” prevents unwanted influence between modules by “cutting” feedback. The direct sampling (DS) algorithm is standard practice for approximating the cut-distribution, but it can be computationally intensive, especially when the number of imputations required is large. An enhanced method is proposed, the Emulating the Conditional Posterior (ECP) algorithm, which leverages emulation to increase the number of imputations. Through numerical experiment it is demonstrated that the ECP algorithm outperforms the traditional DS approach in terms of accuracy and computational efficiency, particularly when resources are constrained. Here, it is also shown how the DS algorithm can be improved using ideas from design of experiments. Some practical recommendations are given for algorithm choice in modular Bayesian analyses.

97 MATHEMATICS AND COMPUTING↗

Particulate plutonium released from the Fukushima Daiichi meltdowns

Traces of Pu have been detected in material released from the Fukushima Daiichi Nuclear Power Plant (FDNPP) in March of 2011; however, to date the physical and chemical form of the Pu have remained unknown. Here we report the discovery of particulate Pu associated with cesium-rich microparticles (CsMPs) that formed in and were released from the reactors during the FDNPP meltdowns. The Cs-pollucite-based CsMP contained discrete U(IV)O 2 nanoparticles, <~10 nm, one of which is enriched in Pu adjacent to fragments of Zr-cladding. The isotope ratios, 235 U/ 238 U, 240 Pu/ 239 Pu, and 242 Pu/ 239 Pu, of the CsMPs were determined to be ~0.0193, ~0.347, and ~0.065, respectively, which are consistent with the calculated isotopic ratios of irradiated-fuel fragments. Thus, considering the regional distribution of CsMPs, the long-distance dispersion of Pu from FNDPP is attributed to the transport by CsMPs that have incorporated nanoscale fuel fragments prior to their dispersion up to 230 km away from the Fukushima Daiichi reactor site.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stratigraphy‐Induced Localization of Microseismicity During CO 2 Injection in Illinois Basin

Abstract Subsurface fluid injection stimulates complex hydromechanical interaction, necessitating the integration of geomechanical data across spatial and temporal scales to consider the sophisticated behavior. Induced seismic response is usually associated with the complex reservoir architecture and pre‐existing features that are three‐dimensional, such as local stratigraphy, fractures, faults, and other discontinuities. This study encompasses laboratory characterization of the coupled hydromechanical response of cores extracted from rock formations in Illinois Basin: reservoir ‐ Mt. Simon sandstone, basal seal ‐ Argenta sandstone, and crystalline basement ‐ Precambrian rhyolite. High‐resolution numerical modeling allows considering the three‐dimensional complexity of the Illinois Basin Decatur Project with spatial resolution comparable to one of the active seismic surveys. A detailed reconstruction of the evolving state of stress in formations lacking direct stress measurements is achieved by numerical modeling that integrated laboratory‐derived hydromechanical properties, a porosity‐permeability relationship, active seismic data, and an inverted three‐dimensional porosity distribution. It appears that the microseismic clusters, mainly observed in the crystalline basement during the injection, are linked to zones experiencing more critically stressed conditions prior to injection. These zones have a potential for reactivation during the injection and are attributed to the specific local stratigraphy of the injection site, as well as transfer of triggering perturbations during the injection.

Bondarenko, N. [University of Illinois Urbana‐Cham↗