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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42

Search for Higgs Boson and Observation of $Z$ Boson through Their Decay into a Charm Quark-Antiquark Pair in Boosted Topologies in Proton-Proton Collisions at $\sqrt{s}$ = 13 TeV

A search for the standard model (SM) Higgs boson ($H$) produced with transverse momentum ($p_T$) greater than 450 GeV and decaying to a charm quark-antiquark ($c\bar{c}$) pair is presented. The search is performed using proton-proton collision data collected at $\sqrt{s} = 13$ TeV by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. Boosted $H \to c\overline{c}$ decay products are reconstructed as a single large-radius jet and identified using a deep neural network charm tagging technique. The method is validated by measuring the $Z \to c\bar{c}$ decay process, which is observed in association with jets at high $p_T$ for the first time with a signal strength of $1.00^{+0.17}_{-0.14}$ (syst)$\pm 0.08$ (theo) $\pm 0.06$ (stat), defined as the ratio of the observed process rate to the SM expectation. The observed (expected) upper limit on $\sigma (H){\cal B}(H \to c\overline{c})$ is set at 47 (39) times the SM prediction at 95\%confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Seeded Stage III glass dissolution behavior of a statistically designed glass matrix

The glass dissolution rate of some glasses accelerates after prolonged time spent at a slow, residual glass dissolution rate. This phenomenon is referred to as Stage III behavior. Here, the acceleration in glass dissolution rate linked to Stage III behavior is significant and may be the most impactful to long-term performance of glass in a repository. This work is aimed at understanding the effect of glass composition on Stage III behavior to add a level of technical defensibility to glass disposal. To this end, a set of twenty-four glass compositions were statistically designed, where eight glass components (SiO 2 , B 2 O 3 , Al 2 O 3 , CaO, Na 2 O, SnO 2 , ZrO 2 , and Others) have been independently varied in order to study the individual effects of each. These glasses have been subjected to static dissolution tests at 90 °C in deionized water and then seeded with zeolite Na-P2 28 days into the testing to induce Stage III behavior. The response of the glasses to the zeolite seeds fell into four primary types: 1) no response to seeds; 2) an immediate linear sustained acceleration in the rate; 3) an immediate linear acceleration in the rate followed by a decrease; and, 4) a progressive acceleration in the rate that is concurrent with the addition of the seeds. The main glass components observed to influence these behaviors were CaO, Al 2 O 3 , B 2 O 3 , and ZrO 2 , where: 1) CaO influenced which glasses showed a Stage III response to seeds (high CaO: Types 2, 3, and 4) or did not respond to seeds (low CaO: Type 1), 2) Al 2 O 3 and B 2 O 3 influenced which glasses showed a sustainable Stage III response (high Al 2 O 3 : Types 2 and 4) versus transitory response (low Al 2 O 3 and high B 2 O 3 : Type 3), and 3) ZrO 2 concentration influenced whether glasses showed a linear (high ZrO 2 : Type 2) versus progressive (low ZrO 2 : Type 4) response to seeds.

36 MATERIALS SCIENCE↗

To Fail or not to Fail: An Exploration of Machine Learning Techniques for Predictive Maintenance

Predictive maintenance refers to the ability to predict when machinery or systems need to be maintained. Making an accurate prediction is quite challenging given the costs for both over-estimating (unnecessary maintenance and reduction in availability of assets) and under-estimating (untimely breakdowns and possible loss of equipment or lives). To address these challenges researchers were able to develop new approaches for analyzing oil samples taken extracting samples from oil-wetted machinery that may provide information critical to developing predictive capabilities. We consider the problem from both supervised (though data limited) and unsupervised approaches and provide a first look into a data driven approach for identification of condition indicators. Through this work we identify a collection of candidate features that can form the basis of condition indicators for both a high level discrimination of failure vs. normal operation as well as a set for potential failure mode identification. Finally, we present an anomaly detection framework for detecting failures which can be a viable solution for an onboard analysis tool in deployed systems.

predictive maintenance, anomaly detection, Laserne↗

Search for flavour-changing neutral-current couplings between the top quark and the Higgs boson in multi-lepton final states in 13 TeV pp collisions with the ATLAS detector

A search is presented for flavour-changing neutral-current interactions involving the top quark, the Higgs boson and an up-type quark (q = u, c ) with the ATLAS detector at the Large Hadron Collider. The analysis considers leptonic decays of the top quark along with Higgs boson decays into two W bosons, two Z bosons or a τ + τ - pair. It focuses on final states containing either two leptons (electrons or muons) of the same charge or three leptons. The considered processes are $t\bar{t}$ and Ht production. For the $t\bar{t}$ production, one top quark decays via $t\rightarrow Hq$. The proton–proton collision data set analysed amounts to (140 fb -1 ) at $(\sqrt{s}={13}\,\hbox {TeV})$. No significant excess beyond Standard Model expectations is observed and upper limits are set on the $t\rightarrow Hq$ branching ratios at 95 % confidence level, amounting to observed (expected) limits of $\mathcal {B}(t\rightarrow Hu)<2.8\,(3.0) \times 10^{-4}$ and $\mathcal {B}(t\rightarrow Hc)<3.3\,(3.8) \times 10^{-4}$. Combining this search with other searches for tHq flavour-changing neutral-current interactions previously conducted by ATLAS, considering $H\rightarrow b\bar{b}$ and $H\rightarrow \gamma \gamma$ decays, as well as $H\rightarrow \tau ^{+}\tau ^{-}$ decays with one or two hadronically decaying τ-leptons, yields observed (expected) upper limits on the branching ratios of $\mathcal {B}(t\rightarrow Hu)<2.6\,(1.8) \times 10^{-4}$ and $\mathcal {B}(t\rightarrow Hc)<3.4\,(2.3) \times 10^{-4}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Numerical eigen-spectrum slicing, accurate orthogonal eigen-basis, and mixed-precision eigenvalue refinement using OpenMP data-dependent tasks and accelerator offload

Performing a variety of numerical computations efficiently and, at the same time, in a portable fashion requires both an overarching design followed by a number of implementation strategies. All of these are exemplified below as we present transitioning the PLASMA numerical library from relying on dependence-driven large tasks to achieving utilization of fine grain tasking and offload to hardware accelerators while keeping its core dependence sets: OpenMP source code pragmas and runtime for most system-level functionality and basic low-level numerical kernels provided directly by hardware vendors or open source projects with vendor contributions. We also present new algorithmic methods and their efficient parallel implementations including fine grained tasking for eigen-spectrum slicing and offload for mixed-precision eigenvalue refinement. We provide performance, scaling, and numerical results showing sizable gains over the available solutions from either the open source and vendor-provided packages.

Luszczek, Piotr↗

Characterization and Optimization of Building Blocks for Specialized Computing Platforms

As noise limits the performance of quantum processors, the ability to characterize this noise and develop methods to overcome it is essential for the future of quantum computing. In this report, we develop a complete set of tools for improving quantum processor performance at the application level, including low-level physical models of quantum gates, a numerically efficient method of producing process matrices that span a wide range of model parameters, and full-channel quantum simulations. We then provide a few examples of how to use these tools to study the effects of noise on quantum circuits.

42 ENGINEERING↗

Reducing Energy Use and Making Energy More Efficient in Noorvik (Final Technical Report)

Final technical report for Remote Alaska Communities Energy Efficiency (RACEE)-funded project for the City of Noorvik. The community reduced per capita energy usage by 18% from 2010 levels by participating in the three phase project that included goal setting, technical assistance, and implementation funding.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Review of Non-Regulatory Energy Efficiency Measures in the United States

Increasing energy efficiency is ubiquitous in many economies, and several mechanisms for achieving this increase, from mandatory policies to voluntary initiatives, have been proposed and implemented. In the United States, the Department of Energy, during the development of its energy conservation standard rules, evaluates the benefits from several of these mechanisms. In this report, we review how estimates of benefits from two types of voluntary energy efficiency initiatives – rebates and voluntary energy efficiency targets (VETs) – compare to the same benefits estimated for minimum energy efficiency standards (MEPS) established in the United States for residential appliances, commercial and industrial equipment, and lighting applications (referred to simply as “products” for the remainder of this report) between 2010 and 2020. Our results show that, overall, these two voluntary measures are estimated to provide, altogether, 36% of the total energy savings estimated to be provided by new efficiency standards, with a total net-present value that corresponds to 52% of the net-present value estimated for standards. When considering all energy conservation rules reviewed in this report, the energy savings a rebate program is estimated to achieve ranges from less than 1% to 86% of the savings from new standards set for the same type of product and at the same level of energy efficiency. As for VETs, the energy savings range from less than 1% to 78% of the savings from standards. Results vary widely across types of products due to (a) the relevance of the monetary incentive relative to incremental upfront costs considered for each type of product, and (b) the estimated level of market barriers associated with each type of product. While voluntary energy efficiency initiatives are not as effective as MEPS in transforming the market and raising the bar of energy efficiency for energy consuming goods in an economy, when applied in tandem with MEPS they can be powerful instruments for promoting and increasing energy efficiency in the economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Safeguards Considerations for Coated Particle Fuel Fabrication Facilities

This study aims to identify where existing fuel fabrication safeguards are limited in application to coated particle fuel fabrication facilities; perform a review of techniques that may be appropriate to address these limitations; and identify where further study is required. The purpose is to ensure the necessary technology and safeguards developments are established to facilitate safeguards-by-design for coated particle fuel fabrication facilities, analogous to the research and development (R&D) efforts in the advanced reactor space, including those requiring coated particle fuels and progress to higher technology readiness levels. Finally, this study will also help meet high priority objectives set forth by the IAEA in establishing safeguards R&D precedence and measurement/procedural standards at emerging fuel fabrication facilities. To achieve these objectives, the report is formatted to (1) distill relevant background information on fuel fabrication of oxide and coated particle fuels; (2) provide an overview of the fuel fabrication techniques for a reference oxide fuel fabrication facility and two selected TRISO fuel fabrication facilities; (3) develop facility models of safeguards approaches for the reference facility and the two TRISO facilities; and (4) identify any observed technology needs or gaps from this analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sensitivity Analysis Tool for Electrochemical Conversion of CO2 to CO

Data presented in poster is sourced from the Electrochemical Catalyst Sensitivity Analysis Tool. This tool comprises a material balance model with cost estimation to estimate the levelized cost of product for CO production via CO2 electrolysis. A set of sensitivity analyses on key system and financial parameters is included with results so that users can test the impacts of these parameters on LCOP.

Henry, Samuel↗

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗

Co-located temperature and electrical resistivity measurements for permafrost mapping, Teller 27, Teller 47 and Kougarok 64, Seward Peninsula, Alaska, late summers of 2018, 2019, 2021, and 2022

This data set contains co-located shallow soil (0.8m below ground level) and electrical resistivity at various depth extracted from Electrical Resistivity Tomography (ERT) measurements. Data were acquired at three watersheds on the southern Seward Peninsula during the late summers of 2018, 2019, 2021, and 2022. The three watersheds are located along the Nome-Teller Highway at mile markers 27 and 47, and along Kougarok Road mile marker 64. The co-located temperature and electrical resistivity data were used to (1) map the spatial extend of near surface permafrost, and (2) for supervised classification of permafrost bodies. This dataset contains .csv, .txt, .srv files and flmd reporting format with data dictionary. Find information about the .srv files at "https://e4d-userguide.pnnl.gov/e4d_guide/elec/e4d_e4d-survey.html". The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗

Vectorization of CMSSW offline software

The CMS experiment has been utilizing vectorization, or SIMD, in parts of its data processing applications for over a decade. On x86 platforms the vectorization level is still SSE3. In the past attempts to use wider vector instruction sets such as AVX or AVX-512 have, in practice, not resulted in improvements in the overall event processing throughput, because the CPUs scale down their frequency when processing AVX instructions. In addition, a notable part of the global pool of CMS’ resources has been old systems either not supporting AVX, or where the CPU frequency downscaling impacts all cores of the CPU. CMS has nevertheless continued to vectorize more of its application code, and in this work we review profiling methods we have found effective to find out pieces of code that would benefit from vectorization, and techniques to transform those codes such that the GCC compiler is able to auto-vectorize those codes. The build system used for CMSSW, Scram, has also been enha nced to be able to build code for multiple CPU microarchitectures such that the shared libraries of desired microarchitecture level can be loaded based on the CPU of the system. This multi-microarchitecture setup is invisible to the workflow management system, which makes its deployment straightforward. We describe in detail how this multi-microarchitecture build is set up, and measure the impact of using wider vector units than SSE3 on the event processing throughput of CMS applications such as simulation and reconstruction on recent x86 CPUs.

Gartung, Patrick↗

Landau-level composition of bound exciton states in magnetic field

Here, we present a theory that studies the state composition of a bound exciton in magnetic field. Using a basis set made of products of free electron and hole wave functions in Landau gauge, we derive a secular equation which shows the relation between Landau levels (LLs) of the electron and hole when a bound exciton is formed. Focusing on excitons in the light cone, we establish a scattering selection rule for the interaction of an electron in LL 𝑛 e with a hole in LL 𝑛 h . We solve the resulting secular equation and identify a simple pairing law, 𝑛 e =𝑛 h +𝑙, which informs us on the construction of a bound exciton state with magnetic quantum number 𝑙, and on the interaction of the exciton magnetic moment with magnetic field. We obtain good agreement between theory results and recent measurements of the diamagnetic shifts of exciton states in WSe 2 monolayers.

2-dimensional systems↗

Understanding the Molecular‐level Interactions Between Ionic Liquids and Molecular Species to Design and Develop Novel Solvent Systems for Environmental and Energy Applications (DOE-EPSCoR – DE‐SC0020282 Final Technical Report)

The central theme of the work is to develop an understanding of the molecular-level interactions between ionic liquids and molecular species that govern a specific set of separations (aliphatic/aromatic, Topic I), reactions (SNAr, high-temp reactions, Topic II) and polymer (ultrahigh performance polymers, Topic III) synthesis processes through the synergistic application of synthesis, characterization and simulation. Understanding these interactions will provide significant insight into how to optimize these and other processes that are influenced by these interactions. An important additional goal is to build the collaborative infrastructure to enable the cluster researchers to develop professional relationships to enhance this and future research endeavors. This collaboration, the Alabama Advanced Solvents Cluster (AASC) is on ongoing collaborative effort between many of the investigators.

36 MATERIALS SCIENCE↗

GPS Spoofing Mitigation and Timing Risk Analysis in Networked Phasor Measurement Units via Stochastic Reachability

To address phasor measurement unit (PMU) vulnerability to spoofing, we propose the use of a set-valued state estimation technique known as stochastic reachability (SR)-based distributed Kalman filter (DKF) that computes secure global positioning system (GPS) timing across a network of receivers. Utilizing SR, we estimate not only GPS time but also its stochastic reachable set, which is parameterized by probabilistic zonotope (p-Zonotope). While requiring known measurement error bounds in only non-spoofed conditions, we designed a two-tiered approach. We first performed measurement-level spoofing mitigation via deviation of a measurement innovation from its expected p-Zonotope. We then performed state-level timing risk analysis via a determination of the intersection probability of the estimated p-Zonotope with an unsafe set that violates IEEE C37.118.1a-2014 standards. Finally, we validated our SR-DKF algorithm by subjecting it to a simulated receiver network to coordinate signal-level spoofing. We demonstrate improved timing accuracy and successful spoofing mitigation via the use of our SR-DKF algorithm. We also validated the robustness of the estimated timing risk as the number of receivers were varied.

47 OTHER INSTRUMENTATION↗

Behavioral and Population Data-Driven Distribution System Load Modeling

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to participate in grid services under Federal Energy Regulatory Commission Order No. 2222 [1]. In this study, we develop a methodology of modeling residential load profiles in different geographic areas with a focus on human behavior impact. First, we construct a behavior-based load profile model leveraging state-of-the-art appliance models. We simulate human activity and occupancy using Markov chain Monte Carlo methods calibrated with the American Time Use Survey data set. Second, we link our model with cleaned Current Population Survey data from the U.S. Census Bureau. Finally, we populate two sets of 500 households using California and Texas census data, respectively, to perform an initial analysis of the load in different geographic areas with various group features (e.g., different income levels). To distinguish the effect of population behavior differences on aggregated load, we simulate load profiles for both sets assuming fixed physical household parameters and weather data. Analysis shows that average daily load profiles vary significantly by income and income dependency varies by locality.

American Time Use Survey↗