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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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DOE OSTI2024

A Cohesive Deep Drilling Field Strategy for LSST Cosmology

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will image billions of astronomical objects in the wide–fast–deep primary survey and in a set of minisurveys including intensive observations of a group of deep drilling fields (DDFs). The DDFs are a critical piece of three key aspects of the LSST Dark Energy Science Collaboration (DESC) cosmological measurements: they provide a required calibration for photometric redshifts (photo- z ) and weak gravitational lensing (WL) measurements and they directly contribute to cosmological constraints from the most distant Type Ia supernovae (SNe Ia). We present a set of cohesive DDF strategies fulfilling science requirements relevant to DESC and following the guidelines of the Survey Cadence Optimization Committee. We propose a method to estimate the observing strategy parameters and we perform simulations of the corresponding surveys. We define a set of metrics for each science case to assess the performance of the proposed observing strategies. We show that the most promising results are achieved with deep rolling surveys characterized by two sets of fields: ultradeep fields ( z ≲ 1.1) observed at a high cadence with a large number of visits over a limited number of seasons, and deep fields ( z ≲ 0.7), observed with a cadence of ~3 nights for 10 yr. These encouraging results should be confirmed with realistic simulations using the LSST scheduler. A DDF budget of ~8.5% is required to design observing strategies satisfying all the cosmological requirements. A lower DDF budget leads to surveys that either do not fulfill the photo- z /WL requirements or are not optimal for SN Ia cosmology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

PARTICLE ACCELERATION AND HEATING BY TURBULENT RECONNECTION

Turbulent flows in the solar wind, large-scale current sheets, multiple current sheets, and shock waves lead to the formation of environments in which a dense network of current sheets is established and sustains “turbulent reconnection.” We constructed a 2D grid on which a number of randomly chosen grid points are acting as scatterers (i.e., magnetic clouds or current sheets). Our goal is to examine how test particles respond inside this large-scale collection of scatterers. We study the energy gain of individual particles, the evolution of their energy distribution, and their escape time distribution. We have developed a new method to estimate the transport coefficients from the dynamics of the interaction of the particles with the scatterers. Replacing the “magnetic clouds” with current sheets, we have proven that the energization processes can be more efficient depending on the strength of the effective electric fields inside the current sheets and their statistical properties. Using the estimated transport coefficients and solving the Fokker–Planck (FP) equation, we can recover the energy distribution of the particles only for the stochastic Fermi process. We have shown that the evolution of the particles inside a turbulent reconnecting volume is not a solution of the FP equation, since the interaction of the particles with the current sheets is “anomalous,” in contrast to the case of the second-order Fermi process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Analysis of RF Surface Loss in a Planar 2D Qubit

The Josephson junction and shunt capacitor form a transmon qubit, which is the cornerstone of modern quantum computing platforms. For reliable quantum computing, it is important how long a qubit can remain in a superposition of quantum states, which is determined by the coherence time (T1). The coherence time of a qubit effectively sets the "lifetime" of usable quantum information, determining how long quantum computations can be performed before errors occur and information is lost. There are several sources of decoherence in transmon qubits, but the predominant one is generally considered to be dielectric losses in the natural oxide layer formed on the surface of the superconductor. In this paper, we present a numerical study of microwave surface losses in planar superconducting antennas of different transmon qubit designs. An asymptotic method for estimating the energy participation ratio in ultrathin films of nanometer scales is proposed, and estimates are given for the limits of achievable minimum RF losses depending on the electrical properties of the surface oxide and the interface of the qubit with the substrate material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Evaluation of the new capture vapourizer for aerosol mass spectrometers (AMS) through laboratory studies of inorganic species

Aerosol mass spectrometers (AMSs) and Aerosol Chemical Speciation Monitors (ACSMs) commercialized by Aerodyne are widely used to measure the non-refractory species in submicron particles. With the standard vapourizer (SV) that is installed in all commercial instruments to date, the quantification of ambient aerosol mass concentration requires the use of the collection efficiency (CE) to correct for the loss of particles due to bounce. Thus, a new capture vapourizer (CV) has been designed to reduce the need for a bounce-related CE correction. Two high-resolution AMS instruments, one with a SV and one with a CV, were operated side by side in the laboratory. Four standard species, NH 4 NO 3 , NaNO 3 , (NH 4 ) 2 SO 4 and NH 4 Cl, which typically constitute the majority of the mass of ambient submicron inorganic species, are studied. The effect of vapourizer temperature ( T v ∼ 200–800 °C) on the detected fragments, CE and size distributions are investigated. A T v of 500–550 °C for the CV is recommended. In the CV, CE was identical (around unity) for more volatile species (e.g. NH 4 NO 3 ) and comparable to or higher than the SV for less-volatile species (e.g. (NH 4 ) 2 SO 4 ), demonstrating an improvement in CE for laboratory inorganic species in the CV. The detected relative intensities of fragments of NO 3 and SO 4 species observed with the CV are different from those observed with the SV, and are consistent with additional thermal decomposition arising from the increased residence time and multiple collisions. Increased residence times with the CV also lead to broader particle size distribution measurements than with the SV. A method for estimating whether pure species will be detected in AMS sizing mode is proposed. Production of CO 2 (g) from sampled nitrate on the vapourizer surface, which has been reported for the SV, is negligible for the CV for NH 4 NO 3 and comparable to the SV for NaNO 3. . We observe an extremely consistent fragmentation for ammonium compared to very large changes for the associated anions. Together with other evidence, this indicates that it is unlikely that a major fraction of inorganic species vapourizes as intact salts in the AMS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2020

Membrane interactions of the globular domain and the hypervariable region of KRAS4b define its unique diffusion behavior

The RAS proteins are GTP-dependent switches that regulate signaling pathways and are frequently mutated in cancer. RAS proteins concentrate in the plasma membrane via lipid-tethers and hypervariable region side-chain interactions in distinct nano-domains. However, little is known about RAS membrane dynamics and the details of RAS activation of downstream signaling. Here, we characterize RAS in live human and mouse cells using single-molecule-tracking methods and estimate RAS mobility parameters. KRAS4b exhibits confined mobility with three diffusive states distinct from the other RAS isoforms (KRAS4a, NRAS, and HRAS); and although most of the amino acid differences between RAS isoforms lie within the hypervariable region, the additional confinement of KRAS4b is largely determined by the protein’s globular domain. To understand the altered mobility of an oncogenic KRAS4b, we used complementary experimental and molecular dynamics simulation approaches to reveal a detailed mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Scintillation Light Triggering Efficiency in MicroBooNE

The MicroBooNE Liquid Argon Time Projection Chamber (LArTPC) has been running since 2015 as part of the Short-Baseline Neutrino (SBN) program at Fermilab and is designed to contribute to address the elusive eV sterile neutrino anomaly. MicroBooNE records both the ionisation charge and scintillation light produced inside the TPC. The latter is collected through PhotoMultiplier Tubes (PMTs) and used for accurate timing and triggering. Having an accurate knowledge of the triggering efficiency at low energies is a key element for the success of MicroBooNE analyses, and the methods developed to obtain can be used by future LArTPCs, especially in the SBN program. For this reason MicroBooNE is developing a data driven method to estimate the trigger efficiency of scintillation light. The goal of this poster is to present a preliminary analysis of calculating this efficiency in MicroBooNE using cosmic ray muons. Results of this analysis will be crucial for many analyses that aim to me asure low energy interactions, and inform triggering strategies in LArTPCs in the SBN and future DUNE program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗
DOE OSTI2020

Processing unit performance projection using dynamic hardware behaviors

Methods for estimating accelerator performance for dynamic hardware behaviors are disclosed. Computer program code to be executed on a first processing unit is received, and an execution of the computer code on the first processing unit is monitored to determine a plurality of performance characteristics. A plurality of dynamic hardware behaviors is determined by applying a clustering algorithm to the performance characteristics, and an equivalent accelerator portion of computer code to be executed on a second processing unit is generated by translating a set of instructions in a first portion of computer code corresponding to a first one of the plurality of dynamic hardware behaviors to an equivalent set of instructions to be executed on the second processing unit. An estimated measure of performance for executing the equivalent accelerator portion on the second processing unit is determined for the first one of the plurality of dynamic hardware behaviors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cooling charge determination for a local thermal management system

A system and method for estimating the state of charge, i.e., the amount of cooling remaining, in a latent heat thermal storage module of a local environmental control system. The local environmental control system stores cooling energy at night by freezing a latent heat phase change material (PCM), and then releasing the stored cooling energy by removing heat from room air flowing through the PCM during the day. Differential temperature sensors are used measure the air temperature drop across the latent thermals storage unit and the fan voltage, which is directly related to fan air flow rate, is sampled. A controller is programmed to determine the charging state from these measurements.

Khalifa, H. Ezzat↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2022

System and method of performing a range estimation for hybrid and electric vehicles

A system is provided for performing an automated range estimation process for an electric vehicle using a processor. Included in the system is a range estimator configured to estimate an initial value of an energy required to travel a unit distance for the electric vehicle. The range estimator generates a first estimation model based on a correlation between a maximum all-electric-range and the energy required to travel a unit distance. Then, the first estimation model is adjusted based on one or more predetermined driving conditions. The maximum all-electric-range of the electric vehicle is updated based on the adjusted first estimation model. An estimated range of the electric vehicle is calculated based on the updated maximum all-electric-range of the electric vehicle and a fraction of total energy capability remaining in the electric vehicle. The estimated range of the electric vehicle is outputted and is used to control the electric vehicle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Thermal Constraint Violations as a Result of Ambient Adjusted Transmission Line Ratings

Ambient Adjusted Ratings allow transmission line current ratings to be increased above static ratings while requiring minimal weather monitoring. However, Ambient Adjusted Ratings are still contingent on static parameters that may not match real world conditions. This poster examines how simulation methods can estimate the extent to which using Ambient Adjusted Ratings could result in the violation of a transmission line's thermal constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Neutron Resonance Theory for Nuclear Reactor Applications: Modern Theory and Practices

The neutron resonance phenomena constitute one of the most fundamental subjects in nuclear physics as well as in reactor physics. It is the area where the concepts of nuclear interaction and the treatment of the neutronic balance in reactor fuel lattices become intertwined. The latter requires the detailed knowledge of resonance structures of many nuclides of practical interest to the development of nuclear energy. The most essential element in reactor physics is to provide an accurate account of the intricate balance between the neutrons produced by the fission process and neutrons lost due to the absorption process as well as those leaking out of the reactor system. The presence of resonance structures in many major nuclides obviously plays an important role in such processes. There has been a great deal of theoretical and practical interest in resonance reactions since Fermi’s discovery of resonance absorption of neutrons as they were slowed down in water. The resonance absorption became the center of attention when the question was raised as to the feasibility of the self-sustaining chain reaction in a natural uranium-fueled system. The threshold of the nuclear era was crossed almost eighty years ago when Fermi and Szilard observed that a substantial reduction in resonance absorption is possible if the uranium was made into the form of lumps instead of a homogeneous mixture with water. In the West, the first practical method for estimating the resonance escape probability in a reactor cell was pioneered by Wigner et al in early forties. (author)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Mitigation Methods for Piperazine Oxidation in Post-Combustion Carbon Capture

Piperazine is a promising second-generation solvent for amine scrubbing in post-combustion CO2 capture. However, the oxidative degradation of PZ can cause environmental problems and economic loss. This work presents the effects of two mitigation methods: carbon treating and N2 sparging, on the PZ oxidation in long-term operations. The species and their respective quantities adsorbed by the activated carbon were tested in a bench-scale device. The carbon was then tested in the High Temperature Oxidation Reactor (HTOR), where the solvent oxidizes at a reasonably fast rate. Pilot plant campaigns were also performed at the UT Austin SRP and the National Carbon Capture Center (NCCC) and the effects were verified. When dissolved Fe is removed by carbon treating or other methods, available soluble Fe in the system dissolves and replaces the dissolved Fe. Therefore, all available Fe and ligands need to be removed for the mitigation to be effective. The sources of soluble Fe include fly ash and the corrosion of stainless steel, and the ligands are degradation products. 8 All PZ degraded solvents have two absorbance peaks at 320 nm and 538 nm. The 320 nm peak is caused by dissolved metals, especially Fe, complexed by degradation products. The 320 nm peak is related to the amine degradation level and can be used as a simple and efficient method to estimate the amine degradation rate. The pilot plant data suggest that NO2 can oxidize PZ significantly, possibly through radical reactions. 0.01 mmol/kg-hr absorption of NO2 increased the PZ oxidation rate from 1.2 mmol/kg-hr to 2.5 mmol/kg-hr.

Yuying, Wu↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2024

Method for Spatiotemporal Solar Power Profile Estimation for a Proposed U.S.–Caribbean–South America Super Grid under Hurricanes

Solar photovoltaic (PV) generation technology stands out as a scalable and cost-effective solution to enable the transition toward decarbonization. However, PV solar output, beyond the daily solar irradiance variability and unavailability during nights, is very sensitive to weather events like hurricanes. Hurricanes nucleate massive amounts of clouds around their centers, shading hundreds of kilometers in their path, reducing PV power output. This research proposes a spatiotemporal method, implemented in MATLAB R2023b coding, to estimate the shading effect of hurricanes over a wide distribution of PV solar plants connected to a high-voltage power infrastructure called the U.S.–Caribbean–South America super grid. The complete interconnection of the U.S., the Caribbean, and South America results in the lowest power valley levels, i.e., an overall percentual reduction in PV power output caused by hurricane shading. The simulations assess the impact of hurricanes in 10 synthetic trajectories spanning from Texas to Florida. The Caribbean would also experience lower power valleys with expanded interconnectivity schemes. The U.S.–Caribbean–South America super grid reduces Caribbean variability from 37.8% to 8.9% in the case study. The proposed spatiotemporal method for PV power profile estimation is a valuable tool for future solar power generation expansion, transmission planning, and system design considering the impact of hurricanes.

14 SOLAR ENERGY↗