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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

tbsinp (00)

The ice nucleation spectrometer (INS) is an offline analytical measurement system used to process filter samples for freezing temperature spectra of immersion-mode ice-nucleating particle (INP) number concentrations. It is almost identical to the Colorado State University (CSU) ice spectrometer design. The INS-AIR is specific to filter samples collected on aerial platforms, such as the DOE ARM tethered balloon system (TBS) operated by Sandia National Laboratories, using miniaturized aerosol filter samplers. Users are referred to the INS instrument handbook for INS-AIR sampler details. INS-AIR filter samples are collected during intensive operational periods at various ARM sites and then processed on the INS at CSU. This filter log contains the detailed metadata at all ARM sites where INP filter sample collection has occurred or is currently ongoing, including both ground-based routine INP sampling (INS) and TBS INP sampling (INS-AIR). Metadata include start and end times, vacuum line pressures and temperatures, and flow rates; total accumulated flow through each filter; and notes on collection issues or weather conditions. Users can also keep up to date with the status of filter and data processing, even before data are available on ARM’s Data Discovery. Users can contact INP mentors Jessie Creamean or Thomas Hill with any questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

US Participation in Valahia 2023

In response to invitation to participate in the Valahia, Romania 2023 Full Field Exercise in October, 2023, host country is requesting exercise objectives and resource needs from the US Aerial Measuring System participants. This document is to illustrate to the IAEA 3rd Consultancy Workshop meeting on Marc 6-7, 2023 (virtually) what will be expected from AMS at the exercise.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Truncated non-linear interferometer-based sensor system

A truncated non-linear interferometer-based sensor system includes an input that receives an optical beam and a non-linear amplifier that generates a probe beam and a conjugate beam from the optical beam. The system's local oscillators are related to the probe beam and the conjugate beam. The system includes a sensor that transduces an input with the probe beam and the conjugate beam. The transduction detects changes in the phase of each of the probe beam and the conjugate beam. The system's phase sensitive detectors detect phase modulations between the respective local oscillators, the probe beam, and the conjugate beam and outputs phase signals based on detected phase modulations. The system measures phase signals indicative of the sensor's input resulting from a sum or difference of the phase signals. The measurement exhibits a quantum noise reduction in an intensity difference, a phase sum, or an amplitude difference quadrature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Microwave Photonics Optical Fiber Method for Measuring Distributed Strain for Hydrologic Applications in the Vadose and Saturated Zones

Distributed strain measurements appear to hold significant potential for monitoring hydrologic processes. Coherence-length-gated Microwave Photonics Interferometry (CMPI) is a distributed sensing technique that measures strain in an optical fiber by reading optical interference phase changes in the microwave domain. The technique provides 10nε resolution when cm spatial resolution is applied. CMPI was used to measure the strain caused by small periodic variations in air pressure (25 Pa amplitude and 4 Hz) in a sand-filled laboratory column used to represent barometric loading in the vadose zone. The strain varied as a periodic function with an amplitude that decreased and a phase that increased with depth. The distribution of amplitude and phase of the strain depended on the water saturation, permeability, and presence of a barrier at the top of the sand. A theoretical analysis suggests that the air pressure diffusivity estimated from pressure data is similar to the diffusivity estimated from the distributed strain. These results indicated that the CMPI distributed strain measurement system could be used to improve monitoring and characterization of the vadose and underlying saturated zone.

Hua, Liwei↗
DOE OSTI2024

Destructive Examination Protocol for 3013-Container-Package Storing Plutonium-Bearing Materials

The 3013-container-package consists of a convenience, inner and outer container and is used for long-term storage of plutonium-bearing materials. A destructive examination (DE) protocol has been developed to examine the container package visually and with microscopic aid to find any corrosion conditions that could result in the loss of the integrity of the container package over its lifetime. The DE protocol contains three main steps: initial container examination, helium (He) leak testing, and detailed imaging and analysis of the inner container closure weld region (ICCWR). The ICCWR has been determined to be bounding, defined as exhibiting worst case conditions for stress corrosion cracking (SCC) of the inner container. To assess SCC in the ICCWR, the inner container lid is cut into quarters and the weld and He-leak testing gasket are removed. Then a citric acid wash is performed to remove adherent chlorides from the ICCWR. The wash is then sent for analysis to determine the concentration of chlorides in the ICCWR. While the analysis for chloride concentration is being performed, the quarter sections are further sectioned into 1/8th subsections by cutting each section in half. These subsections are washed using nitric acid to remove corrosion products. Then each subsection is imaged using a Wide Angle 3-D Measurement System (WAMS). After analysis of microscope images for potential SCC, additional imaging can be performed, including subsurface imaging. After review, a determination is made of whether the container integrity may potentially affect the safe storage of the material.

container↗
DOE OSTI2023

A novel Doppler backscattering (DBS) system to simultaneously measure radio frequency plasma fluctuations and low frequency turbulence

A novel quadrature Doppler Backscattering (DBS) system has been developed and optimized for the E-band (60–90 GHz) frequency range using either O-mode or X-mode polarization in DIII-D plasmas. In general, DBS measures the amplitude of density fluctuations and their velocity in the lab frame. The system can simultaneously monitor both low-frequency turbulence (f < 10 MHz) and radiofrequency plasma density fluctuations over a selectable frequency range (20–500 MHz). Detection of high-frequency fluctuations has been demonstrated for low harmonics of the ion cyclotron frequency (e.g., 2f ci ~ 23 MHz) and externally driven high-frequency helicon waves (f = 476 MHz) using an adjustable frequency down conversion system. Importantly, this extends the application of DBS to a high-frequency spectral domain while maintaining important turbulence and flow measurement capabilities. This unique system has low phase noise, good temporal resolution (sub-millisecond), and excellent wavenumber coverage (k θ ~ 1–20 cm –1 and kr ≲ 30 cm –1 ). As a demonstration, localized internal DIII-D plasma measurements are presented from turbulence (f ≤ 5 MHz), Alfvenic waves (f ~ 6.5 MHz), ion cyclotron waves (f ≥ 20 MHz), as well as fluctuations around 476 MHz driven by an external high-power 476 MHz helicon wave antenna. In the future, helicon measurements will be used to validate GENRAY and AORSA modeling tools for prediction of helicon wave propagation, absorption, and current drive location for the newly installed helicon current drive system on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Method and system to separate optically measured coupled parameters

A system includes a first optical sensor sensitive to both a parameter of interest, Parameter1, and at least one confounding parameter, Parameter2 and a second optical sensor sensitive only to the confounding parameter. Measurement circuitry measures M1 in response to light scattered by the first optical sensor, where M1=value of Parameter1+K*value of Parameter2. The measurement circuitry also measures M2 in response to light scattered by the second optical sensor, where M2=value of Parameter2. Compensation circuitry determines a compensation factor, K, for the confounding parameter based on measurements of M1 and M2 taken over multiple load/unload cycles or over one or more thermal cycles. The compensation factor is used to determine the parameter of interest.

Ganguli, Anurag↗
DOE OSTI2020

From IEC 61853 power measurements to PV system simulations.

The IEC 61853 PV module energy rating standard requires measuring module power (and hence efficiency) over a matrix of irradiance and temperature conditions. These matrix points represent nearly the full range of operating conditions encountered in the field in all but the most extreme locations, and create an opportunity to develop alternative approaches to existing modelssuch as the single-diode models and the Sandia Array Performance Modelfor calculating system performance. This report begins by discussing the bilinear interpolation and extrapolation method from IEC 61853-3, and then describes four existing model-based methods that could be used with matrix measurements. Then a new model is developed and all options are compared according to seven objective criteria using the matrix measurements of four PV modules of different technologies. The results show that the new model is an excellent candidate for launching power matrix-based PV system simulations.

14 SOLAR ENERGY↗
DOE OSTI2022

Design and performance of a variable gap system for thermal conductivity measurements of high temperature, corrosive, and reactive fluids

We report high-temperature fluids such as molten salts, liquid metals, and gasses are being proposed for many advanced energy systems including thermal energy storage devices, concentrating solar plants, and advanced nuclear reactor designs. However, the chemical behavior and thermophysical properties of many of these fluids have not been well characterized, which hinders the design, modeling, safety analysis, and deployment of these systems. Thermal conductivity is a property that is especially limited by existing measurement capabilities, which are subject to errors caused by convection, material interaction, radiative heat transfer, and instrument degradation. Therefore, there is a lack of standard, systematic measurement techniques for high-temperature, reactive, and corrosive fluids. In this work, the development of a variable gap thermal conductivity measurement system is detailed. The system is designed to measure the thermal conductivity of highly corrosive and reactive fluids, and survive operation between 100 °C and 800 °C. The effects of convection are minimized by limiting the thickness of the specimen to thin sizes (<0.3 mm). Corrections for radiative heat transfer were included in the working equations to consider specimens with varying optical properties. The design, construction, instrumentation, operating principles, and data analysis techniques are discussed in detail. The system was tested up to 500 °C using helium gas and molten KNO 3 -NaNO 3 to verify the measurement technique and determine the sources of error. At 300 and 400 °C KNO 3 -NaNO 3 , results showed maximum relative error of 6% when compared to results in the literature. The helium results were within 13% of those in the literature at 300 and 400 °C. Higher errors were observed at 500 °C for both fluids, and the sources of these errors are discussed.

42 ENGINEERING↗
DOE OSTI2023

Development of a large-mass, low-threshold detector system with simultaneous measurements of athermal phonons and scintillation light

For this work, we have combined two low-threshold detector technologies to develop a large-mass, low-threshold detector system that simultaneously measures the athermal phonons in a sapphire detector while an adjacent silicon high-voltage detector detects the scintillation light from the sapphire detector. This detector system could provide event-by-event discrimination between electron and nuclear events due to the difference in their scintillation light yield. While such systems with simultaneous phonon and light detection have been demonstrated earlier with smaller detectors, our system is designed to provide a large detector mass with high amplification for the limited scintillation light. Future work will focus on at least an order of magnitude improvement in the light collection efficiency by having a highly reflective detector housing and custom phonon mask design to maximize light collection by the silicon high-voltage detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Dynamic signal recovery in distribution grids using compressive lossy measurements

Distribution system state estimation requires reliable aggregation of the measured data. However, the large volume of the measured data imposes a significant stress on the underlying communication infrastructure. With the challenges associated with measurement availability, current distribution systems are typically unobservable. To cope with the unobservability issue, compressive sensing theory allows us to recover system state information from a small number of measurements provided the states of the distribution system exhibit sparsity. In this paper, we evaluate the robustness of an updated Kalman filtered modified compressive sensing (KF-ModCS) technique that dynamically estimates the grid states using a small fraction of measured data. In practice, measurements used for sparsity based state estimation may also be intermittent due to communication network induced losses. Further, to understand the effect of packet losses on KF-ModCS, we provide an upper bound for the expected variances of the state estimation error for a given rate of information loss. This upper bound is further improved if the support set of the sparse signal that characterizes the state dynamics does not change over time and/or the reduced model is observable. Simulations based on two practical data sets collected from actual customers in a distribution grid validate the theoretical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Thermodynamic properties of the Nd-Bi system via emf measurements, $\mathrm{DFT}$ calculations, machine learning, and $\mathrm{CALPHAD}$ modeling

Thermodynamic properties of the Nd-Bi system were investigated using a combination of experimental measurements, first-principles calculations based on density functional theory (DFT), data mining and machine learning (DM + ML) predictions, and calculation of phase diagrams (CALPHAD) modeling. The electromotive force (emf) of Nd-Bi alloys in molten LiCl-KCl-NdCl 3 at 773–973 K was measured via coulometric titration of Nd into Bi for the determination of thermochemical properties such as activity coefficients and solubilities of Nd in Bi. A new peritectic reaction of [liquid + NdBi 2 = Nd 3 Bi 7 ] at 774 K was confirmed using differential scanning calorimetry, structural (X-ray diffraction), and microstructural (scanning electron microscopy) analyses. The unknown crystal structure of NdBi2 was suggested to be a mixture of the anti-La 2 Sb configuration and the La 2 Te-type configuration based on ML predictions for over 26,000 data-mined AB 2 -type configurations together with DFT-based verifications. Using the newly acquired experimental data and DFT-based calculations, the thermodynamic description of the Nd-Bi system was remodeled, and a more complete Nd-Bi phase diagram was calculated, including the Nd 3 Bi 7 compound, invariant transition reactions, and liquidus temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Statistical Performance of Forced Oscillation Detectors in the Presence of Missing Measurements

In bulk power systems, measurement-based monitoring for large oscillations can help maintain system reliability. One of the challenges encountered in a recent field demonstration was the unavailability of measurements due to underlying measurement quality or communication problems. During the demonstration, the oscillation detector ignored a measurement location if even 10 seconds of data was missing. To extend the detector's ability to operate in these conditions, this paper evaluates the impact of three methods for addressing missing data. The strengths and weaknesses of each approach are evaluated using theoretical expressions for the probability of detection along with results from simulated data and publicly available field measurements. Based on these results, a suitable approach is identified that can extend the oscillation detector's performance when large segments of data are missing.

Follum, James D.↗
DOE OSTI2024

Forecasting high-dimensional spatio-temporal systems from sparse measurements

This paper introduces a new neural network architecture designed to forecast high-dimensional spatio-temporal data using only sparse measurements. The architecture uses a two-stage end-to-end framework that combines neural ordinary differential equations (NODEs) with vision transformers. Initially, our approach models the underlying dynamics of complex systems within a low-dimensional space; and then it reconstructs the corresponding high-dimensional spatial fields. Many traditional methods involve decoding high-dimensional spatial fields before modeling the dynamics, while some other methods use an encoder to transition from high-dimensional observations to a latent space for dynamic modeling. In contrast, our approach directly uses sparse measurements to model the dynamics, bypassing the need for an encoder. This direct approach simplifies the modeling process, reduces computational complexity, and enhances the efficiency and scalability of the method for large datasets. We demonstrate the effectiveness of our framework through applications to various spatio-temporal systems, including fluid flows and global weather patterns. Although sparse measurements have limitations, our experiments reveal that they are sufficient to forecast system dynamics accurately over long time horizons. Our results also indicate that the performance of our proposed method remains robust across different sensor placement strategies, with further improvements as the number of sensors increases. This robustness underscores the flexibility of our architecture, particularly in real-world scenarios where sensor data is often sparse and unevenly distributed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Building partnerships for development of sustainable energy systems with atmospheric measurements

Atmospheric dynamics often play a critical role in the sustainability and reliability of diverse forms of energy production. This is especially true for the growing number of renewable energy deployments that harness aspects of the environment for power production. While the University of Memphis has a strong research background in energy systems, we have little experience working with the Earth and Environmental Systems Science Division (EESSD) and their associated User Facilities. Of particular interest to us is the Atmospheric Science Research and the Atmospheric Radiation Measurement (ARM) user facility to address surface-boundary layer interactions and physical phenomena. One of the major challenges for understanding and developing energy systems and management platforms is accurate modeling/forecasting of atmospheric conditions across disparate spatial and temporal scales. These conditions are often required to understand the lowest levels of the atmospheric boundary layer, but are also important to understand higher atmospheric conditions where aerosols affect cloud development. The objective of this work was to develop partnerships with national laboratories for collaboration on environmental science and its intersection with sustainable energy systems, as well as to leverage the ARM user facility data repositories to enhance our research capabilities in energy systems and their inter-dependence on environmental systems for future engagement with EESSD. Specifically, we accomplished these objectives by (1) developing collaborations with Oakridge National Laboratory ARM Data Science and Integration Group which resulted in student internships, (2) employed ARM data to develope modeling of the atmospheric boundary layer optical turbulence, and (3) optimally-sized large-scale renewable energy systems and their associated energy storage systems with ARM repository data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗