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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 235 records · Page 13

Blockchain-Based Man-in-the-Middle (MITM) Attack Detection for Photovoltaic Systems

Cybersecurity of photovoltaic (PV) systems entails a much larger scope than just encryption and firewall of communications. For instance, integrity of data in transit between inverters and a cloud server can be compromised by authorized third-party, devices, and internal network within security perimeter (i.e., man-in-the-middle (MITM) attack). To address this challenge, this paper proposes a blockchain-based MITM attack detection method for a PV system. A breakthrough method includes screening network data, network intrusion detection, and hash comparison of in-transit data using distributed ledgers. Furthermore, the proposed method is implemented in Internet-of-Thing (IoT) security modules as clients of a blockchain network and validated by experiments.

blockchain↗

Measurement of $\Delta m^2_{32}$ and $\sin^2\!\theta_{23}$ using Muon Neutrino and Antineutrino Beams in the NOvA Experiment

NOvA is a long-baseline neutrino oscillation experiment located in the mid-west United States. It consists of two functionally identical tracking calorimeters, known as the near and far detector, that measure neutrino interactions induced by the NuMI beam at baselines of 1~km and 810~km. NuMI can be configured to provide a muon neutrino or antineutrino beam. Analysis of \numu~+~\numubar disappearance allows constraint of the $|\Delta m^2_{32}|$ and \sint oscillation parameters. This thesis presents the first NOvA disappearance results using both neutrino and antineutrino data - previous NOvA analyses have only used neutrino beam data. Two analysis improvements are delineated in dedicated chapters - the design of selection criteria to identify events that are fully contained in the far detector and the optimization of particle identification selection criteria in a multi-dimensional parameter space. The full-detector equivalent beam exposures used for this thesis are $8.85\ti mes 10^{20}$ and $6.91\times 10^{20}$~protons~on~target for neutrino and antineutrino data respectively. Under the assumption of a normal (inverted) neutrino mass hierarchy, analysis of the data gives $\Delta m^2_{32}=+2.49^{+0.09}_{-0.07}\times10^{-3}~\text{eV}^2$ ($\Delta m^2_{32}=-2.54\pm0.08\times10^{-3}~\text{eV}^2$) and $\sin^2\theta_{23} = 0.59\pm0.03$ ($\sin^2\theta_{23} = 0.44\pm0.03$). Maximal mixing ($\sin^2\theta_{23} = 0.5$) is disfavoured at the 1.7~\sig level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Industry Perspectives on Advanced Inverters for U.S. Solar Photovoltaic Systems. Grid Benefits, Deployment Challenges, and Emerging Solutions

To clarify current utility strategies and other considerations related to advanced inverter deployment, we interviewed 20 representatives from 11 leading organizations closely involved with advanced inverter pilot testing, protocols, and implementation. Included were representatives from seven utilities, a regional transmission operator, an inverter manufacturer, a leading solar developer, and a consortium for grid codes and standards. Interview data represent geographically the advanced inverter activities identified in SEPA's prior survey results--most interviewed utilities serve California, Arizona, and Hawaii, though we also interviewed others from the Northeast, Mid-Atlantic, and Southeast.

14 SOLAR ENERGY↗

Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models

The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.

artificial intelligence↗

Renewable Energy at NASA's Johnson Space Center

NASA's Johnson Space Center has implemented a great number of renewable energy systems. Renewable energy systems are necessary to research and implement if we humans are expected to continue to grow and thrive on this planet. These systems generate energy using renewable sources - water, wind, sun - things that we will not run out of. Johnson Space Center is helping to pave the way by installing and studying various renewable energy systems. The objective of this report will be to examine the completed renewable energy projects at NASA's Johnson Space Center for a time span of ten years, beginning in 2003 and ending in early 2014. This report will analyze the success of each project based on actual vs. projected savings and actual vs. projected efficiency. Additionally, both positive and negative experiences are documented so that lessons may be learned from past experiences. NASA is incorporating renewable energy wherever it can, including into buildings. According to the 2012 JSC Annual Sustainability Report, there are 321,660 square feet of green building space on JSC's campus. The two projects discussed here are major contributors to that statistic. These buildings were designed to meet various Leadership in Energy and Environmental Design (LEED) Certification criteria. LEED Certified buildings use 30 to 50 percent less energy and water compared to non-LEED buildings. The objectives of this project were to examine data from the renewable energy systems in two of the green buildings onsite - Building 12 and Building 20. In Building 12, data was examined from the solar photovoltaic arrays. In Building 20, data was examined from the solar water heater system. By examining the data from the two buildings, it could be determined if the renewable energy systems are operating efficiently. Objectives In Building 12, the data from the solar photovoltaic arrays shows that the system is continuously collecting energy from the sun, as shown by the graph below. Building 12 has two solar inverters, located on the second floor, that collected the data from the solar photovoltaic arrays. The data displayed here is the total energy produced by the system. These are cumulative amounts, so the last point on the graph shows all of the energy collected from the system since the start of its operation. The data shown here was manually collected from the solar inverters. However, the data is also automatically recorded through EBI. Through analysis of both sets of data it was determined that the EBI data was faulty. For example, from the manually collected data it can be determined that a total of 73 kWh of energy was collected between the dates of 1/16/2014 – 1/22/2014. The EBI data reports that approximately 17800 kWh of energy was collected during the same time frame. Not only does this exceed the time frame examined, but it also exceeds the total energy collected from the start of collection as recorded from the inverters. This leads to the belief that there is a malfunction with the automatic recording of the energy. In Building 20, data was examined from the solar water heater dating back many months and found that the pump for the solar water heater system was not operating properly, as exhibited in the graph shown below. The pump operates on a solar energy system, meaning that it collects energy throughout the day from the sun. Because of this, the system would stop operating shortly after the sun set because of a lack of sunlight. At that point, the graph should show a zero flow rate, but as exhibited in the graph below, that is not the case. It is clearly shown that the pump is continuously operating, even during the night. It was also observed that the majority of the time the pump would not turn on at all, despite good weather conditions. This led to the conclusion that the pump is malfunctioning, and needs to be examined and fixed.

McDowall, Lindsay↗

DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific exploration datasets needed to be acquired, cleaned, reformatted, and assembled in Leapfrog Geothermal. This GDR submission includes all of the cleaned and reformatted (X (m), Y (m), elevation (m), processed data values) datasets used to build the Leapfrog Geodata model. Existing datasets were acquired from the GDR, from AltaRock, and from other sources. This yielded the following datasets: - Digital elevation model produced from LiDAR data by Ramsey and Bard, 2016 - MT surveys from 2006, 2011, 2014, and 2017 (including single inversions) - Gravity surveys from 2006, 2007, and 2011 (including single) - Earthquake catalogs from PNSN, LLNL, and the Newberry EGS Demonstration project - Seismic velocity model from Templeton et al., 2014 - The Frone, 2015 temperature model and a new one produced through extrapolating downhole temperature measurements and the SMU temperature at depth maps. Two versions of the new model are provided: 250 m spacing and 500 m spacing - EarthVision geologic model with alteration from Moser et al., 2016 - Well data from EGS well 55-29, deep geothermal wells, coreholes (GEO N-2 through 5) and several thermal gradient holes - "Newberry Well Data:" Location, simple lithology, directional survey data, and temperature data for the 34 wells and coreholes used in the Newberry PFA Although there are additional 2D datasets available in the area, such as aeromagnetic surveys, these were not included in the analysis. While it may be possible to project these datasets into three dimensions by assuming the surface measurements do not vary with depth, this method is associated with high uncertainty. Preexisting inversions of these data were unavailable, and inverting additional geophysical datasets is outside the scope of this project.

15 GEOTHERMAL ENERGY↗

Analytical desmearing of Bonse–Hart ultra-small-angle neutron scattering data via truncated Abel inversion

A non-iterative analytical framework based on the truncated Abel inversion is developed for desmearing Bonse–Hart ultra-small-angle neutron scattering (USANS) data. The method directly inverts the slit-averaged intensity without empirical extrapolation or iterative regularization, establishing a closed-form relationship between the measured and intrinsic scattering profiles. Numerical benchmarks on representative models, including a rigid-line form factor, a Lorentzian function and a fractal structural model, demonstrate quantitative recovery of the ground-truth intensity across the full Q range. Application to a deuterated polystyrene/poly(2-vinylpyridine) blend further confirms that the approach yields smooth continuous profiles consistent with companion small-angle neutron scattering data. The truncated Abel inversion thus provides a stable, model-independent and physically transparent route for accurate desmearing of Bonse–Hart USANS measurements.

Huang, Guan-Rong [National Tsing Hua University, T↗

Reference model for CH4 and N2O and trends

Data from the Stratospheric and Mesospheric Sounder on Nimbus 7 were used as the basis for a model of the abundances of nitrous oxide and methane in the stratosphere. A version of this was produced two years ago (Taylor, Dudhia, and Rodgers - hereafter called the original paper) and in this new paper some of the possible error sources and long term trends are considered in more detail. The principle source of error in the SAMS retrievals is thought to be the use of climatological ozone profiles to invert the temperature profile data. However, it was found that the effect is too small, and of the opposite sign, to explain the discrepancies between satellite and in situ measurements, noted in the original paper. As expected, no systematic trends which exceed the estimated error in the data are found in either methane or nitrous oxide.

Taylor, F. W.↗

Effect of Blocking and Superconducting Layer Doping on the Superconductivity and Magnetic Properties of Polycrystalline Sr{sub 2}CaCu{sub 2}O{sub 6}

The possible difference in the properties upon doping the Sr{sub 2}CaCu{sub 2}O{sub 6} superconducting or blocking layers with Fe and Eu respectively was investigated in this work. The homogeneous Sr{sub 2−y}Eu{sub y}CaCu{sub 2}O{sub 6+δ} and Sr{sub 2}CaCu{sub 2−x}Fe{sub x}O{sub 6+δ} (y = 0, 0.1, 0.5, x = 0, 0.05) compounds were produced by a high-pressure synthesis route. Judging by the magnetic susceptibility measurements, all samples exhibit a superconductivity transition and the Eu/Fe concentration dependencies on the diamagnetic moment and average T{sub c} have been constructed using the experimental data. As a result, an unusual behavior of the T{sub c} value was observed for the samples with doped Eu: a fivefold reduction in the europium concentration in the sample does not give a noticeable effect on the transition temperature value while the diamagnetic signal becomes more stronger. Complex superconducting dome was found for Eu-doped material: 0.1 ≤ y ≤ 0.5 region T{sub c} vs. concentration data were approximated by inverted parabola-like curve with a maximum at y = 0.3. Difference in properties of the Eu and Fe-doped samples was also found in the behavior of the hysteresis loops showed the opposite orientations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Method and apparatus for determining wave characteristics using interaction with a known wave

The described system and method uses data from interaction between a known wave and an unknown wave to analyze or characterize the unknown wave using cross correlation frequency resolved optical gating (X-FROG). The system may obtain X-FROG trace data from the interaction between the two waves. The system analyzes the X-FROG trace data using a modified principal component generalized projection method strategy to invert the X-FROG trace data, analyzing or characterizing the unknown wave. Results of the analysis can be provided in real time and displayed.

Kane, Daniel James↗

Advancing Dynamic Modeling of Grid-Connected PV Inverter Using Bi-LSTM-Based AI Model

Power electronic converters (PECs) are widely used in modern power systems to facilitate the interconnection between various AC or DC sources and loads. Because of the extensive integration, the power system has grown into a more dynamic system in which the dynamics of the PECs must be adequately modeled. The paper presents a new bidirectional long short-term memory (Bi-LSTM) method for evaluating grid-connected inverter-based resources (IBR) dynamics. The method is tested using real hardware data from a grid -connected commercial inverter in laboratory experiments. Results show the Bi-LSTM model accurately reproduces the detailed IBR model's dynamics, even when the internal structure is unknown and parameters are unknown, preventing the disclosure of the manufacturer's confidential data.

Subedi, Sunil [ORNL] (ORCID:000000034069090X)↗

The use of atmospheric prediction models to invert infrasound for linear-equivalent time domain moment tensors: Source Physics Experiment, Phase 1

We invert far field infrasound data for the equivalent seismo-acoustic time domain moment tensor to assess the effects of variable atmospheric models as well as to quantify the relative contributions of two presumed source phenomena. The infrasound data was produced by a series of underground chemical explosions that were conducted during the Source Physics Experiment, (SPE) which was originally designed to study explosion-generated seismo-acoustic signal phenomena. The goal of the work presented herein is two-fold: the first goal is to investigate the sensitivity of the estimated time domain moment tensors to variability of the estimated atmospheric model. The second goal is to determine the relative contribution of two possible source mechanisms to the observed infrasonic wave field. Rather than using actual atmospheric observations to estimate the necessary atmospheric Green's functions, we build a series of atmospheric models that rely on publicly available, regional atmospheric observations and the assumption that the acoustic energy results from a linear combination of an underground isotropic explosion and surface spall. The atmospheric observations are summarized and interpolated onto a 3D grid to produce a model of sound speed at the time of the experiment. For each of four SPE acoustic datasets that we invert, we produced a suite of three atmospheric models, based on ten years of regional meteorological observations: an average model, which averages the atmospheric conditions for ten years prior to each SPE event, as well as two extrema models. We find that the inversion yields relatively repeatable results for the estimated spall source. Conversely, the estimated isotropic explosion source is highly variable. This suggests that the majority of the observed acoustic energy is produced by the spall source and/or our modeling of the elastic energy propagation, and it's subsequent conversion to acoustic energy via linear elastic-to-acoustic coupling at the free surface, is too simplistic.

58 GEOSCIENCES↗

Autonomous Inverter Controls for Resilient and Secure Grid Operation: Vector Control Design for Grid Forming

The project addresses both fundamental and practical challenges of GFM/GFL inverter control for the power grids with high inverter based resources (IBRs) penetration. A data- driven modeling technique is applied to accurately model dynamics of PWM inverters, including electromagnetic-transient (EMT). Systematic and integrative designs of grid- forming (GFM) and grid-following (GFL) primary controls are developed to guarantee system performance under either normal or abnormal operating conditions without violating constraints. This modeling and control framework provides black-start capability in case of an outage without relying on rotating generators, and its secondary control is also shown to enhance resilience against cyber-physical attacks.

14 SOLAR ENERGY↗

Quantitative proton radiography and shadowgraphy for arbitrary intensities

Charged-particle radiography and shadowgraphy data can be directly inverted to obtain a line-integrated transverse Lorentz force or a line-integrated transverse refractive index gradient if intensity modulations due to scattering and absorption are negligible, and angular deflections are small. We develop a new direct-inversion algorithm based on plasma physics and compare it to a new Monge–Ampère code and an existing power diagram code. The measured or source intensity is represented by electrons subject to drag, and the other intensity by fixed ions. The decrease in kinetic plus electrostatic energy determines convergence. The displacement of the electrons from their initial to their equilibrium positions determines the line-integrated force or refractive index gradient. We have implemented two approaches: PIC (particle in cell) and Lagrangian fluid, in 1-D and 2-D. The PIC code works for arbitrary intensities, can work efficiently in parallel, and can make use of existing codes. The Lagrangian code requires less memory and is faster than the PIC code without massively parallel processing, but fails in 2-D for large intensity modulations. The Monge–Ampère code is by far the fastest in 2-D, without massively parallel processing, but fails for intensities with large voids, high contrast ratios and large deflections across the boundaries, and could not obtain the degree of convergence possible with the PIC code. As a result, the power diagram code was by far the slowest and most memory intensive, and failed for large peaks in the measured intensity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

pnnl/PVML_FaultSignatureDetection (33416-E)

This invention does PV fault signature extraction and detection based on unstructured field data, irradiance sensors, and inverter operational history logs obtained from Ecogy towards reducing OEM maintenance costs.

Veeramany, Arun [Pacific Northwest National Labora↗

INTEGRATE – Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project developed a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. Training data was obtained from improved turbulence and transition models for RANS and hybrid RANS/LES solvers with machine-learned physics-based data-augmented corrections and then using the resulting neural-network(s) augmented RANS model to run thousands of 2-D and 3-D CFD simulations.

17 WIND ENERGY↗