SEARCH · Search NASA

Results for “high frequency data”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗

DOE OSTI2024

Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet

cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

SpinQuest Polarized Target System

The SpinQuest experiment at Fermilab uses a solid-state polarized ammonia target held at a magnetic field of 5 T, immersed in liquid helium-4, which is held at approximately 1K by the evaporation refrigerator. The refrigerator provides the required cooling power during the dynamic nuclear polarization (DNP) process and the high intensity interaction with the 120 GeV proton beam from the Fermilab main injector. The refrigerator was designed in compliance with the American Society of Mechanical Engineers (ASME) to operate safely at Fermilab. The high pumping capacity ($17,000 \:m^3/h$) roots stack provides the required pumping speed during DNP production data taking and a custom-made radiation hard flow control valve regulates the refrigerator temperature during the thermal equilibrium calibration measurements. The frequency of the microwave generator, an Extended Interaction Oscillator (EIO), is automated to keep the maximum polarization while the (Nuclear Magnetic Resonance) NMR system continuously measures the polarization of the target material. In this talk, an overview of the SpinQuest polarized target system will be presented as well as a brief report of recent commissioning activities and target performance during the early production runs in 2024.

Bandara, Vibodha [Colombo U.]↗

DOE OSTI2025

Electro-optic sampling of classical and quantum light

Full characterization of electric-field waveforms in amplitude and phase is achieved across the terahertz to visible spectral range through interaction with an optical pulse shorter than a half-cycle period via the Pockels (linear electro-optic) effect. This technique of electro-optic sampling has become an indispensable tool in various areas, including ultrafast pump-probe, time-domain and frequency-comb spectroscopies, quantum optics, high-harmonic generation, and attosecond science, and holds great promise for further advances. Not only does it enable spectroscopic measurements with record dynamic range and temporal resolution, along with massively parallel real-time spectral data acquisition, but its remarkable sensitivity also allows the detection of vacuum fluctuations, i.e., “zero-point motion” of electric fields, profoundly impacting our understanding of the fundamental laws of nature.

Benea-Chelmus, Ileana-Cristina (ORCID:000000024814↗

DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗

DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗

DOE OSTI2024

Divalent Titanium via Reductive N−C Coupling of a Ti IV Nitrido with π ‐Acids

The nitrido-ate complex [(PN) 2 Ti(N){μ 2 -K(OEt 2 )}] 2 (1) (PN − =(N-(2-P i Pr 2 -4-methylphenyl)-2,4,6-Me 3 C 6 H 2 ) reductively couples CO and isocyanides in the presence of DME or cryptand (Kryptofix222), to form rare, five-coordinate Ti II complexes having a linear cumulene motif, [K(L)][(PN) 2 Ti(NCE)] (E=O, L=Kryptofix222, (2); E=NAd, L=3 DME, (3); E=N t Bu, L=3 DME, (4); E=NAd, L=Kryptofix222, (5)). Oxidation of 2–5 with [Fc][OTf] afforded an isostructural Ti III center containing a neutral cumulene, [(PN) 2 Ti(NCE)] (E=O, (6); E=NAd (7), N t Bu (8)) and characterization by CW X-band EPR spectroscopy, revealed unpaired electron to be metal centric. Moreover, 1e − reduction of 6 and 7 in the presence of Kryptofix222cleanly reformed corresponding discrete Ti II complexes 2 and 5, which were further characterized by solution magnetization measurements and high-frequency and -field EPR (HFEPR) spectroscopy. Furthermore, oxidation of 7 with [Fc*][B(C 6 F 5 ) 4 ] resulted in a ligand disproportionated Ti IV complex having transoid carbodiimides, [(PN) 2 Ti(NCNAd) 2 ] (9). Comparison of spectroscopic, structural, and computational data for the divalent, trivalent, and tetravalent systems, including their 15 N enriched isotopomers demonstrate these cumulenes to decrease in order of backbonding as Ti II →Ti III →Ti IV and increasing order of π-donation as Ti II →Ti III →Ti IV , thus displaying more covalency in Ti III species. Lastly, we show a synthetic cycle whereby complex 1 can deliver an N-atom to CO and CNAd.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Low Frequency Vibrational Modes of Two-Dimensional Lead-Free Metal Halide Double Perovskites

2D layered double perovskites of (S-MPA) 4 AgBiI 8 (MPA-AgBiI 8 ) and (S-MPA) 4 CuBiI 8 (MPA-CuBiI 8 ) (S-MPA, S-β-methylphenethylammonium) were synthesized with a hydrothermal method. The crystal structure of MPA-AgBiI 8 was determined using single-crystal X-ray diffraction (scXRD). Powder XRD (pXRD) data suggest that the crystal structure of MPA-CuBiI 8 is more complex than that of MPA-AgBiI 8 . UV-Vis electronic absorption spectra of these perovskites reveal a bandgap of 2.03 eV for both. Short exciton lifetime from time-resolved photoluminescence (TRPL) results and low PL intensity of the Cu-based perovskite suggest a high density of trap states within the bandgap. Low frequency Raman spectra of both materials show distinct peaks and a slightly higher frequency for the Cu-based perovskite than the Ag-based perovskite. Density functional theory (DFT) calculations were conducted to simulate the low frequency Raman spectra and help explain the different phonon modes, which are collective vibrations of metal halide bond bending and stretching within the Ag- and Cu-centered octahedra coupled with MPA libration and twisting within the inorganic layer. The DFT theory also quantified octahedral distortions in the two perovskites. Furthermore, this combined experimental and computational study provides new insights into the low frequency vibrations of 2D perovskites.

Halogens↗

DOE OSTI2024

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases, distribution system state estimation (DSSE) and fault identification are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1 feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system↗

DOE OSTI2024

High-Temperature Water Adsorption Isotherms and Ambient Temperature Water Diffusion Rates on Water Harvesting Metal–Organic Frameworks

Water adsorption isotherms from 25 to 125 °C were measured for three metal−organic frameworks (MOFs), MOF-303, MOF-LA2-1, and MIL-100(Fe), which are frequently studied for water harvesting applications. The results show how the step in the water adsorption isotherm varies as a function of temperature and detail the combination of pressure and temperature necessary to remove adsorbed water. Furthermore, isobaric−isothermal Gibbs ensemble Monte Carlo simulations performed for MOF-303 shed light on the change in occupation numbers of the different known water adsorption sites with increasing temperature. Additionally, the diffusion rates of water through these materials were measured using concentration swing frequency response, and micropore diffusion was identified as the controlling mechanism. The Darken relation was used to show the dependence of the diffusion rate on the concentration and the impact of the adsorption isotherm slope. The adsorption of water on MOF-LA2-1 is faster than that on MIL-100(Fe). These data show that MOF-LA2-1 with its high-water adsorption capacity, quick adsorption rate, and favorable desorption energetics is a leading candidate for atmospheric water harvesting.

Adsorption↗

DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗

DOE OSTI2025

Long-term calibration and validation of stability of the Auger Engineering Radio Array using the diffuse Galactic radio emission

The Auger Engineering Radio Array (AERA) measures radio emission from high-energy extensive air showers. Consisting of 153 autonomous radio-detector stations spread over 17 km^2, it detects radio waves in the frequency range of 30 to 80 MHz. Accurate characterization of the detector response is crucial for proper interpretation of the collected data. Previously, this was achieved through laboratory measurements of the analog chain and simulations and measurements of the antenna's directional response. In this paper, we perform an absolute calibration using the continuously monitored sidereal modulation of the diffuse Galactic radio emission. Calibration is done by comparing the average frequency spectra recorded by the stations with predictions from seven different models of the full radio sky, accounting for the system response, which includes the antenna, filters, and amplifiers. The analysis of the calibration constants over a period of seven years shows no relevant and no significant ageing effect in the AERA antennas. This result confirms the long-term stability of the detector stations and demonstrates the possibility for a radio detector to effectively monitor ageing effects of other detectors operating over extended periods.

Antennas↗

DOE OSTI2025

Identifying Urban Pluvial Frequency Flooding Hotspots Using the Topographic Control Index and Remote Sensing Radar Images for Early Warning Systems

Identifying areas that frequently experience post-rainfall ponding is essential for effective flood mitigation and planning. This study integrates Sentinel-1 radar imagery and the Topographic Control Index (TCI) to identify 378 flood-prone urban depressions in Beaumont, Texas. Out of 159 major rainfall events, only six had Sentinel-1 radar imagery acquired within six hours of peak rainfall, and these were used to generate the flood frequency map; the ground-based flood sensor data were used to verify that these selected events corresponded to actual peak rainfall and to validate radar-detected water pixels. Validation results showed 100% precision, 70.87% recall, an F1-score of 82.95%, and 71.32% overall accuracy. Approximately 84% of medium-to-high TCI depressions overlapped with Beaumont’s two-year inundation map, confirming a strong relationship between TCI and observed flooding. A total of 124 depressions retained significant water, and after excluding 25 engineered detention ponds, 99 natural depressions remained flood vulnerable. Among these, 74 depressions with medium or high TCI were identified as the highest-priority nuisance flooding hotspots. The results demonstrate that combining TCI with radar imagery provides a reliable and cost-effective approach for identifying areas prone to frequent urban ponding. This framework supports practical decision-making for drainage improvements, hotspot identification, and early-warning system development in urban flood-prone regions.

Sentinel-1 radar imagery↗

DOE OSTI2026

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗

DOE OSTI2024

High-Resolution Frequency-Domain Spectroscopic and Modeling Studies of Photosystem I (PSI), PSI Mutants and PSI Supercomplexes

Photosystem I (PSI) is one of the two main pigment–protein complexes where the primary steps of oxygenic photosynthesis take place. This review describes low-temperature frequency-domain experiments (absorption, emission, circular dichroism, resonant and non-resonant hole-burned spectra) and modeling efforts reported for PSI in recent years. In particular, we focus on the spectral hole-burning studies, which are not as common in photosynthesis research as the time-domain spectroscopies. Experimental and modeling data obtained for trimeric cyanobacterial Photosystem I (PSI 3 ), PSI 3 mutants, and PSI 3 –IsiA 18 supercomplexes are analyzed to provide a more comprehensive understanding of their excitonic structure and excitation energy transfer (EET) processes. Detailed information on the excitonic structure of photosynthetic complexes is essential to determine the structure–function relationship. We will focus on the so-called “red antenna states” of cyanobacterial PSI, as these states play an important role in photochemical processes and EET pathways. The high-resolution data and modeling studies presented here provide additional information on the energetics of the lowest energy states and their chlorophyll (Chl) compositions, as well as the EET pathways and how they are altered by mutations. We present evidence that the low-energy traps observed in PSI are excitonically coupled states with significant charge-transfer (CT) character. The analysis presented for various optical spectra of PSI 3 and PSI 3 -IsiA 18 supercomplexes allowed us to make inferences about EET from the IsiA 18 ring to the PSI 3 core and demonstrate that the number of entry points varies between sample preparations studied by different groups. In our most recent samples, there most likely are three entry points for EET from the IsiA 18 ring per the PSI core monomer, with two of these entry points likely being located next to each other. Therefore, there are nine entry points from the IsiA 18 ring to the PSI 3 trimer. We anticipate that the data discussed below will stimulate further research in this area, providing even more insight into the structure-based models of these important cyanobacterial photosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Variational data augmentation for a learning-based granular predictive model of power outages

As the trend in climate change continues, extreme weather events are expected to occur with increasing frequency and severity and pose a significant threat to the electric power infrastructure. Regardless of the efforts a utility puts towards hardening the grid, storm-induced damage to the utility assets such as cables and distributed energy resources (DERs) that are particularly vulnerable to such events is unavoidable. Access to a highly granular, in space and time, outage forecasting tool with long lead times (i.e., days ahead) will enhance the efficiency of service restoration efforts. Here, in this study, we propose to develop and implement a multi-model framework as an operational tool based on a granular and multi-day outage forecasting model using operational numerical weather prediction model forecasts and detailed component outage information. An innovative two-layered recurrent neural network, i.e., a long-short-term-memory (LSTM)-based variational autoencoder (VAE) framework and a sliding window are used to address the uneven distribution of different types of weather events and make better use of the time-series data. Case studies are performed to demonstrate the performance of the new framework.

54 ENVIRONMENTAL SCIENCES↗