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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗
DOE OSTI2020

Radius-to-frequency Mapping and FRB Frequency Drifts

We build a model of radius-to-frequency mapping in magnetospheres of neutron stars and apply it to frequency drifts observed in fast radio bursts (FRBs). We assume that an emission patch propagates along the dipolar magnetic field lines, producing coherent emission with frequency, direction, and polarization defined by the local magnetic field. The observed temporal evolution of the frequency depends on the relativistic effects of time contraction and the curvature of the magnetic field lines. The model generically produces linear scaling of the drift rate, $\dot{\omega}$ ∝-${\omega}$, matching both numerically and parametrically the rates observed in FBRs; a more complicated behavior of $\dot{\omega}$ is also possible. Fast rotating magnetospheres produce higher drifts rates for similar viewing parameters than the slowly rotating ones. In the case of repeaters, the same source may show variable drift patterns depending on the observing phase. We expect rotational of polarization position angle through a burst, though by smaller amount than in radio pulsars. All of these findings compare favorably with properties of FBRs, strengthening their possible loci in the magnetospheres of neutron stars.

Magnetars↗
DOE OSTI2025

Passband Signal Detection at the Edge

Algorithms for radio frequency (RF) spectrum awareness need to be compatible with edge hardware to be practical for many applications. We developed a signal detection and classification model for the ZCU111 RF System-on-a-Chip (RFSoC) that operates on the fast Fourier transform of passband RF data. The system can detect and classify multiple signals of interest and display the predictions in real-time. The model consists of a modified ConvNeXt backbone and YOLOv3 head to operate on the Deep Learning Processing Unit on the RFSoC. We gathered datasets for training and testing by using a software defined radio to transmit example signals of Wi-Fi 802.11 b/g, Wi-Fi 802.11 n, FM Radio, LTE and LTE-M. By leveraging multiple inputs on the RFSoC frontend, the datasets span up to 4 GHz of bandwidth. The models showed high performance in classification accuracy, center frequency error, bandwidth error, and detection accuracy for both single and multi-signal datasets.

42 ENGINEERING↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Fast Seismic Anomalies Under Continents Explained by the Delaminated Lower Continental Crust—Implications From High Pressure‐Temperature Elasticity of Jadeite

Seismic tomography has shown that the shear wave velocities (Vs) under continents, especially under cratons, are extremely fast at 100–200 km depth, which is difficult to explain by low temperatures or high Mg#. Alternatively, delaminated eclogitic lower continental crust has been proposed to account for these fast seismic anomalies. However, the thermoelastic properties of jadeite which constitutes up to 60–80 mol% of clinopyroxene in the potentially delaminated lower continental crust are not well constrained. In this study, we measured the single-crystal elasticity of jadeite by Brillouin spectroscopy under simultaneous high pressure and temperature conditions for the first time. We found that the temperature dependence of Vs of jadeite is extremely small if not negligible. The seismic velocities of the potentially delaminated lower continental crusts were subsequently modeled and found to match the widely observed fast seismic anomalies under cratons between 100 and 200 km depth.

Geology↗
DOE OSTI2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32 x 32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Unexpected structural/motional mode of water intercalated into an α-crystalline zirconium phosphate deduced by 31 P and 2 H solid-state MAS NMR spectra

Here, in developing the approach to understanding dynamics of intercalates in layered materials, crystalline-layered zirconium phosphate Zr (HPO 4 ) 2 ·0.35D2O has been prepared and characterized by the 1 H, 31 P, and 2 H solid-state MAS NMR spectra, including 31 P and 2 H T 1 measurements. At temperatures >253 K, the intercalated water shows two spectrally-distinguished deuterons unprecedentedly with different DQCC's and 2 H T 1 times, one of which is hydrogen bonded. The collected data allowed to identify an unexpected bonding/dynamic mode of water molecules, which experience fast rotation around the hydrogen bond, formed with a zirconium-coordinated oxygen. The low-temperature 2 H MAS NMR experiments have demonstrated the presence of additional hydrogen bond P—(H)O˙˙˙ DO, population of which grows on cooling to 195 K corresponding to the doubly hydrogen-bonded immobile water molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Adaptively controlled fast production of defect-free beryllium ion crystals using pulsed laser ablation

Trapped atomic ions find wide applications ranging from precision measurement to quantum information science and quantum computing. Beryllium ions are widely used due to the light mass and convenient atomic structure of beryllium; however, conventional ion loading from thermal ovens exerts undesirable gas loads for a prolonged duration. Here, we demonstrate a method to rapidly produce pure linear chains of beryllium ions with pulsed laser ablation, serving as a starting point for large-scale quantum information processing. Our method is fast compared to thermal ovens, reduces the gas load to only 10 -12 Torr (10 -10 Pa) level, yields a short recovery time of a few seconds, and also eliminates the need for a deep ultraviolet laser for photoionization. We also study the loading dynamics, which show non-Poissonian statistics in the presence of sympathetic cooling. In addition, we apply feedback control to obtain defect-free ion chains with desirable lengths.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Time delay lens modelling challenge

ABSTRACT In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant H0. However, published state-of-the-art analyses require of order 1 yr of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge, we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated data sets. The results in Rungs 1 and 2 show that methods that use only the point source positions tend to have lower precision ($10\!-\!20{{\ \rm per\ cent}}$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic data sets can recover H0 within the target accuracy (|A| < 2 per cent) and precision (<6 per cent per system), even in the presence of a poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.

Ding, X.↗
DOE OSTI2022

How slowly can the early Universe expand?

When the expansion of the Universe is dominated by a perfect fluid with equation of state parameter w and a sound speed c s satisfying w = $c^{2}_{s}$ ≤ 1 , the Hubble parameter H and time t satisfy the bound Ht ≥ 1/3 . There has been recent interest in “ultraslow” expansion laws with Ht <1/3 (sometimes described as “fast expanding” models). Here, we examine various models that can produce ultraslow expansion: scalar fields with negative potentials, barotropic fluids, braneworld models, or a loitering phase in the early Universe. Scalar field models and barotropic models for ultraslow expansion are unstable to evolution toward w = 1 or w → ∞ in the former case and w → ∞ in the latter case. Braneworld models can yield ultraslow expansion but require an expansion law beyond the standard Friedman equation. Loitering early universe models can produce a quasistatic expansion phase in the early Universe but require an exotic negative-density component. These results suggest that appeals to an ultraslow expansion phase in the early Universe should be approached with some caution, although the loitering early universe may be worthy of further investigation. These results do not apply to ultraslow contracting models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Low duty cycle pulsed UV technique for spectroscopy of aluminum monochloride

We present what we believe to be a novel technique to minimize UV-induced damage in experiments that employ second-harmonic generation cavities. The principle of our approach is to reduce the duty cycle of the UV light as much as possible to prolong the lifetime of the used optics. The low duty cycle is achieved by ramping the cavity into resonance for a short time during the experimental cycle when the light is used and tuning it to an off-resonant state otherwise. The necessary fast ramp and length-stabilization control of the cavity is implemented with the FPGA-based STEMlab platform. We demonstrate the utility of this method by measuring the isotope shift of the electronic transition (X 1 Σ ← A 1 Π) in AlCl at 261.5 nm in a pulsed molecular beam experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Use of Modern Tunnel Boring Machines for Underground Pumped Storage (CRADA 464)

The National Renewable Energy Laboratory initiated a Prize with support from Argonne National Laboratory (ANL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL), and sponsored by the U.S. Department of Energy Water Power Technologies Office (DOE WPTO) to encourage ideas to reduce the time to commissioning for PSH projects. As a result, nine finalists have been chosen to develop their concepts in advance of the FAST Prize Pitch Contest to be held on October 7, 2019. The National Labs will provide technical and business advisement to the noted FAST Prize finalists in preparation for this Pitch Contest.

42 ENGINEERING↗
DOE OSTI2023

Shot 3 Post-Shot Report: Fault Analysis of MK-X Data [Slides]

This presentation constitutes a post-shot report for the MK-X performance on Shot 3 (13 July 2022). It focuses primarily on the analysis of electrical faults which have been a persistent issue in MK-X performance and were a significant focus of the test. The MK-X is a helical flux compression generator (HFCG) that has been manufactured in a novel and very cost-effective way. Shot 3 was the fourth test in a series which began with a low initial-current-level HFCG test coupled to a dummy load (Shot 0) and then a high stress test (Shot 1) coupled to a primitive pulse forming network (PFN). Shot 0 performed close to expectation but Shot 1 had early time losses that could not be explained. As a result, Shots 2 and 3 had dual goals. Each shot looked at MK-X performance relative to the early time losses, and since the amount of current generated on the first two tests was a useful amount, we coupled to a fast R43S Ranchero flux compression generator for Shot 2 to ascertain Ranchero’s performance with higher-than-ever initial current and another PFN load. Then Shot 3 implemented a specific change to the MK-X and coupled to only a low inductance PFN load. The report shows that Shots 1-3 all have qualitatively similar losses and the change made for Shot 3 to explore losses led to even further losses. However, the PFN on shot 3 was low inductance and in spite of the losses, 32 MA was generated. This report discusses the losses seen specifically on Shot 3 and compares the electrical and camera data along with a careful comparison to 3 D MHD modeling.

42 ENGINEERING↗
DOE OSTI2023

A Schottky Tune Meter for the Fermilab Mu2E Delivery Ring

The Mu2E experiment will measure the ratio of the rate of the neutrinoless, coherent conversion of muons into electrons as a measure of Charged Lepton Flavor Violation. As part of the Mu2E experiment, a proton storage ring, called the Delivery Ring, will utilize resonant extraction to slow-spill protons to the experiment. To regulate and optimize the Delivery Ring resonant extraction process, a fast tune measurement scheme will be required. This Mu2E tune meter will measure the average tune and the tune spectrum, in multiple time slices, through the entire resonant extraction cycle of nominally 43 msec. The Mu2E tune meter system utilizes vertical and horizontal 21.4 MHz Schottky detector resonant pickups, taken from the decommissioned Tevatron, high-gain amplifiers and digital down-conversion FPGA logic for its signal processing. This paper will present the design of this Schottky tune meter as well as tune measurements from the Mu2E delivery ring.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Picosecond measurements of plastic scintillator pulse shapes from gamma-ray interactions

An understanding of the pulse shape of organic scintillators can provide insight into scintillation mechanisms and inform the selection of the optimal detector material for a given application. Although the timing properties of organic scintillators have been extensively studied, significant discrepancies persist in reported rise and decay times. New plastic scintillating media have also been developed in recent years for which no literature data exist. The goal of this work is to provide high-precision measurements of the pulse shape of a suite of fast plastic organic scintillators from Eljen Technology—EJ-200, EJ-204, EJ-208, EJ-230, EJ-232, and EJ-232Q (with 0.5% benzophenone)—under excitation from $γ$-ray sources. The contributors to the system temporal resolution were quantified, and the dominant source of uncertainty was identified as the determination of the start time of a scintillation event. A pulse shape model was applied to the reconstructed temporal distributions, and rise and decay times were extracted and compared with manufacturer specifications. This work outlines a measurement approach to obtain the pulse shape of organic scintillators in response to $γ$-rays with temporal resolution on the order of tens of picoseconds, yielding data required for modeling plastic scintillator based detection systems for a range of applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗