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NASA NTRS2004

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM for digital-to-optical correlation-filter data conversion, and a charge-coupled device (CCD) for detection of correlation peaks. In operation, the input scene grabbed by a video sensor is streamed into the input SLM. Precomputed correlation-filter data files representative of known targets are then downloaded and sequenced into the filter SLM at a rate of 1,000 Hz. When there occurs a match between the input target data and one of the known-target data files, the CCD detects a correlation peak at the location of the target. Distortion- invariant correlation filters from a bank of such filters are then sequenced through the optical correlator for each input frame. The net result is the rapid preliminary recognition of one or a few targets.

Moynihan, Philip↗

NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 0.5. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Fluorescence↗

NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

remote sensing↗

DOE OSTI2024

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

NASA NTRS2010

Optimized FPGA Implementation of Multi-Rate FIR Filters Through Thread Decomposition

Multirate (decimation/interpolation) filters are among the essential signal processing components in spaceborne instruments where Finite Impulse Response (FIR) filters are often used to minimize nonlinear group delay and finite-precision effects. Cascaded (multi-stage) designs of Multi-Rate FIR (MRFIR) filters are further used for large rate change ratio, in order to lower the required throughput while simultaneously achieving comparable or better performance than single-stage designs. Traditional representation and implementation of MRFIR employ polyphase decomposition of the original filter structure, whose main purpose is to compute only the needed output at the lowest possible sampling rate. In this paper, an alternative representation and implementation technique, called TD-MRFIR (Thread Decomposition MRFIR), is presented. The basic idea is to decompose MRFIR into output computational threads, in contrast to a structural decomposition of the original filter as done in the polyphase decomposition. Each thread represents an instance of the finite convolution required to produce a single output of the MRFIR. The filter is thus viewed as a finite collection of concurrent threads. The technical details of TD-MRFIR will be explained, first showing its applicability to the implementation of downsampling, upsampling, and resampling FIR filters, and then describing a general strategy to optimally allocate the number of filter taps. A particular FPGA design of multi-stage TD-MRFIR for the L-band radar of NASA's SMAP (Soil Moisture Active Passive) instrument is demonstrated; and its implementation results in several targeted FPGA devices are summarized in terms of the functional (bit width, fixed-point error) and performance (time closure, resource usage, and power estimation) parameters.

DSP↗

DOE OSTI2022

Molecular-Level Control over Ionic Conduction and Ionic Current Direction by Designing Macrocycle-Based Ionomers

Poor ionic conductivity of the catalyst-binding, submicrometer- thick ionomer layers in energy conversion and storage devices is a huge challenge. However, ionomers are rarely designed keeping in mind the specific issues associated with nanoconfinement. Here, we designed nature-inspired ionomers (calix-2) having hollow, macrocyclic, calix[4]arene-based repeat units with precise, sub-nanometer diameter. In ≤100 nm-thick films, the in-plane proton conductivity of calix-2 was up to 8 times higher than the current benchmark ionomer Nafion at 85% relative humidity (RH), while it was 1-2 orders of magnitude higher than Nafion at 20-25% RH. Confocal laser scanning microscopy and other synthetic techniques allowed us to demonstrate the role of macrocyclic cavities in boosting the proton conductivity. The systematic self-assembly of calix-2 chains into ellipsoids in thin films was evidenced from atomic force microscopy and grazing incidence small-angle X-ray scattering measurements. Moreover, the likelihood of alignment and stacking of macrocyclic units, the presence of one-dimensional water wires across this macrocycle stacks, and thus the formation of long-range proton conduction pathways were suggested by atomistic simulations. We not only did see an unprecedented improvement in thin-film proton conductivity but also saw an improvement in proton conductivity of bulk membranes when calix-2 was added to the Nafion matrices. Nafion-calix-2 composite membranes also took advantage of the asymmetric charge distribution across calix[4]arene repeat units collectively and exhibited voltage-gating behavior. The inclusion of molecular macrocyclic cavities into the ionomer chemical structure can thus emerge as a promising design concept for highly efficient ion-conducting and ion-permselective materials for sustainable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Energy Efficient Thermoplastic Composite Manufacturing

The objective of the project was to establish an effective and affordable method to lay-up and consolidate/join large thermoplastic composite aerospace structure with cycle times measured in minutes rather than hours. Composite airplane designs have proven efficient and effective however future potential product production rates are challenging what the current systems can efficiently produce due to material lay-down constraints and extended thermal cycle times. The ability to lay-up then rapidly heat, consolidate, and cool large complex composite structures plus very accurately tool them (i.e. matching CTE of composite materials) along with very precise thermal control is a difficult challenge. Current systems such as autoclave processing of thermoset materials require long cycle times due to method of heating and the large associated thermal masses. These extended cycle times inhibit the ability to meet higher rate production scenarios due to the need for multiple sets of equipment and tools. Thermoplastic composite materials were used to facilitate more rapid cycle times via the elimination of a need for a cure dwell at temperature. Also, utilized induction heating along with smart susceptors to enable the quick cycle times needed while providing precise intrinsic thermal control. The intrinsic control of the induction heating process via the smart susceptors along with the use of laser assisted fiber placement were the key innovations areas developed. The ability to rapidly heat and then precisely control the temperature of the consolidation component was paramount to the success of this project. It is this unique processing attribute coupled with the thermoplastic material characteristics along with rapid lay-up methods that are novel and advantageous. While many requirements and influencing factors decide the materials and processes utilized for future airplane construction, the forecast of accelerated production rates and the recent performance successes of composites in airplane construction provide an opportunity for this processing technology to have significant influence. During the course of this project a number of key accomplishments were completed. They are as follows: The needed laser assisted fiber placement capabilities have been developed and validated on a component of meaningful scale and complexity. Subsequently, a thermoplastic preform of the part scale-up part design was laser assisted fiber placed and made availalbe for consolidation. An induction consolidation system was sized, designed, and fabricated resulting in the full capability to consolidate the scale-up component. The tool for induction consolidating of the scale-up component was designed and fabricated. An aluminum pressure bladder was welded and formed for use as the pressurization membrane to perform the needed application of pressure on the part at temperature to achieve consolidation. The induction consolidation system consisting of the restraint, induction power supply, induction tool with integrated induction coils and smart susceptor liners, along with the aluminum bladder were successfully used to consolidate a large thermoplastic skin. The capability of accomplishing rapid heat-up rates and cool down rates for consolidation of large thermoplastic skins with precise thermal control and even pressure application at the consolidation temperature was validated. The general conclusion is that the use of induction consolidation with smart susceptors is an effective method to rapidly and efficiently consolidate large thermoplastic composite components and enable affordable high rate manufacturing of composites. More specific conclusions generated by this project are as follows: A restraint type induction consolidation system provides an affordable option over the standard press when using the induction consolidation processing method. Aluminum bladders can be formed to the complex shapes needed and supply uniform pressure for consolidation and co-consolidation of thermoplastic composite materials. Straightforward modifications can be made to existing fiber placement robotic systems to enable their use for thermoplastic lay-up applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1994

Precise mean sea level measurements using the Global Positioning System

This paper describes the results of a sea level measurement test conducted off La Jolla, California, in November of 1991. The purpose of this test was to determine accurate sea level measurements using a Global Positioning System (GPS) equipped buoy. These measurements were intended to be used as the sea level component for calibration of the ERS 1 satellite altimeter. Measurements were collected on November 25 and 28 when the ERS 1 satellite overflew the calibration area. Two different types of buoys were used. A waverider design was used on November 25 and a spar design on November 28. This provided the opportunity to examine how dynamic effects of the measurement platform might affect the sea level accuracy. The two buoys were deployed at locations approximately 1.2 km apart and about 15 km west of a reference GPS receiver located on the rooftop of the Institute of Geophysics and Planetary Physics at the Scripps Institute of Oceanography. GPS solutions were computed for 45 minutes on each day and used to produce two sea level time series. An estimate of the mean sea level at both locations was computed by subtracting tide gage data collected at the Scripps Pier from the GPS-determined sea level measurements and then filtering out the high-frequency components due to waves and buoy dynamics. In both cases the GPS estimate differed from Rapp's mean altimetric surface by 0.06 m. Thus, the gradient in the GPS measurements matched the gradient in Rapp's surface. These results suggest that accurate sea level can be determined using GPS on widely differing platforms as long as care is taken to determine the height of the GPS antenna phase center above water level. Application areas include measurement of absolute sea level, of temporal variations in sea level, and of sea level gradients (dominantly the geoid). Specific applications would include ocean altimeter calibration, monitoring of sea level in remote regions, and regional experiments requiring spatial and temporal resolution higher than that available from altimeter data.

Kelecy, Thomas M.↗

NASA NTRS2005

Growth from Solutions: Kink dynamics, Stoichiometry, Face Kinetics and stability in turbulent flow

1. Kink dynamics. The first segment of a polygomized dislocation spiral step measured by AFM demonstrates up to 60% scattering in the critical length l*- the length when the segment starts to propagate. On orthorhombic lysozyme, this length is shorter than that the observed interkink distance. Step energy from the critical segment length based on the Gibbs-Thomson law (GTL), l* = 20(omega)alpha/(Delta)mu is several times larger than the energy from 2D nucleation rate. Here o is tine building block specific voiume, a is the step riser specific free energy, Delta(mu) is the crystallization driving force. These new data support our earlier assumption that the classical Frenkel, Burton -Cabrera-Frank concept of the abundant kink supply by fluctuations is not applicable for strongly polygonized steps. Step rate measurements on brushite confirms that statement. This is the1D nucleation of kinks that control step propagation. The GTL is valid only if l* <Dk/vk, the diffusion path of a kink that has diffusivity Dk and average growth velocity vk. This is equivalent to supersaturations sigma less than approx. alpha/2l*, where alpha is the building block size. For lysozyme, sigma much less than (1%). Conventionally used interstep distance generated by screw dislocation, 19(omega)alpha/Delta(mu) should be replaced by the very different real one, approx.4l*. 2. Stoichiometry. Kink, and thus step and face rates of a non-Kossel complex molecular monocomponent or any binary, AB, lattice was found theoretically to be proportional to 1/(zeta(sup 1/2) + zeta(sup - 1/2)), where zeta = [B]/[A] is the stoichiometry ratio in solution. The velocities reach maxima at zeta = 1. AFM studies of step rates on CaOxalate monohydrate (kidney stones) from aqueous solution was found to obey the law mentioned above. Generalization for more complex lattice will be discussed. 3. Turbulence. In agreement with theory, high precision in-situ laser interferometry of the (101) KDP crystal face shows step bunching if solution flows parallel to the step flow. The bunch height increases with the distance the bunch travels, i.e. with the face size. However, when the flow rate, u, increases, at u greater than approx. 1 m / s , the average step bunch height decreases as 1/u. The pheonomenon is attributed to the turbulent rather than laminar viscous boundary layer where diffusivity Dt = 0.5u(sub tau),y, i.e. increases linearly with the distance y from the solid face. Friction velocity, u(sub tau) approx. u(sup 7/8). Dramatically larger rate of the mass/heat transport within the turbulent, as compared to the laminar, viscous layer will be discussed.

Chernov, A. A.↗

NASA NTRS2011

Monolithic Flexure Pre-Stressed Ultrasonic Horns

High-power ultrasonic actuators are generally assembled with a horn, backing, stress bolt, piezoelectric rings, and electrodes. The manufacturing process is complex, expensive, difficult, and time-consuming. The internal stress bolt needs to be insulated and presents a potential internal discharge point, which can decrease actuator life. Also, the introduction of a center hole for the bolt causes many failures, reducing the throughput of the manufactured actuators. A new design has been developed for producing ultrasonic horn actuators. This design consists of using flexures rather than stress bolts, allowing one to apply pre-load to the piezoelectric material. It also allows one to manufacture them from a single material/plate, rapid prototype them, or make an array in a plate or 3D structure. The actuator is easily assembled, and application of pre-stress greater than 25 MPa was demonstrated. The horn consists of external flexures that eliminate the need for the conventional stress bolt internal to the piezoelectric, and reduces the related complexity. The stress bolts are required in existing horns to provide prestress on piezoelectric stacks when driven at high power levels. In addition, the manufacturing process benefits from the amenability to produce horn structures with internal cavities. The removal of the pre-stress bolt removes a potential internal electric discharge point in the actuator. In addition, it significantly reduces the chances of mechanical failure in the piezoelectric stacks that result from the hole surface in conventional piezoelectric actuators. The novel features of this disclosure are: 1. A design that can be manufactured from a single piece of metal using EDM, precision machining, or rapid prototyping. 2. Increased electromechanical coupling of the horn actuator. 3. Higher energy density. 4. A monolithic structure of a horn that consists of an external flexure or flexures that can be used to pre-stress a solid piezoelectric structure rather than a bolt, which requires a through hole in the piezoelectric material. 5. A flexure system with low stiffness that accommodates mechanical creep with minor reduction in pre-stress.

Sherrit, Stewart↗

NASA NTRSDate not supplied

Advancing Metasurfaces Towards New Frontiers: Nonvolatile Reconfigurable Optics

The applications of adaptive optics extend across multiple sectors, encompassing areas such as LiDAR, biological and chemical sensing, and free-space communications. In this study, we report on the design, fabrication, testing, and modeling of electrically reconfigurable metasurfaces using a low-loss high contrast phase change material, Ge2Sb2Se4Te integrated with an IR-transparent silicon microheater. Through this work, we introduce a reliable architecture for switching PCM-based metasurfaces within an integrated circuit configuration which is compatible with standard foundry fabrication processes. We demonstrate the capability of controlling the transmission of electromagnetic waves through the precise stimulation of PCM-based pixels, each spanning a few hundred microns, over numerous cycles. By leveraging PCM-based pixels, we unlock the potential to create metasurfaces encompassing a diverse range of functionalities such as dielectric filters, metalens, or beam steering devices, which is governed by the design of the meta-atoms. Further, we perform an in-depth investigation into the failure mechanism utilizing techniques such as Fourier transform IR spectroscopy (FTIR), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and thermal modeling. According to our results, due to a sharp temperature rise at the PCM/heater interface, we observe severe delamination of the PCM from the heater. More uniform PCM deposition, better adhesion at the PCM/heater interface, and a more uniform temperature distribution in the device could potentially mitigate the failure and lead to a longer life-time. By addressing these challenges, we aim to unlock the full potential of PCM-based devices and advance the field of adaptive optics.

Phase change material↗

DOE OSTI2021

Multiphonon diffuse scattering in solids from first principles: Application to layered crystals and two-dimensional materials

Time-resolved diffuse scattering experiments have gained increasing attention due to their potential to reveal nonequilibrium dynamics of crystal lattice vibrations with full momentum resolution. Although progress has been made in interpreting experimental data on the basis of one-phonon scattering, understanding the role of individual phonons can be sometimes hindered by multiphonon excitations. In Ref. [M. Zacharias, H. Seiler, F. Caruso, D. Zahn, F. Giustino, P. C. Kelires, and R. Ernstorfer, Phys. Rev. Lett. 127, 207401 (2021)], we have introduced a rigorous approach for the calculation of the all-phonon inelastic scattering intensity of solids from first-principles. In the present work, we describe our implementation in detail and show that multiphonon interactions are captured efficiently by exploiting translational and time-reversal symmetries of the crystal. We demonstrate its predictive power by calculating the scattering patterns of monolayer molybdenum disulfide (MoS 2 ), bulk MoS 2 , and black phosphorus (bP), and we obtain excellent agreement with our measurements of thermal electron diffuse scattering. Remarkably, our results show that multiphonon excitations dominate in bP across multiple Brillouin zones, while in MoS 2 they play a less pronounced role. We expand our analysis for each system and examine the effect of individual atomic and interatomic vibrational motion on the diffuse scattering signals. We further demonstrate the high-throughput capability of our approach by reporting all-phonon scattering maps of two-dimensional MoSe 2 , WSe 2 , WS 2 , graphene, and CdI 2 , rationalizing in each case the effect of multiphonon processes. As a side point, we show that the special displacement method reproduces the thermally distorted configuration that generates precisely the all-phonon diffuse pattern. In conclusion, the present methodology opens the way for systematic calculations of the scattering intensity in crystals and the accurate interpretation of static and time-resolved inelastic scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

ACHILLES-GENIE Interface for Neutrino Simulations, ADRIANO2 Tile Prototype for High-Granularity Dual-Readout Calorimetry

ICARUS (Imaging Cosmic And Rare Underground Signals) is a liquid argon time projection chamber (LArTPC) detector that pursues the sterile neutrino, which relies on accurate simulations of neutrino-argon interactions. REDTOP (Rare Eta Decays To Observe new Physics) is a proposed low-energy, high-intensity meson factory designed to explore rare $\eta$/$\eta'$ meson decays and probe physics beyond the Standard Model. As a next-generation experiment, this requires both accurate simulations and innovative detector technologies. This project contributes to both ICARUS, from a simulation perspective, and REDTOP, from both a simulation and detection perspective, through the event generation of lepton-nucleon interactions and the physical enhancement of the calorimeter technology within the REDTOP detector. We developed an interface between ACHILLES (A CHIcago Land Lepton Event Simulator), a theory-driven lepton-level event generator, and GENIE, a robust event generator framework used for neutrino physics. By incorporating the precise theoretical cross-section calculations of ACHILLES into the experimental realism of GENIE, the interface allows for improved accuracy of neutrino-nucleon simulations, which can be adapted for the proton beam specifications of the REDTOP meson factory as well as for the ICARUS experiment. In parallel, we developed an improved prototype for the ADRIANO2 (A Dual Readout Integrally Active Non-segmented Option) dual-readout calorimeter tiles for the REDTOP detector. To improve the efficiency of the lead-glass tiles trapping Cherenkov light for energy reconstruction and particle identification, we optimized the application of a highly reflective coating. Through viscosity and thickness control, masking, and a custom spray technique, we refined the coating process to reduce surface defects and improve light yield. Together, these efforts strengthen the ICARUS neutrino program and REDTOP's capability of detecting rare decay events.

Visser, Erin [Michigan State U.]↗

DOE OSTI2025

Enhancing ICARUS and REDTOP Software and Hardware: Event Generator Interface Development and Calorimeter Tile Prototype

Visser, Erin [Michigan State U.] (ORCID:0009000184↗

DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Integration of Total-Sky Imager Data with a Physics-Based Smart Persistence Model for Intra-Hour Forecasting of Solar Radiation

Short-term solar forecasting models based solely on global horizontal irradiance (GHI) measurements are often unable to discriminate the forecasting of the factors affecting GHI from those that can be precisely computed by atmospheric models. Our previous study introduced a Physics-based Smart Persistence model for Intra-hour forecasting of solar radiation (PSPI) that decomposed the forecasting of GHI into the computation of extraterrestrial solar radiation and solar zenith angle and the forecasting of cloud albedo and cloud fraction. The extraterrestrial solar radiation and solar zenith angle were accurately computed by the Solar Position Algorithm (SPA) developed at the National Renewable Energy Laboratory (NREL). A cloud retrieval technique was used to estimate cloud albedo and cloud fraction from surface-based observations of GHI. With the assumption of persistent cloud structures, the cloud albedo and cloud fraction were predicted for future time steps using a two-stream approximation and a 5-minute exponential weighted moving average, respectively. The model evaluation indicated the estimation and forecast of cloud fraction mostly contributed to the uncertainty of the PSPI though it overcame the persistence and smart persistence models in all forecast time horizons between 5 and 60 minutes. This study aims to enhance the PSPI by ingesting surface-based observations of cloud fraction from a total sky imager (TSI). The estimation and forecast of cloud albedo is correspondingly improved by utilizing the cloud fraction observations and thus leads to more accurate GHI forecast. Various time-series analysis methods are also investigated on the forecasting of cloud fraction and cloud albedo for further improving the GHI forecast. These improvements are valuable for many applications, such as forecasting energy use for buildings, grid operations, and ultimately bringing down the cost of solar energy.

14 SOLAR ENERGY↗

DOE OSTI2021

On the Feynman-alpha method for reflected fissile assemblies

The Feynman-alpha method is a neutron noise technique that is used to estimate the prompt neutron period of fissile assemblies. The method and quantity are of widespread interest including in applications such as nuclear criticality safety, safeguards and nonproliferation, and stockpile stewardship; the prompt neutron period may also be used to infer the k eff multiplication factor. The Feynman-alpha method is predicated on time-correlated neutron detections that deviate from a Poisson random variable due to multiplication. Traditionally, such measurements are diagnosed with one-region point kinetics, but two-region models are required when the fissile assembly is reflected. This paper presents a derivation of the two-region point kinetics Feynman-alpha equations based on a double integration of the Rossi-alpha equations, develops novel propagation of measurement uncertainty, and validates the theory. Validation is achieved with organic scintillator measurements of weapons-grade plutonium reflected by various amounts of copper to achieve k eff values of 0.83–0.94 and prompt periods of 5–75 ns. The results demonstrate that Feynman-alpha measurements should use the two-region model instead of the one-region model. The simplified one-region model deviates from the validated two-region models by as much as 10% in the estimate of the prompt neutron period, and the two-region model reduces to the one-region model for small amounts of reflector. The Feynman-alpha estimates of the prompt neutron period are compared to those of the Rossi-alpha approach. The comparative results demonstrate that the Feynman-alpha method is more precise than the Rossi-alpha method and more accurate for k eff < 0.92, whereas the Rossi-alpha method is generally more accurate for higher multiplications. Here, the uncertainty propagation developed in this work should be used for all Feynman-alpha measurements and will therein improve fitting accuracy and appropriate precision estimates.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗