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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗
DOE OSTI2024

Mechanochromic Palettes of Cholesteric Liquid Crystal Elastomers for Visual Signaling

Mechanochromic photonic materials present promising prospects for enhancing diverse facets of human life. Cholesteric liquid crystal elastomers (CLCEs) present immediate mechanochromic properties, allowing their utility in various fields, including camouflages, textiles, and anticounterfeiting. Nonetheless, it is essential to provide differentiated color information corresponding to diverse types and degrees of deformation for practical use in real life. Herein, we investigate the mechanochromic responses of CLCEs using their optical rotation under compression and uniaxial stretching. The CLCEs exhibit the same reflection colors indistinguishable for compression and uniaxial stretching due to their contracted pitches. In contrast, the linearly polarized light passing through deformed CLCEs can be modulated by optical rotation, resulting in distinct transmission colors that can be discerned through mechanical deformations. We demonstrate a visual signaling system with color information derived from optical rotation. By comprehending and manipulating the mechanoresponsive behavior of CLCEs, we can advance these materials into innovative solutions with enhanced functionality and performance, thereby broadening their applications for human life enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data vs. MC Comparison of Light Signal from Cosmic Rays in the ICARUS Detectors

Currently, the ICARUS-T600 liquid argon TPC is collecting data exposed to Booster Neutrino and Numi off-axis beams within the SBN program at Fermilab. A light detection system, based on PMTs deployed behind the TPC wire chambers, is in place to detect vacuum ultraviolet photons produced by ionizing particles in LAr. This system is fundamental for the detector operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the TPC is exposed to a huge flux of cosmic rays due to its operations at shallow depths, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the beam spill gates. This contribution will primarily focus on the comparative study (data vs. MC) of light signal of cosmic muons to validate the light emulation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

The Impact of Reconstruction in Pandora on Sensitivity to the Low-Energy Excess Signal at MicroBooNE

With the MicroBooNE collaboration’s first low-energy excess (LEE) searches complete and twice the amount of data to analyse in future iterations, it is imperative that we begin considering the potential analysis upgrades that can be achieved, such as those in the event reconstruction level. This note identifies the areas in Pandora reconstruction framework that could be improved upon, and evaluates their impact through cheated selections using MicroBooNE’s exclusive pionless LEE search as a benchmark. Vertexing and proton reconstruction improvements are demonstrated to have significant potential benefits in terms of sensitivity to the LEE signal and thus should be prioritised. Sensitivity projections for the full 10.1e20 POT are 3.2σ and 2.3σ for vertex and proton cheated selections respectively, and 3.3σ for the combined effect of both, compared to 2.1σ in the absence of the cheated selections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Multiplexing and Demultiplexing Signals for Radiography Application Using the Discrete Fourier Transform

Our goal is to develop an X-ray phase-contrast imaging system that can provide excellent soft tissue contrast of phase, attenuation, and small-angle scatter. We propose to replace the common system of G0, G1, and G2 gradings with a biprism array to replace the G1 grading and introduce a novel X-ray tube designed to replace the motion of the phase stepping grading G2. The proposed X-ray tube uses temporal multiplexing to provide simultaneous virtual “electronic phase stepping.” In this work the discrete Fourier transform is used to separate from the composite measurement individual X-ray phase contrast measurements sampled at different frequencies. The method performs a discrete Fourier transform of a composite refence sequence to obtain using the frequency amplitudes calibration factors needed to extract the X-ray phase contrast measurement amplitudes from the composite image. The composite reference sequence is the sum of the individual sequences, at different frequencies, with amplitudes of one. The method takes the discrete Fourier transform of this composite reference sequence; whereby, the amplitude of each frequency component is compared with the total sum of its stand-alone sequence amplitude. A calibration factor is determined so that the amplitude of this composite reference frequency times the calibration factor must equal the total sum of the sequence amplitude—the zero-frequency amplitude of the discrete Fourier transform of its stand-alone sequence. To demultiplex the composite measured signal these calibration factors are multiplied by the amplitudes of the frequency components of the discrete Fourier transform of the composite X-phase-contrast measurement to obtain the amplitude of each frequency encoded measurement. Using these calibration factors, we demonstrate with the discrete Fourier transform in Mathematica the extraction of individual images from a composite image that one would expect obtaining from our proposed new X-ray phase contrast imaging system. We then demonstrate as an example how using images from X-ray phase contrast data one can calculate phase, attenuation and the dark field images using grading phase step data supplied to use from Microworks, GmbH in Karlsruhe, Germany.

42 ENGINEERING↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗
DOE OSTI2025

Analog Signal Multiplexing System for the IOTA Proton Injector

he Fermilab Accelerator Science and Technology (FAST) Facility at FNAL is a dedicated research and development center focused on advancing particle accelerator technologies for future applications worldwide. Currently, a key objective of FAST Opera-tions is to commission the 2.5 MeV IOTA Proton Injec-tor (IPI) and enable proton injection into the Integrable Optics Test Accelerator (IOTA) storage ring. The low and medium-energy sections of the IPI include four frame-style dipole trims and two multi-function cor-rectors with independently controlled coils, requiring readout of 32 analog channels for current and voltage monitoring in total. To reduce cost and optimize rack space within the PLC-based control system, a 32-to-4 analog signal multiplexing system was designed and implemented. This system enables real-time readback of excitation parameters from all magnetic correctors. This paper presents the design, construction, implementation, and performance of the multiplexing system.

MacLean, Daniel R. [Fermilab] (ORCID:0000000210103↗
DOE OSTI2025

Enhanced Lighting Signals for Safety and Efficiency - Experiments With Addressable LEDs

For enhanced roadway safety, clear and immediate visual cues are essential for preventing accidents between drivers and pedestrians. At intersections, however, the line of sight to other roadway users may be obstructed by vehicles and infrastructure. Additionally, adverse conditions, including low visibility, poor weather, or inadequate lighting can increase the potential for collisions. Distracted drivers and pedestrians can further exacerbate the risk of accidents, particularly when using a smartphone, rather than focusing on roadway surroundings. These issues demonstrate the need for infrastructure upgrades that enhance visibility and awareness at crosswalks. A potential solution is through enhanced lighting signals integrated into the roadway infrastructure. One such example is the use of addressable LEDs, individually controllable lights that can change color and brightness instantaneously through programmable microcontrollers. They can be installed and integrated into crosswalks to maintain visibility in conditions where pedestrians may be difficult to see, while also offering peripheral cues to pedestrians who may be distracted by their phones or other objects rather than the road. Such a system (as one example) that is integrated into a traffic intersection digital twin that tracks all roadway users accurately, has the potential to enhance visibility of vulnerable road users, and thus enhance safety. This paper examines the potential implementation and feasibility of this technology, as well as the safety benefits it could provide. Laboratory experiments with addressable LEDs reveal the capabilities and challenges of this technology for roadway infrastructure safety. These findings could pave the way for more integrated lighting in infrastructure for vehicles and pedestrians at intersections, merge and diverge locations, and other areas where complex interactions present safety hazards. Such lighting solutions, enabled by modern computation and communications, could enhance safety and efficiency in our transportation system and improve overall mobility.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Probing BSM Oscillatory Signals with the DUNE Detectors and the LBNF Neutrino Beam: NSI and Sterile Neutrino Sensitivities

The Deep Underground Neutrino Experiment (DUNE) is a flagship long-baseline accelerator neutrino experiment under construction in the U.S. With a 1,300 km distance between its Near Detector (ND) and Far Detector (FD), the world’s most intense LBNF (Long-Baseline Neutrino Facility) neutrino beam, and high-resolution LArTPC (Liquid Argon Time Projection Chamber) detectors, DUNE will measure the neutrino oscillation parameters with unprecedented precision. In addition to the determination of the neutrino mass ordering and the potential discovery of Charge-Parity violation in the leptonic sector, DUNE's capabilities present a unique opportunity for probing Beyond the Standard Model (BSM) physics signals with neutrinos. Examples of BSM physics manifestations include the presence of Non-Standard Interactions (NSI) of neutrinos with matter, or the existence of sterile neutrinos that mix with 3-Flavor neutrinos. In this study, we present a joint ND+FD fit to simulated data assessing DUNE's sensitivity to probing neutrino NSI, as well as scenarios including sterile neutrino mixing.

Prais, Luiz [Cincinnati U.] (ORCID:000000018224947↗
DOE OSTI2022

Searching for Exotic Signals with the NOvA Experiment

Two highly segmented NOvA scintillation detectors, separated by 810 km and located in the pathof the NuMI neutrino beam produced at Fermilab, are optimized to study the neutrino oscillationphenomenon. At the same time, the larger Far Detector with 4,000 m2 surface area is capable to search for the low-mass magnetic monopoles, and to monitor the flux of the high-multiplicitycosmic ray showers. The smaller Near Detector, located 100 m underground at Fermilab, is ableto search for the presence of possible elusive Dark Matter particles in the high-intensity NuMIneutrino beam, and to study the seasonal variations of multi-muon cosmic flux component. BothNOvA detectors serve in combination as a powerful supernova neutrino detector, and allow forthe multi-messenger signal searches in coincidence with LIGO/Virgo gravitational wave events.A survey of the most recent NOvA results on these topics is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Multivariable quantum signal processing (M-QSP): prophecies of the two-headed oracle

Recent work shows that quantum signal processing (QSP) and its multi-qubit lifted version, quantum singular value transformation (QSVT), unify and improve the presentation of most quantum algorithms. QSP/QSVT characterize the ability, by alternating ansätze, to obliviously transform the singular values of subsystems of unitary matrices by polynomial functions; these algorithms are numerically stable and analytically well-understood. That said, QSP/QSVT require consistent access to a single oracle, saying nothing about computing joint properties of two or more oracles; these can be far cheaper to determine given an ability to pit oracles against one another coherently. This work introduces a corresponding theory of QSP over multiple variables: M-QSP. Surprisingly, despite the non-existence of the fundamental theorem of algebra for multivariable polynomials, there exist necessary and sufficient conditions under which a desired stable multivariable polynomial transformation is possible. Moreover, the classical subroutines used by QSP protocols survive in the multivariable setting for non-obvious reasons, and remain numerically stable and efficient. Up to a well-defined conjecture, we give proof that the family of achievable multivariable transforms is as loosely constrained as could be expected. The unique ability of M-QSP to obliviously approximate joint functions of multiple variables coherently leads to novel speedups incommensurate with those of other quantum algorithms, and provides a bridge from quantum algorithms to algebraic geometry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

On the energy landscape of symmetric quantum signal processing

Symmetric quantum signal processing provides a parameterized representation of a real polynomial, which can be translated into an efficient quantum circuit for performing a wide range of computational tasks on quantum computers. For a given polynomial f , the parameters (called phase factors) can be obtained by solving an optimization problem. However, the cost function is non-convex, and has a very complex energy landscape with numerous global and local minima. It is therefore surprising that the solution can be robustly obtained in practice, starting from a fixed initial guess Φ 0 that contains no information of the input polynomial. To investigate this phenomenon, we first explicitly characterize all the global minima of the cost function. We then prove that one particular global minimum (called the maximal solution) belongs to a neighborhood of Φ 0 , on which the cost function is strongly convex under the condition ‖ f ‖ ∞ = O ( d − 1 ) with d = d e g ( f ) . Our result provides a partial explanation of the aforementioned success of optimization algorithms.

Wang, Jiasu↗
DOE OSTI2025

Block encoding bosons by signal processing

Block Encoding (BE) is a crucial subroutine in many modern quantum algorithms, including those with near-optimal scaling for simulating quantum many-body systems, which often rely on Quantum Signal Processing (QSP). Currently, the primary methods for constructing BEs are the Linear Combination of Unitaries (LCU) and the sparse oracle approach. In this work, we demonstrate that QSP-based techniques, such as Quantum Singular Value Transformation (QSVT) and Quantum Eigenvalue Transformation for Unitary Matrices (QETU), can themselves be efficiently utilized for BE implementation. Specifically, we present several examples of using QSVT and QETU algorithms, along with their combinations, to block encode Hamiltonians for lattice bosons, an essential ingredient in simulations of high-energy physics. We also introduce a straightforward approach to BE based on the exact implementation of Linear Operators Via Exponentiation and LCU (LOVE-LCU). We find that, while using QSVT for BE results in the best asymptotic gate count scaling with the number of qubits per site, LOVE-LCU outperforms all other methods for operators acting on up to qubits, highlighting the importance of concrete circuit constructions over mere comparisons of asymptotic scalings. Using LOVE-LCU to implement the BE, we simulate the time evolution of single-site and two-site systems in the lattice theory using the Generalized QSP algorithm and compare the gate counts to those required for Trotter simulation.

Kane, Christopher F↗
DOE OSTI2024

Overexpression of the Mas1 gene mitigated LPS-induced inflammatory injury in mammary epithelial cells by inhibiting the NF-κB/MAPKs signaling pathways

Breast infection is the primary etiology of mastitis in dairy cows, leading to a reduction in the quality of dairy products and resulting in substantial economic losses for animal husbandry. Although antibiotic treatment can eliminate the pathogenic microorganisms that induce mastitis, it cannot repair the inflammatory damage of mammary epithelial cells and blood milk barrier. Mas1 is a G protein-coupled receptor, and its role in lipopolysaccharide (LPS) -induced inflammatory injury to mammary epithelial cells has not been studied. LPS treatment of EpH4 EV cells led to a significant downregulation of Mas1 transcript levels, which attracted our great interest, suggesting that Mas1 may be an important target for the treatment of mastitis. Therefore, this study intends to verify the role of Mas1 in the inflammatory injury of EpH4 EV cells by gene overexpression technology and gene silencing technology. The findings demonstrated that the overexpression of the Mas1 gene effectively reversed the activation of the nuclear factor-κB/mitogen-activated protein kinase (NF-κB/MAPK) signaling pathways induced by LPS, while also suppressing the upregulation of pro-inflammatory mediators. Furthermore, overexpression of the Mas1 gene reversed the downregulation of zonula occludens 1 (ZO-1), Occludin, and Claudin-3 caused by LPS, suggesting that Mas1 could promote to repair the blood-milk barrier. However, the silencing of the Mas1 gene using siRNA resulted in a contrasting effect. These results indicated that Mas1 alleviated the inflammatory injury of mammary epithelial cells induced by LPS.

Yan, Shuping↗
DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗
DOE OSTI2021

A Study of Integrated Signal and Power Transfer for Compact Isolated SiC MOSFET Gate-Drivers

This work discusses a novel set of alternate implementations of isolated gate driver circuits for power electronic transistors. The proposed topologies for the driver have been designed specifically for SiC power MOSFET. Three different solutions are discussed, all of them providing the required gate turn-on and turn-off command signal with galvanic isolation, but also supplying power to the secondary side of the driver by means of magnetic transformers. The resulting solutions, all of them implemented with simple circuitry, enable the integration of the driver into the power cell, allowing for theoretical higher power density values in the final system. The principle of operation of the different solutions is discussed, and then the main relevant implementation details are presented. After that, the operation of the circuits is demonstrated experimentally, by testing a set of prototypes of these drivers. This provides a comprehensive design example that assesses the feasibility of the proposed solutions. Finally, the main results of the performance of the three gate drivers, on an SiC MOSFET-based prototype are presented and compared.

42 ENGINEERING↗
DOE OSTI2022

Searching for an Enhanced Signal of the Onset of Color Transparency in Baryons with D(e,e′p)n Scattering

Observation of the onset of color transparency in baryons would provide a new means of studying the nuclear strong force and would be the first clear evidence of baryons transforming into a color-neutral point-like size in the nucleus as predicted by quantum chromodynamics. Recent C(e,e′p) results from electron-scattering did not observe the onset of color transparency (CT) in protons up to spacelike four-momentum transfers squared, Q2=14.2 GeV2. The traditional methods of searching for CT in (e,e′p) scattering use heavy targets favoring kinematics with already initially reduced final state interactions (FSIs) such that any CT effect that further reduces FSIs will be small. The reasoning behind this choice is the difficulty in accounting for all FSIs. D(e,e′p)n, on the other hand, has well-understood FSI contributions from double scattering with a known dependence on the kinematics and can show an increased sensitivity to hadrons in point-like configurations. Double scattering is the square of the re-scattering amplitude in which the knocked-out nucleon interacts with the spectator nucleon, a process that is suppressed in the presence of point-like configurations and is particularly well-studied for the deuteron. This suppression yields a quadratic sensitivity to CT effects and is strongly dependent on the choice of kinematics. Here, we describe a possible Jefferson National Accelerator Facility (JLab) electron-scattering experiment that utilizes these kinematics and explores the potential signal for the onset of CT with enhanced sensitivity as compared to recent experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R 2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m 3 /m 3 ). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

47 OTHER INSTRUMENTATION↗