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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ultrafast Annealing Improves SNR and Long-Term Stability of a Highly Multiplexed Line-by-Line FBG Array Inscribed by Femtosecond Laser in a Coreless Fiber for Extreme-Temperature Applications

This study reports the fabrication of a fourth-order line-by-line fiber Bragg grating (FBG) array using femtosecond laser inscription within a highly multimode coreless optical fiber, with a particular focus on achieving substantial multiplexing capabilities. An ultrafast annealing procedure is employed, resulting in an impressive enhancement of the FBG sensor’s fringe visibility by approximately 13 dB, signifying a notable improvement of approximately ~4 dB. This substantial enhancement contributes to the long-term stability and performance of the multiplexed FBG array in extreme-temperature conditions. The systematic fabrication approach employed for the multiplexed FBG array guarantees a high signal-to-noise ratio (SNR) for each individual FBG within the array. This FBG array is intended for extreme-temperature applications, addressing limitations associated with traditional FBGs based on doped optical fibers, including SNR degradation and temperature-induced fringe drift. Testing at temperatures up to 1120 °C demonstrates the FBG array’s stability without fluctuations in readings. Furthermore, it endures seven heat cycles, spanning from 500 °C to 1120 °C, over 60 h, exhibiting outstanding thermal stability. Furthermore, this highly multiplexed FBG array with an ultrafast annealing approach holds promise for extreme-temperature environments, such as steelmaking, where precise and reliable distributed temperature monitoring is imperative.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Beacon-based precision navigation and timing (PNT) system

Beacon-based Precision Navigation and Timing (PNT) may use a constellation of space vehicles (e.g., small, low cost satellites) coupled to a network of ground stations and a network of beacons. Such a system be provided at a cost that is approximately 100 times lower than GPS both to build and to operate. The resulting system may also provide fast acquisition, improved SNR, improved anti-jam and anti-spoofing capabilities, and six-inch scale location determination, making it applicable to both existing PNT applications and enabling new applications.

Judd, Stephen↗
DOE OSTI2015

TU-F-CAMPUS-I-05: Investigation of An EMCCD Detector with Variable Gain in a Micro-CT System

Purpose: To investigate the performance of a newly built Electron Multiplying Charged Coupled Device (EMCCD) based Micro-CT system, with variable detector gain, using a phantom containing contrast agent of different concentrations. Methods: We built a micro- CT system with an EMCCD having 8 microns pixels and on-chip variable gain. We tested the system using a phantom containing five tubes filled with different iodine contrast solutions (30% to 70%). First, we scanned the phantom using various x-ray exposures values at 40 kVp and constant detector gain. Next, for the same tube currents, the detector gain was increased to maintain the air value of the projection image constant. A standard FDK algorithm was used to reconstruct the data. Performance was analyzed by comparing the signal-to-noise ratio (SNR) measurements for increased gain with those for the low constant gain at each exposure. Results: The high detector gain reconstructed data SNR was always greater than the low gain data SNR for all x-ray settings and for all iodine features. The largest increases were observed for low contrast features, 30% iodine concentration, where the SNR improvement approached 2. Conclusion: One of the first implementations of an EMCCD based micro- CT system was presented and used to image a phantom with various iodine solution concentrations. The analysis of the reconstructed volumes showed a significant improvement of the SNR especially for low contrast features. The unique on-chip gain feature is a substantial benefit allowing the use of the system at very low x-ray exposures per frame.Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp. Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Real-time image denoising of mixed Poisson–Gaussian noise in fluorescence microscopy images using ImageJ

Fluorescence microscopy imaging speed is fundamentally limited by the measurement signal-to-noise ratio (SNR). To improve image SNR for a given image acquisition rate, computational denoising techniques can be used to suppress noise. However, common techniques to estimate a denoised image from a single frame either are computationally expensive or rely on simple noise statistical models. These models assume Poisson or Gaussian noise statistics, which are not appropriate for many fluorescence microscopy applications that contain quantum shot noise and electronic Johnson–Nyquist noise, therefore a mixture of Poisson and Gaussian noise. In this paper, we show convolutional neural networks (CNNs) trained on mixed Poisson and Gaussian noise images to overcome the limitations of existing image denoising methods. The trained CNN is presented as an open-source ImageJ plugin that performs real-time image denoising (within tens of milliseconds) with superior performance (SNR improvement) compared to conventional fluorescence microscopy denoising methods. The method is validated on external datasets with out-of-distribution noise, contrast, structure, and imaging modalities from the training data and consistently achieves high-performance ( > <#comment/> 8 d B ) denoising in less time than other fluorescence microscopy denoising methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Fourth Generation MPDV and MBR at DARHT

A new experimental setup for diagnosing hydrotest performance was designed, built, and implemented at DARHT. The setup consists of 128 points of fourth generation (Gen4) multiplexed photonic Doppler velocimetry (MPDV) and 128 separate points of modulation based ranging (MBR) to serve as a direct complement to the MPDV. The diagnostics were designed to overcome limitations in the third generation of the MPDV diagnostic that limited laser launch power to ~10 mW per point. As the main failure mechanism identified in the third generation MPDV system arose from stimulated Brillouin scattering, a nonlinear optical phenomenon inherent in standard single mode fiber, the fourth generation MPDV system reduced the number of time-multiplexed channels by a factor of two. This has allowed laser launch power to be increased to as much as 200 mW per channel which is a 20 times increase in the signal to noise ratio (SNR) as compared with the third generation system. This document will first discuss the previous limitations and describe the design of the system. This will be followed by the results of a simple flyer plate experiment used to demonstrate the improved SNR as well as calibrate the phase errors in the system that MBR is sensitive to.

42 ENGINEERING↗
DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Adaptive Circuit Learning for Quantum Metrology

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization techniques to search for encoder and decoder circuits that scalably improve sensitivity under given application and noise characteristics. Furthermore, our approach uses a variational algorithm that can learn a quantum sensing circuit based on platform-specific control capacity, noise, and signal distribution. The quantum circuit is composed of an encoder which prepares the optimal sensing state and a decoder which gives an output distribution containing information of the signal. We optimize the full circuit to maximize the Signal-to-Noise Ratio (SNR). Furthermore, this learning algorithm can be run on real hardware scalably by using the "parameter-shift" rule which enables gradient evaluation on noisy quantum circuits, avoiding the exponential cost of quantum system simulation. We demonstrate up to 13.12x SNR improvement over existing fixed protocol (GHZ), and 3.19x Classical Fisher Information (CFI) improvement over the classical limit on 15 qubits using IBM quantum computer. More notably, our algorithm overcomes the decreasing performance of existing entanglement-based protocols with increased system sizes.

42 ENGINEERING↗
DOE OSTI2014

Using phase information to enhance speckle noise reduction in the ultrasonic NDE of coarse grain materials

Materials with a coarse grain structure are becoming increasingly prevalent in industry due to their resilience to stress and corrosion. These materials are difficult to inspect with ultrasound because reflections from the grains lead to high noise levels which hinder the echoes of interest. Spatially Averaged Sub-Aperture Correlation Imaging (SASACI) is an advanced array beamforming technique that uses the cross-correlation between images from array sub-apertures to generate an image weighting matrix, in order to reduce noise levels. This paper presents a method inspired by SASACI to further improve imaging using phase information to refine focusing and reduce noise. A-scans from adjacent array elements are cross-correlated using both signal amplitude and phase to refine delay laws and minimize phase aberration. The phase-based and amplitude-based corrected images are used as inputs to a two-dimensional cross-correlation algorithm that will output a weighting matrix that can be applied to any conventional image. This approach was validated experimentally using a 5MHz array a coarse grained Inconel 625 step wedge, and compared to the Total Focusing Method (TFM). Initial results have seen SNR improvements of over 20dB compared to TFM, and a resolution that is much higher.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Convergent laser beam shapes: Unveiling the dynamics of Laser-induced elastic waves in composite materials

Overcoming the low signal-to-noise ratio (SNR) in laser ultrasonic testing of composite materials remains a significant challenge. Current efforts focus on enhancing SNR by inserting more energy into the material through temporal and/or spatial modulation of the laser beam. However, potential SNR improvements through wave convergence and wave energy manipulation have been overlooked. This paper addresses this gap by demonstrating the convergence of different wave types to a designated point and by showing the feasibility of directing absorbed laser energy into a specific wave type through spatial modulation of the laser beam. To achieve this, mathematical expressions for the convergent laser beams are derived. Various laser beam profiles are then introduced to the thermoelastic equations and solved using the finite element method. The sample under investigation is a transversely isotropic unidirectional carbon fiber reinforced plastic, characterized by anisotropic thermal expansion coefficients and thermal conductivities. Results reveal pronounced convergence of the intended wave type at the center due to laser beam shaping. This study showcases the ability to direct absorbed laser energy toward a specific wave type through spatial modulation of the laser beam and highlights the role of material anisotropy in energy focusing.

composite materials↗
DOE OSTI2015

SU-C-201-03: Coded Aperture Gamma-Ray Imaging Using Pixelated Semiconductor Detectors

Purpose: Improved localization of gamma-ray emissions from radiotracers is essential to the progress of nuclear medicine. Polaris is a portable, room-temperature operated gamma-ray imaging spectrometer composed of two 3×3 arrays of thick CdZnTe (CZT) detectors, which detect gammas between 30keV and 3MeV with energy resolution of <1% FWHM at 662keV. Compton imaging is used to map out source distributions in 4-pi space; however, is only effective above 300keV where Compton scatter is dominant. This work extends imaging to photoelectric energies (<300keV) using coded aperture imaging (CAI), which is essential for localization of Tc-99m (140keV). Methods: CAI, similar to the pinhole camera, relies on an attenuating mask, with open/closed elements, placed between the source and position-sensitive detectors. Partial attenuation of the source results in a “shadow” or count distribution that closely matches a portion of the mask pattern. Ideally, each source direction corresponds to a unique count distribution. Using backprojection reconstruction, the source direction is determined within the field of view. The knowledge of 3D position of interaction results in improved image quality. Results: Using a single array of detectors, a coded aperture mask, and multiple Co-57 (122keV) point sources, image reconstruction is performed in real-time, on an event-by-event basis, resulting in images with an angular resolution of ∼6 degrees. Although material nonuniformities contribute to image degradation, the superposition of images from individual detectors results in improved SNR. CAI was integrated with Compton imaging for a seamless transition between energy regimes. Conclusion: For the first time, CAI has been applied to thick, 3D position sensitive CZT detectors. Real-time, combined CAI and Compton imaging is performed using two 3×3 detector arrays, resulting in a source distribution in space. This system has been commercialized by H3D, Inc. and is being acquired for various applications worldwide, including proton therapy imaging R&D.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID

Purpose: The purpose of this study was to validate the use of a cascaded linear system model for MV cone-beam CT (CBCT) using a multi-layer (MLI) electronic portal imaging device (EPID) and provide experimental insight into image formation. A validated 3D model provides insight into salient factors affecting reconstructed image quality, allowing potential for optimizing detector design for CBCT applications. Methods: A cascaded linear system model was developed to investigate the potential improvement in reconstructed image quality for MV CBCT using an MLI EPID. Inputs to the three-dimensional (3D) model include projection space MTF and NPS. Experimental validation was performed on a prototype MLI detector installed on the portal imaging arm of a Varian TrueBeam radiotherapy system. CBCT scans of up to 898 projections over 360 degrees were acquired at exposures of 16 and 64 MU. Image volumes were reconstructed using a Feldkamp-type (FDK) filtered backprojection (FBP) algorithm. Flat field images and scans of a Catphan model 604 phantom were acquired. The effect of 2×2 and 4×4 detector binning was also examined. Results: Using projection flat fields as an input, examination of the modeled and measured NPS in the axial plane exhibits good agreement. Binning projection images was shown to improve axial slice SDNR by a factor of approximately 1.4. This improvement is largely driven by a decrease in image noise of roughly 20%. However, this effect is accompanied by a subsequent loss in image resolution. Conclusion: The measured axial NPS shows good agreement with the theoretical calculation using a linear system model. Binning of projection images improves SNR of large objects on the Catphan phantom by decreasing noise. Specific imaging tasks will dictate the implementation image binning to two-dimensional projection images. The project was partially supported by a grant from Varian Medical Systems, Inc. and grant No. R01CA188446-01 from the National Cancer Institute.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Report to Lincoln Labs on TWPAs

This past spring LLNL’s Quantum Sensor’s team received two TWPA amplifiers from Lincoln Labs along with a data-sheet explaining handling, operations and expected performance. Here we will outline some of the initial tests performed on this amplifiers as part of LLNL’s Quantum Sensors Strategic Initiative (QSSI). Initial testing confirmed that both amplifiers worked and provided gain and SNR improvement similar to that called out in the data-sheets provided.

42 ENGINEERING↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Model Card for WaveDP

WaveDP was trained using both earthquake signals and pure noise waveforms from the Stanford Earthquake Dataset (STEAD). The model achieved a median signal-to-noise ratio (SNR) improvement of 7 dB. Because the model uses seismograms as direct input, the model is four times faster than an existing model for signal denoising that uses spectral representations of seismograms as input.

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Compressive Phase Contrast Tomography

When x-rays penetrate soft matter, their phase changes more rapidly than their amplitude. Interference effects visible with high brightness sources creates higher contrast, edge enhanced images. When the object is piecewise smooth (made of big blocks of a few components), such higher contrast datasets have a sparse solution. We apply basis pursuit solvers to improve SNR, remove ring artifacts, reduce the number of views and radiation dose from phase contrast datasets collected at the Hard X-Ray Micro Tomography Beamline at the Advanced Light Source. We report a GPU code for the most computationally intensive task, the gridding and inverse gridding algorithm (non uniform sampled Fourier transform).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗