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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques -- A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Space vehicle with customizable payload and docking station

A “black box” space vehicle solution may allow a payload developer to define the mission space and provide mission hardware within a predetermined volume and with predetermined connectivity. Components such as the power module, radios and boards, attitude determination and control system (ADCS), command and data handling (C&DH), etc. may all be provided as part of a “stock” (i.e., core) space vehicle. The payload provided by the payload developer may be plugged into the space vehicle payload section, tested, and launched without custom development of core space vehicle components by the payload developer. A docking station may facilitate convenient development and testing of the space vehicle while reducing handling thereof.

Judd, Stephen↗
DOE OSTI2021

Architecture Of A Multi-channel Data Streaming Device With An Fpga As A Coprocessor

The design of a data acquisition system often involves the integration of a Field Programmable Gate Array (FPGA) with analog front-end components to achieve precise timing and control. Reuse of these hardware systems can be difficult since they need to be tightly coupled to the communications interface and timing requirements of the specific ADC used. A hybrid design exploring the use of FPGA as a coprocessor to a traditional CPU in a dataflow architecture is presented. Reduction in the volume of data and gradual transitioning of data processing away from a hard real-time environment are both discussed. Chief design concerns, including data throughput and precise synchronization with external stimuli, are addressed. The discussion is illustrated by the implementation of a multi-channel digital integrator, a device based entirely on commercial off-the-shelf (COTS) equipment.

Nogiec, Jerzy M.↗
DOE OSTI2021

High power handling digitizer using photonics

Devices, methods for analog-to-digital converters (ADCs) that perform high-dynamic range measurements based on optical techniques are disclosed. In one example aspect, an optical encoder includes a polarization rotator configured to receive a train of optical pulses, and an electro-optic (EO) modulator coupled to an output of the polarization rotator. The EO modulator is configured to receive a radio frequency (RF) signal and to produce a phase modulated signal in accordance with the RF signal. The optical encoder also includes a polarizing beam splitter coupled to the output of the EO modulator; and an optical hybrid configured to receive two optical signals from the polarizing beam splitter and to produce four optical outputs that are each phase shifted with respect to one another.

DeVore, Peter Thomas Setsuda↗
DOE OSTI2022

Multi-channel high-speed converter clock synchronization with autonomous coherent deterministic latency

A system and corresponding method that achieves coherency and deterministic latency (CDL) autonomously upon power on is disclosed. The system, for example, a multi-channel RF system, may require CDL with respect to the digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) assigned to the channels in the system. CDL is achieved through a timed combination of external reference and synchronization signals, resetting and disabling of various clock dividers, and enabling clock generation. In addition to synchronizing all of the clocks, the data acquisition sequence must be synchronized across all of the channels, whether they are on chips, cards, or chassis. Data acquisition synchronization may be implemented using an initiator/target or a wired OR mode configuration.

Brady, Charles E.↗
DOE OSTI2023

Digital encoding algorithm for pixelated detectors

A detector for imaging and efficiently digitizing a spatial distribution of photon flux includes pixel circuits that compressively encode pixel values generated by integrated analog to digital converters (ADCs). On-pixel digital compression circuits (DCCs) implement compression to increase continuous frame rate by reducing the number of bits per pixel while keeping quantization error below Poisson noise. Several mapping algorithms for photon-counting and charge-integrating detectors and compact digital logic implementations are presented.

Hammer, Michael P.↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux from galactic core-collapse supernovae. These neutrinos, which exist in the low energy range of up to a few tens of MeV and are responsible for carrying away over 99% of the gravitational binding energy of the supernova, provide an opportunity to study the end of life evolution of massive stars, as well as unique properties and interactions of neutrinos. Because galactic supernovae are expected to occur only on the timespan of every few decades, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, detecting these supernova interactions requires sifting through a large amount of data, and DUNE detectors require a trigger to signal when supernova neutrino events occur. Machine learning provides a potential approach to creating this trigger. This project generates ADC and ground truth images of neutrino interactions in a LArTPC detector as simulated by the Model of Argon Reaction Low Energy Yields (MARLEY) to be used for machine learning. The eventual goal of this work is to facilitate DUNE s detection of supernova neutrino interactions by building a machine learning pipeline to train the trigger algorithm.

Damish, Stephanie↗
DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux originating from galactic core-collapse supernovae. These neutrinos provide an opportunity to study the end of life evolution of massive stars, and reveal information about the structure of core-collapse that is not visible in observations of the electromagnetic spectrum. Because of the rarity of these events, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, this will require sifting through a large quantity of data, motivating the development of a trigger algorithm to identify significant events and discard irrelevant data. Machine learning provides a potential approach to building this trigger. This project generates ADC and ground truth images of simulated neutrino interactions in a LArTPC detector to be used for machine learning, and uses them to train a sparse Convolutional Neural Network (C NN). The performance of this model when applied to the task of pixel classification based on interaction type is examined. This project found that the sparse CNN approach has the potential to have high accuracy in pixel classification, meaning it may be highly relevant to the development of a supernova neutrino trigger for the DUNE far detector.

Damish, S.↗
DOE OSTI2024

Calibration of the analog beam-signal hardware for the credited engineered beam power limit system at the Proton Power Upgrade Project at the Spallation Neutron Source

A programmable signal processor-based credited safety control that calculates pulsed beam power based on beam kinetic energy and charge was designed as part of the Proton Power Upgrade (PPU) project at the Spallation Neutron Source (SNS). The system must reliably shut off the beam if the average power exceeds 2.145 MW averaging over 60 seconds. System calibration requires pedigree in measurements, calibration setup, and calculations. This paper discusses the calibration of the analog beam signal components up to and including the Analog Digital Convertors (ADCs) for implementation into the Safety Programmable Logic Controllers (PLCs) and Field Programmable Gate Arrays (FPGAs).

Bobrek, Miljko↗
DOE OSTI2024

High power handling digitizer using photonics

Devices, methods for analog-to-digital converters (ADCs) that perform high-dynamic range measurements based on optical techniques are disclosed. In one example aspect, an optical encoder includes a polarization rotator configured to receive a train of optical pulses, and an electro-optic (EO) modulator coupled to an output of the polarization rotator. The EO modulator is configured to receive a radio frequency (RF) signal and to produce a phase modulated signal in accordance with the RF signal. The optical encoder also includes a polarizing beam splitter coupled to the output of the EO modulator; and an optical hybrid configured to receive two optical signals from the polarizing beam splitter and to produce four optical outputs that are each phase shifted with respect to one another.

DeVore, Peter Thomas Setsuda↗
DOE OSTI2024

Development of online pulse-finding algorithms for the Mu2e Stopping Target Monitor and an evaluation of the signal to background ratio for the Mu2e stopped-muon rate determination

This thesis presents a determination of the acceptance of the Mu2e Stopping Target Monitor (STM) detector for both signal and background events. The rate of X-rays of a specific energy in the STM is used to determine the rate of stopped muons in the aluminium stopping target, which is used as the normalisation for all Mu2e measurements, particularly the branching ratio for a charged lepton flavour violating (cLFV) process. The acceptance for the 347\,keV $2p-1s$ aluminium signal X-ray is determined to be $(8.03 \pm 0.05) \times 10^{-10}$\,cm$^{-2}$ and the acceptance for the background photons (at 347\,keV) to be $(3.19 \pm 0.21) \times 10^{-8}$\,cm$^{-2}$. This results in a signal-to-background ratio of approximately two which is significantly higher than had previously been estimated. These signal-to-background rates are used to determine the time required to achieve a statistical uncertainty of 10\% on the number of 347\,keV X-rays as a function of the detector resolution and back ground rate. For a resolution of 2\,keV, and the background rate determined in this thesis, approximately one minute of data is required. The three corrections needed to be applied to the measured 347\,keV rate to determine the rate of stopped muons are also determined and potential sources of bias arising from the background shape, background fit range and energy calibration are investigated and found to be insignificant. The raw energy of the particles in the STM detector comes from a 16-bit ADC digitising at $\sim 300$\,MHz. It is not possible to store all the raw digitisations and online algorithms have been developed to rapidly select pulses in the detector and reconstruct their energy. The performance of these algorithms has been characterised with simulated data as a function of detector rate and resolution and optimum operating points for the algorithms have been defined. The integrity of the algorithms has also been demonstrated and characterised on test-beam data at high r ates and with radioactive sources at low rates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Development of BPM electronics for PIP-II at Fermilab

This paper presents the uTCA4.0-based BPM electronics for PIP-II, featuring four 250 MSPS ADCs and a Xilinx UltraScale+ MPSoC FPGA with 10 GbE uplink. Design elements include signal conditioning, clock, and thermal management. The FPGA performs signal processing, time tagging, digital down-conversion, and phase drift compensation. Position and phase resolution, and thermal stability - is validated through dedicated testing.

Liu, Shengli [Fermilab] (ORCID:0009000128436936)↗
DOE OSTI2025

Obsidian

Obsidian A35 is a compact FPGA carrier board designed to interface with ADCs, DACs or other devices, either stand-alone or as an I/O expansion board. The connectivity includes 1 GigE, 4 SFP, 6 PMOD, FTDI USB and Arduino shield compatible header. The board features also a FPGA boot SPI Flash, on-chip DDR3 memory, VCXO and White Rabbit compatibility.

Moore, Victoria [Lawrence Berkeley National Labora↗
DOE OSTI2026

CAPTAN+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗
DOE OSTI2022

Prompt and non-prompt J/ψ production cross sections at midrapidity in proton-proton collisions at $ \sqrt{\mathrm{s}} $ = 5.02 and 13 TeV

The production of J /ψ is measured at midrapidity ( |y| < 0 . 9) in proton-proton collisions at \( \sqrt{s} \) = 5 . 02 and 13 TeV, through the dielectron decay channel, using the ALICE detector at the Large Hadron Collider. The data sets used for the analyses correspond to integrated luminosities of \( \mathcal{L} \) int = 19.4 ± 0.4 nb - 1 and \( \mathcal{L} \) int = 32.2 ± 0.5 nb - 1 at \( \sqrt{s} \) = 5 . 02 and 13 TeV, respectively. The fraction of non-prompt J /ψ mesons, i.e. those originating from the decay of beauty hadrons, is measured down to a transverse momentum p T = 2 GeV /c (1 GeV /c ) at \( \sqrt{s} \) = 5 . 02 TeV (13 TeV). The p T and rapidity ( y ) differential cross sections, as well as the corresponding values integrated over p T and y , are carried out separately for prompt and non-prompt J /ψ mesons. The results are compared with measurements from other experiments and theoretical calculations based on quantum chromodynamics (QCD). The shapes of the p T and y distributions of beauty quarks predicted by state-of-the-art perturbative QCD models are used to extrapolate an estimate of the \( \mathrm{b}\overline{\mathrm{b}} \) pair cross section at midrapidity and in the total phase space. The total \( \mathrm{b}\overline{\mathrm{b}} \) cross sections are found to be \( {\sigma}_{\mathrm{b}\overline{\mathrm{b}}} \) = 541 ± 45 (stat . ) ± 69 \( {\left(\mathrm{syst}.\right)}_{-12}^{+10} \) (extr . ) μ b and \( {\sigma}_{\mathrm{b}\overline{\mathrm{b}}} \) = 218 ± 37 (stat . ) ± 31 \( {\left(\mathrm{syst}.\right)}_{-9.1}^{+8.2} \) (extr . ) μ b at \( \sqrt{s} \) = 13 and 5.02 TeV, respectively. The value obtained from the combination of ALICE and LHCb measurements in pp collisions at \( \sqrt{s} \) = 13 TeV is also provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Higher harmonic non-linear flow modes of charged hadrons in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV

Anisotropic flow coefficients, v n , non-linear flow mode coefficients, χ n,mk , and correlations among different symmetry planes, ρ n,mk are measured in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV. Results obtained with multi-particle correlations are reported for the transverse momentum interval 0.2 < p T < 5.0 GeV/c within the pseudorapidity interval 0.4 < |η| < 0.8 as a function of collision centrality. The v n coefficients and χ n,mk and ρ n,mk are presented up to the ninth and seventh harmonic order, respectively. Calculations suggest that the correlations measured in different symmetry planes and the non-linear flow mode coefficients are dependent on the shear and bulk viscosity to entropy ratios of the medium created in heavy-ion collisions. The comparison between these measurements and those at lower energies and calculations from hydrodynamic models places strong constraints on the initial conditions and transport properties of the system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗