Search NASA⌕ Search

SEARCH · Search NASA

Results for “ADCS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

All-digital Sensor System for Distributed Downhole Pressure Monitoring in Unconventional Fields

This project developed and validated (through field tests) a new low-cost all-digital pressure sensing technology for in situ distributed downhole pressure monitoring in unconventional oil and gas (UOG) fields. The all-digital sensing technology uses a built-in non-electric analog-to-digital converter (ADC) to transform the pressure information into a combination of binary (ON/OFF) states. As such, the system does not need downhole electronics for signal conditioning and telemetry. The all-digital sensors can be remotely logged over a long distance, and many sensors can be multiplexed for distributed sensing. Based on a review of unconventional wells in the Lower 48 states, the specification of the sensor is to measure pressure up to 69 MPa (10,000 psi) and temperature up to 250°C. A sensor with a helical bourdon sensing element and a digital signal decoder of 50 mm diameter and 109 mm length was constructed. The helical bourdon sensing element was made of 304L stainless steel and filled with motor oil. The digital converter was made up of 8 digital reading pads constructed of high-temperature epoxy with conductive inserts made of stainless steel. The sensor had a linear response to pressure with an accuracy of 0.14 MPa (20 psi). To withstand the high pressure, the sensor was enclosed in a stainless-steel pressure housing with a wall thickness of 5.5 mm, a diameter of 73 mm, and a length of 724 mm. In the laboratory tests, the sensor exhibited no temperature-related effects on the results. The sensor did not show drift over a 14-day test period at elevated pressure. A field test was conducted where the sensor was deployed in a test wellbore at the Quest drilling test facility to a depth of 0 feet over three weeks. The sensor was attached to the production rods, along with a downhole reference sensor of PPS27 type, which is a permanent downhole monitoring system. During the testing phase, the test well annular blow-out preventer was closed, and the well was pressurized at the surface to 11 MPa (1600 psi). The sensor read the elevated bottom hole pressure of 1500 psi. A multiplexing unit was created for the sensor to deploy multiple sensors on one data transmission line in a distributed approach. The multiplexing unit was tested in a simulated environment of 3048 m (10,000 ft) with five sensors distributed. The sensors were pressurized at different intervals. The multiplexed sensors recorded the correct pressure, and the multiplexing did not interfere with the readings. The proposed concept of an all-digital pressure sensor for harsh downhole environments was designed, manufactured, and tested in the laboratory and tested at the field to a up to 69 MPa and 250°C. This technology has high-temperature tolerance and has potential in downhole areas outside oil and gas, such as carbon capture and storage (CCS) and geothermal wells. The sensor concept has been proven in this project, but to create a commercially viable product, manufacturing a sensor with a smaller diameter needs to be performed.

02 PETROLEUM↗
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 that will train the trigger algorithm.

Damish, Stephanie↗
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 µm\textsuperscript{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\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} 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\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗
DOE OSTI2024

Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. This effort is pursuing the co-design development of high-performance readout smart pixel ASICs for a future Phase III High Luminosity upgrade of the Large Hadron Collider. A 1.6mm2 ASIC prototype was designed by Fermilab in CMOS 28 nm bulk process and submitted for manufacturing in February 2024. It leverages the analog front-end pixel design of a previous prototype fabricated and tested in 2023, which achieved a simulated detection level of ~400e- with 30fF input capacitance. The ROIC consists of two matrices of 16×16 smart pixels, each 25×25 μm2 in size. Each smart pixel contains a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. There is digital space for the integration of our fully combinatorial AI that performs momentum classification at the bunch crossing rate. The total power consumption is ∼6μW per pixel, which corresponds to ~1mW/cm2. The ASIC incorporates programmable front-end charge injection circuitry to generate pixel cluster charges during characterization. The cluster profile will be generated to duplicate hit characteristics of various momentum (pT). We will present early results from chip testing.

Parpillon, Benjamin↗
DOE OSTI2025

Performance and automatic calibration scheme of the waveform sampler in the ETROC2 ASIC chip

The waveform sampler in the CMS ETROC2 chip for LGAD gain aging monitoring is a 2.56-GS/s 12-bit 8x-Interleaved ADC that consists of a coarse SAR stage, and a fine stage. This architecture delivers high performance on a relatively modest 65 nm process, while requires finding up to 24 calibration constants through calibration. We developed an automatic calibration method using charge injection test data. After calibration, the baseline random error is reduced by a factor of 2.5–3 compared to the default calibration, and a 5% charge measurement precision is achieved in 15 fC charge injection tests.

Fu, Tao [Unlisted, US]↗
DOE OSTI2026

Apex Study: Compensating Transient Beam Loading in the RHIC 28 MHZ

With the EIC on the way, it is important that developments and strategies are in place to deal with the very high beam currents that the machine will feature. Specifically, the EIC will collide beams of up to 2.5 A, three times the beam current in RHIC. This higher beam current will cause significant voltage transients in the cavity fields which can lead to longitudinal instabilities and beam loss. In anticipation of these negative effects, studies were carried out on the RHIC 28 MHz cavities using newly developed firmware and software to diagnose and combat beam loading. Diagnostic tools such as the bunch-by-bunch (BbyB) ADC firmware and digital network analyzer (DNA) were used to characterize the closed loop system and transient on the cavity voltage magnitude and phase. Then, a one-turn delay feedback (OTFB) and adaptive feed-forward (aFFWD) were used to minimize the transient beam loading. The studies were carried out with beam during 2 accelerator physics experiements (APEXs) using one of the 28 MHz accelerating cavities here at RHIC.

43 PARTICLE ACCELERATORS↗
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 OSTI2024

ARM Aerial Facility (AAF) Merged Value-Added Product Report for Historical G-1 Field Campaigns

For 30 years, the U.S. Department of Energy (DOE) Office of Science supported an instrumented Grumman Gulfstream-1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) user facility Data Center (ADC) and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated data set was recently developed covering the final six years of G-1 operations (2013 to 2018). The integrated data set includes data collected from 236 flights (766.4 hours). Four of the seven field campaigns were based in the U.S. One campaign collected data from the wildfires in the U.S. Pacific Northwest and agricultural burns in the lower Mississippi River valley as part of the Biomass Burning Observation Project (BBOP) in 2013. In 2015, the ARM Cloud Aerosol Precipitation Experiment provided data on atmospheric rivers and associated aerosol-cloud interactions that produce heavy precipitation on the U.S. west coast during the early spring. Research data from Airborne Carbon Measurements-V (ACME-V), collected during the summer of 2015, gave scientists insight into trends and variability of trace gases in the atmosphere over the North Slope of Alaska to improve arctic climate models. In the early summer and autumn of 2016, the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign provided an extensive data set geared toward coupled processes that affect the life cycle of shallow clouds through the interaction among aerosol, cloud, land surface, and ecosystems. In 2014 (March and October), the airborne sampling moved outside of the U.S. to the city of Manaus in central Amazonia, Brazil, where residential and industrial emissions were extensively characterized by flights of the G-1. The GoAmazon2014/15 aircraft campaign data are being integrated with aquatic and terrestrial ecosystem measurements to quantify anthropogenic perturbations to a usually pristine tropical environment. Another international airborne mission was carried out in the Eastern North Atlantic region. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign saw the G-1 aircraft fly from Terceira Island in the Azores during the summer of 2017 and the winter of 2018. The campaign studied both seasons to measure key aerosol and cloud processes under various meteorological and cloud conditions with different aerosol sources. Then the G-1 deployed to the Sierras de Córdoba range in central Argentina from October to November 2018 for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign to study orographic convective cloud interactions with their surrounding environment. These comprehensive datastreams provide much-needed insight into spatiotemporal variability of thermodynamic quantities, aerosol and cloud states, and properties for addressing essential science questions in Earth system process studies.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2026

Short Circuit Detection and Voltage Sense for High Voltage Ionization Tube Power Supplies

Fermilab's PIP-II upgrade requires new rack-mounted power supplies for Beam Loss Monitor (BLM) ionization tubes compatible with the microTCA 4.1 standard, supporting high-side current measurement for short circuit detection, voltage sense telemetry, and low-side current measurement for beam loss readout. This work presents the design and preliminary schematic of such a supply. A resistive current sensing approach was chosen over inductive, optical, and Hall-effect alternatives for its independence from cable length and component availability. A 500 mΩ inline shunt steps the 2 kV common mode voltage down to roughly 70 V, producing a ~27 μV pulse during a short, which is amplified 500x, compared against a 14-bit DAC threshold, and latched to drive a fault line. Voltage sense steps the 2 kV output down at a 1V/1000V ratio, buffers it with a low bias current amplifier, and digitizes it via a 24-bit ADC over SPI. Onboard power is regulated from 12 V down to isolated 5 V and 3.3 V rails, with capacitive isolation on FPGA communication lines. Lumped parameter models were developed for the ionization tube (0.327 nF, 20 to 200 GΩ dynamic resistance) and the RG-58 coaxial cable to support the design. Component selection is complete and a preliminary schematic has been drawn in Altium Designer, forming the foundation for future prototyping and validation.

Yu, Kellen [Cornell U.]↗
DOE OSTI2022

The Readout Electronics of the Mu2e Electromagnetic Calorimeter

The Mu2e electromagnetic calorimeter has been designed to measure ~100 MeV electrons with energy resolution σE/E <10%, time resolution σt < 500ps and position resolution σx < 1cm. The detector is composed of 1348 un-doped CsI crystals coupled to two large area Silicon Photomultipliers (SiPMs). Each SiPM is connected to a Front End Electronics (FEE) chip which hosts the shaping amplifier and the high voltage linear regulator. A group of 20 FEE is controlled by one Mezzanine Board (MB) which transmits the amplified signals to one Digitizer ReAdout Controller board (DiRAC). The DiRAC samples the waveforms at 200 MHz with 12-bit ADCs, packs the data according to the Mu2e custom format and transmits them to the event builder through an optical transceiver. To limit the number of pass-through connectors and the length of the cables, the readout and digitization electronics is located inside the detector cryostat and close to the interaction target. The boards will have to sustain a neutron fluence of about 5x10 10 n/cm 2 @ 1 MeVeq (Si)/y and a Total Ionizing Dose of about 12 krad, while working into a 1T magnetic field and a vacuum of 10 (-4) Torr. This harsh operational environment has made the electronics design challenging and required an extended campaign of tests to select and qualify the employed electronic components. In this paper we report on the board architecture and design, on the qualification of the prototypes, as well as on the results of the first vertical slice test of the Mu2e calorimeter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Clostridium autoethanogenum isopropanol production via native plasmid pCA replicon

Clostridium autoethanogenum is a model gas-fermenting acetogen for commercial ethanol production. It is also a platform organism being developed for the carbon-negative production of acetone and isopropanol by gas fermentation. We have assembled a 5.5 kb pCA plasmid for type strain DSM10061 (JA1-1) using three genome sequence datasets. pCA is predicted to encode seven open-reading frames and estimated to be a low-copy number plasmid present at approximately 12 copies per chromosome. RNA-seq analyses indicate that pCA genes are transcribed at low levels and two proteins, CAETHG_05090 (putative replication protein) and CAETHG_05115 (hypothetical, a possible Mob protein), were detected at low levels during batch gas fermentations. Thiolase (thlA), CoA-transferase (ctfAB), and acetoacetate decarboxylase (adc) genes were introduced into a vector for isopropanol production in C. autoethanogenum using the native plasmid origin of replication. The availability of the pCA sequence will facilitate studies into its physiological role and could form the basis for genetic tool optimization.

09 BIOMASS FUELS↗
DOE OSTI2022

Exogenous Hemin alleviated cadmium stress in maize (Zea mays L.) by enhancing leaf photosynthesis, AsA-GSH cycle and polyamine metabolism

Cadmium (Cd) stress is one of the principal abiotic stresses that inhibit maize growth. The research was to explore (hemin chloride) Hemin (100 μmol L −1 ) on photosynthesis, ascorbic acid (AsA)-glutathione (GSH) cycle system, and polyamine metabolism of maize under Cd stress (85 mg L −1 ) using nutrient solution hydroponics, with Tiannong 9 (Cd tolerant) and Fenghe 6 (Cd sensitive) as experimental materials. The results showed that Hemin can increase leaf photosynthetic pigment content and ameliorate the ratio of Chlorophyll a/chlorophyll b ( Chla / Chlb ) under Cd stress. The values of ribose 1, 5-diphosphate carboxylase/oxygenase (RuBPcase) and phosphoenolpyruvate carboxylase (PEPCase), and total xanthophyll cycle pool [(violoxanthin (V), antiflavin (A) and zeaxanthin (Z)] increased, which enhancing xanthophyll cycle (DEPS) de-epoxidation, and alleviating stomatal and non-stomatal limitation of leaf photosynthesis. Hemin significantly increased net photosynthetic rate ( P n ), stomatal conductance ( g s ), transpiration rate ( T r ), photochemical quenching coefficient ( qP ), PSII maximum photochemical efficiency ( F v /F m ), and electron transfer rate ( ETR ), which contributed to the improvement of the PSII photosynthetic system. Compared with Cd stress, Hemin can reduce thiobartolic acid reactant (TBARS) content, superoxide anion radical (O 2 − ) production rate, hydrogen peroxide (H 2 O 2 ) accumulation, and the extent of electrolyte leakage (EL); decreased the level of malondialdehyde (MDA) content and increased the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT); slowed the decrease in dehydroascorbic acid reductase (DHAR) and monodehydroascorbate reductase (MDHAR) activity and the increase in glutathione reductase (GR) and ascorbate peroxidase (APX) activity in leaves; promoted the increase in AsA and GSH content, decreased dehydroascorbic acid (DHA) and oxidized glutathione (GSSG), and increased AsA/DHA and GSH/GSSG ratios under Cd stress. Hemin promoted the increase of conjugated and bound polyamine content, and the conversion process speed of free putrescine (Put) to free spermine (Spm) and spermidine (Spd) in maize; decreased polyamine oxidase (PAO) activity and increased diamine oxidase (DAO), arginine decarboxylase (ADC), ornithine decarboxylase (ODC) and S-adenosylmethionine decarboxylase (SAMDC) enzyme activities in leaves under Cd stress.

Piao, Lin↗
DOE OSTI2022

Benchmarking Real-Time Control Platforms Using a Matlab/Simulink Coder with Applications in the Control of DC/AC Switched Power Converters

In the control of DC/AC switched power converters (SPC), one of the most important aspects to be considered is the selection of the real-time control platform. The real-time control platform must be able to meet the high performance efficiency and regulation requirements of the DC/AC SPC, as these typically operate at switching frequencies in the order of kHz to MHz. For this reason, the hardware characteristics of the ADC and PWM, and the processing capacity of the real-time control platform are of vital importance when implementing advanced digital controllers that maintain voltage and current levels within regulatory standards. In this context, we aimed to perform a comparative study of the computation times of different real-time control platforms when implementing different control strategies for DC/AC switched power converters. We also analyzed the impact of the real-time control platforms on the THD of the voltages generated by the DC/AC switched power converters. With the help of this paper, researchers and developers will have criteria to select which real-time control platform to use in real-time control for DC/AC SPC applications.

42 ENGINEERING↗
DOE OSTI2020

Calibration of calorimetric measurement in a liquid argon time projection chamber

The liquid argon time projection chamber provides high-resolution event images and excellent calorimetric resolution for studying neutrino physics and searching for beyond-standard-model physics. In this article, we review the main physics processes that affect detector response, including the electronics and field responses, space charge effects, electron attachment to impurities, diffusion, and recombination. We describe methods to measure those effects, which are used to calibrate the detector response and convert the measured raw analog-to-digital converter (ADC) counts into the original energy deposition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Multiplexed Readout for an Experiment with a Large Number of Channels Using Single-Electron Sensitivity Skipper-CCDs

This paper presents the implementation of a multiplexed analog readout electronics system that can achieve single-electron counting using Skipper-CCDs with non-destructive readout. The proposed system allows the best performance of the sensors to be maintained, with sub-electron noise-level operation, while maintaining low-bandwidth data transfer, a minimum number of analog-to-digital converters (ADC) and low disk storage requirement with zero added multiplexing time, even for the simultaneous operation of thousands of channels. These features are possible with a combination of analog charge pile-up, sample and hold circuits and analog multiplexing. The implementation also aims to use the minimum number of components in circuits to keep compatibility with high-channel-density experiments using Skipper-CCDs for low-threshold particle detection applications. Performance details and experimental results using a sensor with 16 output stages are presented along with a review of the circuit design considerations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Search for Axions in Magnetic White Dwarf Polarization at Lick and Keck Observatories

We present the most sensitive search to date for light axion-like particles with masses below a micro-eV, using spectropolarimetric data collected from the Lick and Keck Observatories. The conversion of optical photons emitted from the surface of a magnetic white dwarf (MWD) into axions in the strong magnetic field around the star induces a nearly wavelength-independent linear polarization in the observed starlight. We analyze the Stokes parameters $(U, Q, I)$ measured with the Kast spectrograph at the Lick Observatory toward the MWDs SDSS J033320+000720 and ZTF J190132+145807, and with the LRISp-ADC instrument at the Keck Observatory toward ZTF J190132+145807, SDSS J002129+150223, and SDSS J100356+053825 to search for this effect. The data show no evidence of axion-induced linear polarization, and we set world-leading constraints on the axion-photon coupling $|g_{aγγ}| \lesssim 1.7 \times 10^{-12} \,\mathrm{GeV}^{-1}$ at the $95\%$ confidence level for masses $m_a \lesssim 2 \times 10^{-7}\,\mathrm{eV}$.

FOS: Physical sciences↗
NASA NTRS1967

Simple first order data compression processor concept

Data-compression processing systems based on an analog-to-digital converter /ADC/, includes a qualitative comparator for comparison of the ADC output with a ramp generator, which is connected as a bidirectional binary counter with selective inputs. A bidirectional ramp counter selects the proper ramp through a ramp generator selection network.

Anderson, T. O.↗