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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Delay-locked-loop timing error mitigation

Systems, methods, and circuits provide delay-locked loop (DLL) timing error mitigation. A DLL false-lock detection system can include DLL circuitry configured to receive a reference clock signal having a time period. The system can include shift register circuitry and latched comparison circuitry which can determine a time period of a locked condition of the DLL delay line with respect to the reference clock signal time period. The system can determine whether the system is correctly locked to the base time period or incorrectly locked to a multiple of the base time period. A further system can operate to cause a phase detector circuitry in a DLL to ignore the first edge of a reference clock signal presented to the phase detector circuitry and thereby avoid stuck-lock conditions.

Filippini, Leo↗
NASA NTRS1986

Atmospheric contributions to the column variance in direct-detection dial

One of the most important parameters of a Differential Absorption Lidar (DIAL) system is the delay time between the on and off resonant pulses. It is important that this delay time is sufficiently small to ensure that the atmosphere is effectively frozen between the pulses. Therefore, most Dial systems were designed with two lasers firing alternately less than 1 msec apart. Despite the importance of this parameter in the design of DIAL systems and its contribution to the overall error of a column measurement, very little is known about the size of the error for the case of a direct-detection system using atmospheric backscatter. The ultraviolet DIAL system uses two independent YAG/dye lasers and is therefore suitable for measuring the effects of different pulse delays on the variance of column measurements for a variety of atmospheric conditions. A set of DIAL returns were acquired with the two lasers tuned to the same wavelength and with a range of pulse delay times between 250 microseconds and several minutes. This data set was recorded in full on a computer and was used both to test different averaging techniques and also to evaluate atmospheric contributions to DIAL columns.

Milton, M. J. T.↗
NASA NTRS1983

Aerodynamic coefficient identification package dynamic data accuracy determinations: Lessons learned

The errors in the dynamic data output from the Aerodynamic Coefficient Identification Packages (ACIP) flown on Shuttle flights 1, 3, 4, and 5 were determined using the output from the Inertial Measurement Units (IMU). A weighted least-squares batch algorithm was empolyed. Using an averaging technique, signal detection was enhanced; this allowed improved calibration solutions. Global errors as large as 0.04 deg/sec for the ACIP gyros, 30 mg for linear accelerometers, and 0.5 deg/sec squared in the angular accelerometer channels were detected and removed with a combination is bias, scale factor, misalignment, and g-sensitive calibration constants. No attempt was made to minimize local ACIP dynamic data deviations representing sensed high-frequency vibration or instrument noise. Resulting 1sigma calibrated ACIP global accuracies were within 0.003 eg/sec, 1.0 mg, and 0.05 deg/sec squared for the gyros, linear accelerometers, and angular accelerometers, respectively.

Heck, M. L.↗
DOE OSTI2021

Organic contamination detection for isotopic analysis of water by laser spectroscopy

Hydrogen and oxygen stable isotope ratios (δ 2 H, δ 17 O, and δ 18 O values) are commonly used tracers of water. These ratios can be measured by isotope ratio infrared spectroscopy (IRIS). However, IRIS approaches are prone to errors induced by organic compounds present in plant, soil, and natural water samples. A novel approach using 17 O-excess values has shown promise for flagging spectrally contaminated plant samples during IRIS analysis. A systematic assessment of this flagging system is needed to prove it useful. Errors induced by methanol and ethanol water mixtures on measured IRIS and isotope ratio mass spectrometry (IRMS) results were evaluated. For IRIS analyses both liquid- and vapour-mode (via direct vapour equilibration) methods are used. The δ 2 H, δ 17 O, and δ 18 O values were measured and compared with known reference values to determine the errors induced by methanol and ethanol contamination. In addition, the 17 O-excess contamination detection approach was tested. This is a post-processing detection tool for both liquid and vapour IRIS triple-isotope analyses, utilizing calculated 17 O-excess values to flag contaminated samples. Organic contamination induced significant errors in IRIS results, not seen in IRMS results. Methanol caused larger errors than ethanol. Results from vapour-IRIS analyses had larger errors than those from liquid-IRIS analyses. The 17 O-excess approach identified methanol driven error in liquid- and vapour-mode IRIS samples at levels where isotope results became unacceptably erroneous. For ethanol contaminated samples, a mix of erroneous and correct flagging occurred with the 17 O-excess method. Here our results indicate that methanol is the more problematic contaminant for data corruption. The 17 O-excess method was therefore useful for data quality control. Organic contamination caused significant errors in IRIS stable isotope results. These errors were larger during vapour analyses than during liquid IRIS analyses, and larger for methanol than ethanol contamination. The 17 O-excess method is highly sensitive for detecting narrowband (methanol) contamination error in vapour and liquid analysis modes in IRIS.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1971

Digital correction of geometric and radiometric errors in ERTS data.

The sensor systems of the ERTS-A satellite are discussed and sources of geometric and radiometric errors in the received images are identified. Digital algorithms are presented for detection of reseau and ground control points, for rapid implementation of geometric corrections, and for radiometric correction of errors caused by shading, image motion, modulation transfer function, and quantum and systematic noise.

Bakis, R.↗
DOE OSTI2021

Preliminary Evidence of Gas-Phase Water Splitting on Holmium Nitrogen Oxide Clusters

Preliminary Evidence of Gas-Phase Water Splitting on Holmium Nitrogen Oxide Clusters Christopher A. Zarzana1, Makayla R. Baxter , Introduction: Molecular hydrogen is a potential energy carrier that could be used to help implement a clean energy economy if it is generated from splitting of water. Improvements in the efficiencies of water-splitting electrolyzers relies on development of novel materials with enhanced performance. However, research in this area is slowed due to underdeveloped understanding of the mechanisms of device performance due to challenges interrogating the fundamental chemical reactions at play in bulk materials. Studies of the intrinsic reactivity of clusters that are representative of the reactive sites of these materials can increase understanding of the fundamental reaction mechanisms involved in hydrogen production, allowing for more efficient development of new water-splitting materials. Methods: Holmium tetranitrato ([Ho(NO3)4]-) clusters were generated in gas-phase using the electrospray ionization source of a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer. Spray solutions consisted of aqueous holmium (Ho) nitrate solutions (at nominally 3 mM) diluted to 30 µM in acetonitrile. The holmium (Ho) tetranitrato clusters were isolated using the quadrupole and were subsequently activated and allowed to react with background water in the collision cell. High resolution, high mass accuracy spectra were recorded using the time-of-flight. Mass accuracy was ensured using external calibration with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Preliminary data: Collisional activation of the holmium tetranitrato complexes ([Ln(NO3)4]-) resulted in an expected series of ions resulting from the loss of ·NO and ·NO2. This included an ion at m/z = 382.885 assigned as [HoO2(NO3)3]- (theoretical m/z=382.884, error=-1.2 ppm), resulting from loss of ·NO, and an ion at m/z=366.890 assigned as [HoO(NO3)3]- (theorical m/z=366.889, error=-1.8 ppm), resulting from loss of ·NO2. Additional ions were detected that would result from more complicated losses from [Ho(NO3)4]-, including ions at m/z=320.898 assigned as [HoO2(NO3)2]- (theoretical m/z=320.896, error=-4.9 ppm), at m/z=304.904 assigned as [HoO(NO3)2]- (theoretical m/z=304.901, error=-8.1 ppm, very low signal), and at m/z=288.908 assigned as [Ho(NO3)2]- (theoretical m/z=288.907, error=-3.4 ppm). This ion series would arise from loss of some combination of ·NO, ·NO2, and ·NO3, although it is not known whether these losses occur sequentially (e.g. loss of ·NO and ·NO3 to yield [HoO2(NO3)2]-) or as a single species (e.g. direct loss of N2O4). These ions were accompanied by a complementary series representing addition of a single water molecule. This included an ion at m/z=338.908 assigned as [HoO2(NO3)2H2O]- (theoretical m/z=338.907, error=-4.1 ppm), an ion at m/z=322.912 assigned as [HoO(NO3)2H2O]- (theoretical m/z=322.912, error=1.2 ppm), and an ion at m/z=306.918 assigned as [Ho(NO3)2H2O]-, (theoretical m/z=306.918, error=-3.7 ppm). An additional hydrated ion was observed at m/z=276.921 assigned as [HoO2(NO3) H2O]- (theoretical m/z=276.919, error=-7.3 ppm), although corresponding dehydrated ion was not observed. An additional ion was observed at m/z=367.898 that has been assigned as [Ho(NO3)3OH]- (theoretical m/z=367.897, error=-2.5 ppm). It is hypothesized that this ion arises from addition of water to [Ho(NO3)3]- followed by elimination of a hydrogen radical. Neither [Ho(NO3)3]- nor [Ho(NO3)3H2O]- were detected, suggesting that, if the hypothesis is correct, addition of water to [Ho(NO3)3]- and its subsequent splitting is rapid. Elimination of HNO3 from [Ho(NO3)4H2O]- could also yield [Ho(NO3)3OH]-; however, no [Ho(NO3)4H2O]- ions were observed. Novelty: Potential evidence of water splitting on gas-phase lanthanide clusters offers a way to study the intrinsic reactivity of hydrogen-generation materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

The Swift BAT Perspective on Non-Thermal Emission in HIFLUGCS Galaxy Clusters

The search for diffuse non-thermal, inverse Compton (IC) emission from galaxy clusters at hard X-ray energies has been underway for many years, with most detections being either of low significance or controversial. Until recently, comprehensive surveys of hard X-ray emission from clusters were not possible; instead, individually proposed-for. long observations would be collated from the archive. With the advent of the Swift BAT all sky survey, any c1u,;ter's emission above 14 keV can be probed with nearly uniform sensitivity. which is comparable to that of RXTE, Beppo-SAX, and Suzaku with the 58-month version of the survey. In this work. we search for non-thermal excess emission above the exponentially decreasing, high energy thermal emission in the flux-limited HIFLUGCS sample. The BAT emission from many of the detected clusters is marginally extended; we are able to extract the total flux for these clusters using fiducial models for their spatial extent. To account for thermal emission at BAT energies, XMM-Newton EPIC spectra are extracted from coincident spatial regions so that both the thermal and non-thermal spectral components can be determined simultaneou,;ly in joint fits. We find marginally significant IC components in 6 clusters, though after closer inspection and consideration of systematic errors we are unable to claim a clear detection in any of them. The spectra of all clusters are also summed to enhance a cumulative non-thermal signal not quite detectable in individual clusters. After constructing a model based on single temperature

Wik, Daniel R.↗
NASA NTRS2000

Multimodality Instrument for Tissue Characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip is discussed. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network, program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration.

Mah, Robert W.↗
NASA NTRS2004

Multimodality instrument for tissue characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration. The use of this system will make surgical procedures safer, more accurate, and more efficient. Other applications of this system include the detection, prognosis and treatment of breast cancer, prostate cancer, spinal diseases, and use in general exploratory surgery.

Mah, Robert W.↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
NASA NTRS2012

The Atacama Cosmology Telescope: A Measurement of the Thermal Sunyaev-Zel'dovich Effect Using the Skewness of the CMB Temperature Distribution

We present a detection of the unnormalized skewness (T(sup ~)(sup 2)(n(circumflex)) induced by the thermal Sunyaev-Zel'dovich (tSZ) effect in filtered Atacama Cosmology Telescope (ACT) 148 GHz cosmic microwave background temperature maps. Contamination due to infrared and radio sources is minimized by template subtraction of resolved sources and by constructing a mask using outlying values in the 218 GHz (tSZ-null) ACT maps. We measure (T(sup ~)(sup 3) (n(circumflex)) = -31 plus or minus 6 micro-K(sup 3) (measurement error only) or plus or minus 14 micro-K(sup 3) (including cosmic variance error) in the filtered ACT data, a 5sigma detection. We show that the skewness is a sensitive probe of sigma(sub 8), and use analytic calculations and tSZ simulations to obtain cosmological constraints from this measurement. From this signal alone we infer a value of sigma(sub 8) = 0.78 sup +0.03 sub -0.04 (68% C.L.) sup +0.05 sub -0.16. Our results demonstrate that measurements of nonGaussianity can be a useful method for characterizing the tSZ effect and extracting the underlying cosmological information.

Wilson, Michael J.↗
NASA NTRS2005

The Terrestrial Planet Finder coronagraph dynamics error budget

The Terrestrial Planet Finder Coronagraph (TPF-C) demands extreme wave front control and stability to achieve its goal of detecting earth-like planets around nearby stars. We describe the performance models and error budget used to evaluate image plane contrast and derive engineering requirements for this challenging optical system.

coronagraph↗
NASA NTRS1983

Study of an automatic trajectory following control system

It is shown that the estimator part of the Modified Partitioned Adaptive Controller, (MPAC) developed for nonlinear aircraft dynamics of a small jet transport can adapt to sensor failures. In addition, an investigation is made into the potential usefulness of the configuration detection technique used in the MPAC and the failure detection filter is developed that determines how a noise plant output is associated with a line or plane characteristic of a failure. It is shown by computer simulation that the estimator part and the configuration detection part of the MPAC can readily adapt to actuator and sensor failures and that the failure detection filter technique cannot detect actuator or sensor failures accurately for this type of system because of the plant modeling errors. In addition, it is shown that the decision technique, developed for the failure detection filter, can accurately determine that the plant output is related to the characteristic line or plane in the presence of sensor noise.

Vanlandingham, H. F.↗
NASA NTRS2004

Nulling interferometers: the importance of systematic errors and the X-Array configuration

The nulling interferometers proposed for planet detection are arrays of collector telescopes whose amplitudes and phases are carefully controlled to generate a null response at the star. Perturbations in the amplitude and phase response of the instrument lead to time-dependent fluctuations in the stellar leakage that can mimic a planet signal. Understanding these non-linear systematic errors is important, since they drive most of the instrument requirements for missions such as the Terrestrial Planet Finder and Darwin. We show that 'amplitude-phase' errors are the dominant source of instrument noise. They are unaffected by the technique of phase chopping, increase rapidly at short wavelengths, are largely independent of the size and transmission efficiency of the collector optics, and depend only weakly on the nulling configuration and distance to the target system. Detection of an Earth around a G-type star like the sun requires -1.5 nm of path control and -0.1% control of the amplitude, integrated over all frequencies, including DC. This paper also introduces the X-Array - a new nulling configuration with 4 collectors and a central combiner arranged in an X pattern. This has a number of advantages over the standard dual Bracewell layout, and over other configurations that have been proposed

Dubovitsky, Serge↗
DOE OSTI2026

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗
DOE OSTI2022

Application of Frequency Division Multiplexing and Neural Networks in the Operation and Diagnosis of the Stator Current and Shaft Position Sensors Used in Electric/Hybrid Vehicles

Fast, precise and robust sensing of currents and motor shaft angle is essential for the excellent performance of electric and hybrid vehicles (EV/HEV). Multiplexing techniques are commonly applied in data acquisition systems (DAQs) to digitize the signals sensed in EV/HEV drives. Frequency-division multiplexing (FDM) applied to get the signals from current sensors and resolver angular position sensor has advantages over conventional multiplexing approaches. However, problems such as aging and mechanical imperfections distort the outputs of those sensors, producing measurement errors of the angular position and currents. Conventional techniques designed to compensate for those errors cannot be applied in signals multiplexed in frequency. This paper proposes online techniques to detect and compensate for the distortions in the resolver sensor and current sensors. The demultiplexing process was adjusted to allow distortion detection and compensation. An auto-associative neural network (ANN) compensates for the current measurement error, while an energy-based technique is applied to compensate for the distortions in the resolver outputs. The obtained results show that the distortions were compensated, allowing a more accurate estimation of stator currents and angular position when FDM is applied in EV/HEV DAQs.

Pereira Pinto, Joao↗
DOE OSTI2025

Accelerating Discovery of Atomistic Defects via Machine Learning

The quantification of defects such as vacancies in crystalline structures is a cornerstone of materials science research. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within a crystalline lattice, aiming to expedite detection while improving accuracy. Additionally, we explore the transferability of these ML techniques, identifying characteristics of atomistic imaging data that complicate this task. We show how the integration of ML can drive innovation, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗
DOE OSTI2021

Bit error protection in cache memories

A computing device having a cache memory that is configured in a write-back mode is described. A cache controller in the cache memory acquires, from a record of bit errors that are present in each of a plurality of portions of the cache memory, a number of bit errors in a portion of the cache memory. The cache controller detects a coherency state of data stored in the portion of the cache memory. Based on the coherency state and the number of bit errors, the cache controller selects an error protection from among a plurality of error protections. The cache controller uses the selected error protection to protect the data stored in the portion of the cache memory from errors.

Kalamatianos, John↗