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At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

DOE OSTI2017

Analysis and improvement of input channel selection algorithm for reliability of control systems in nuclear power plants - 138

In most of non-safety NSSS (Nuclear Steam Supply System) control systems, a process input is composed of two channels for redundancy. In a normal situation, the average of both input channels is used in the control algorithm. If a failed channel is detected, the 'channel selection algorithm' chooses the remaining normal input channel. For a bumpless transition, many implemented control systems include the 'ramping rate' function, which makes it possible for the selected input to slowly approach the new input channel. However, it recently turned out that this function adopted for positive effects may result in unintended consequences for the related control system and the plant in certain cases. Due to a process transient in the plant according to a significant event, any related sensor input signal can rapidly change and finally exceed the pre-defined range for detecting an out-of-range event in a short time. During the process of channel conversion due to a rapid transient in the plant, the processed input from the redundant channels can be distorted if the ramping rate function is not properly implemented. As a result, it can result in a plant shutdown because the control system fails to perform the critical function to mitigate a plant transient. To solve these potential problems, we analyzed the overall causes and derived a proposed algorithm for improving reliability and performance of the control systems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2012

Explanatory Supplement to the WISE All-Sky Release Products

The Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010) surveyed the entire sky at 3.4, 4.6, 12 and 22 microns in 2010, achieving 5-sigma point source sensitivities per band better than 0.08, 0.11, 1 and 6 mJy in unconfused regions on the ecliptic. The WISE All-Sky Data Release, conducted on March 14, 2012, incorporates all data taken during the full cryogenic mission phase, 7 January 2010 to 6 August 20l0,that were processed with improved calibrations and reduction algorithms. Release data products include: (1) an Atlas of 18,240 match-filtered, calibrated and coadded image sets; (2) a Source Catalog containing positions and four-band photometry for over 563 million objects, and (3) an Explanatory Supplement. Ancillary products include a Reject Table that contains 284 million detections that were not selected for the Source Catalog because they are low signal-to-noise ratio or spurious detections of image artifacts, an archive of over 1.5 million sets of calibrated WISE Single-exposure images, and a database of 9.4 billion source extractions from those single images, and moving object tracklets identified by the NEOWISE program (Mainzer et aI. 2011). The WISE All-Sky Data Release products supersede those from the WISE Preliminary Data Release (Cutri et al. 2011). The Explanatory Supplement to the WISE All-Sky Data Release Products is a general guide for users of the WISE data. The Supplement contains an overview of the WISE mission, facilities, and operations, a detailed description of WISE data processing algorithms, a guide to the content and formals of the image and tabular data products, and cautionary notes that describe known limitations of the All-Sky Release products. Instructions for accessing the WISE data products via the services of the NASA/IPAC Infrared Science Archive are provided. The Supplement also provides analyses of the achieved sky coverage, photometric and astrometric characteristics and completeness and reliability of the All-Sky Release data products. The WISE All-Sky Release Explanatory Supplement is an on-line document that is updated frequently to provide the most current information for users of the WISE data products. The Explanatory Supplement is maintained at: http://wise2.ipac.caltech.edu/docs/release/allsky/expsup/index.html WISE is a joint project of the University of California, Los Angeles and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. NEOWISE is a project of the Jet Propulsion Laboratory/California Institute of Technology, funded by the Planetary Science Division of the National Aeronautics and Space Administration.

Source record↗

DOE OSTI2016

Development of an Ion Mobility Spectrometry-Orbitrap Mass Spectrometer Platform

Complex samples benefit from multidimensional measurements where higher resolution enables more complete characterization of biological and environmental systems. To address this challenge, we developed a drift tube-based ion mobility spectrometry-Orbitrap mass spectrometer (IMS-Orbitrap MS) platform. To circumvent the time scale disparity between the fast IMS separation and the much slower Orbitrap MS acquisition, we utilized a dual gate and pseudorandom sequences to multiplexed injection of ions and allowing operation in signal averaging (SA), single multiplexing (SM) and double multiplexing (DM) IMS modes to optimize the signal-to-noise ratio of the measurements. For the SM measurements, a previously developed algorithm was used to reconstruct the IMS data. A new algorithm was developed for the DM analyses involving a two-step process that first recovers the SM data and then decodes the SM data. The algorithm also performs multiple refining procedures in order to minimize demultiplexing artifacts. The new IMS-Orbitrap MS platform was demonstrated by the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution proved essential for accurate assignment of molecular formulae.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Problematic projection to the in-sample subspace for a kernelized anomaly detector

We examine the properties and performance of kernelized anomaly detectors, with an emphasis on the Mahalanobis-distance-based kernel RX (KRX) algorithm. Although the detector generally performs well for high-bandwidth Gaussian kernels, it exhibits problematic (in some cases, catastrophic) performance for distances that are large compared to the bandwidth. By comparing KRX to two other anomaly detectors, we can trace the problem to a projection in feature space, which arises when a pseudoinverse is used on the covariance matrix in that feature space. Here, we show that a regularized variant of KRX overcomes this difficulty and achieves superior performance over a wide range of bandwidths.

58 GEOSCIENCES↗

DOE OSTI2020

Anomaly Detection and Mitigation for Wide-Area Damping Control using Machine Learning

In an interconnected multi-area power system, wide-area measurement based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power flows below to their transmission capacity. The effect of wide-area damping control (WADC) significantly depends on both power and cyber systems. At the cyber system layer, an adversary can inflict the WADC process by compromising either measurement signals, control signals or both. Stealthy and coordinated cyber-attacks may bypass the conventional cybersecurity measures to disrupt the seamless operation of WADC. This paper proposes an anomaly detection (AD) algorithm using supervised Machine Learning and a model-based logic for mitigation. The proposed AD algorithm considers measurement signals (input of WADC) and control signals (output of WADC) as input to evaluate the type of activity such as normal, perturbation (small or large signal faults), attack and perturbation-and-attack. Upon anomaly detection, the mitigation module tunes the WADC signal and sets the control status mode as either wide-area mode or local mode. The proposed anomaly detection and mitigation (ADM) module works inline with the WADC at the control center for attack detection on both measurement and control signals and eliminates the need for ADMs at the geographically distributed actuators. Here, we consider coordinated and primitive data-integrity attack vectors such as pulse, ramp, relay-trip and replay attacks. The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for 2-area 4-machine power system. The ADM module shows effective performance with 96:5% accuracy to detect anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Monitoring and Control of Chemical Composition of InGaN Layers During MOCVD

This Department of Energy SBIR Phase II grant targets the inefficiency of the epitaxial processes used to deposit wide band-gap semiconductor thin films that are an essential part of the next generation high-brightness LEDs for solid state lighting. Non-uniformity of the layers over a single wafer and non-repeatability over the wafers in a single batch, separate batches and separate reactors are some of the primary source of reduced manufacturing yield. The team performed extensive research, development and validation of an in-situ spectroscopic optical monitoring and epitaxial process control system. The system monitors the LED thin films as they grow on the individual wafers inside the epitaxial reactor, records the signal in a broad spectral range and processes the information to retrieve essential film quality parameters and their variation over a single wafer, all the wafers in a batch and multiple batches. A novel software algorithm is implemented, which performs real-time spectral pattern recognition and displays any abnormalities or differences in the deposition, which is used by the engineer to optimize the epitaxial process. The project resulted in the optimization of the LED film growth and improvement of its uniformity and repeatability, reducing the cost of the final LED devices.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Modular VLSI Reed-Solomon Decoder

Proposed Reed-Solomon (RS) decoder assembled from very-large-scale integrated-circuit (VLSI) building blocks. Decoder exploits recursive forms in RS decoding algorithms. RS codes capable of correcting random or burst errors in telemetry and other data-communication signals. Because of small size and low power consumption, advantageous to employ several such decoders in parallel-processing scheme to increase decoding speed.

Liu, K. Y.↗

NASA NTRS1999

Design Description of the X-33 Avionics Architecture

In this paper, we provide a design description of the X-33 avionics architecture. The X-33 is an autonomous Single Stage to Orbit (SSTO) launch vehicle currently being developed by Lockheed Martin for NASA as a technology demonstrator for the VentureStar Reusable Launch Vehicle (RLV). The X-33 avionics provides autonomous control of die vehicle throughout takeoff, ascent, descent, approach, landing, rollout, and vehicle safing. During flight the avionics provides communication to the range through uplinked commands and downlinked telemetry. During pre-launch and post-safing activities, the avionics provides interfaces to ground support consoles that perform vehicle flight preparations and maintenance. The X-33 Avionics is a hybrid of centralized and distributed processing elements connected by three dual redundant Mil-Std 1553 data buses. These data buses are controlled by a central processing suite located in the avionics bay and composed of triplex redundant Vehicle Mission Computers (VMCs). The VMCs integrate mission management, guidance, navigation, flight control, subsystem control and redundancy management functions. The vehicle sensors, effectors and subsystems are interfaced directly to the centralized VMCs as remote terminals or through dual redundant Data Interface Units (DIUs). The DIUs are located forward and aft of the avionics bay and provide signal conditioning, health monitoring, low level subsystem control and data interface functions. Each VMC is connected to all three redundant 1553 data buses for monitoring and provides a complete identical data set to the processing algorithms. This enables bus faults to be detected and reconfigured through a voted bus control configuration. Data is also shared between VMCs though a cross channel data link that is implemented in hardware and controlled by AlliedSignal's Fault Tolerant Executive (FTE). The FTE synchronizes processors within the VMC and synchronizes redundant VMCs to each other. The FTE provides an output-voting plane to detect, isolate and contain faults due to internal hardware or software faults and reconfigures the VMCs to accommodate these faults. Critical data in the 1553 messages are scheduled and synchronized to specific processing frames in order to minimize data latency. In order to achieve an open architecture, military and commercial off-the-shelf equipment is incorporated using common processors, standard VME backplanes and chassis, the VxWorks operating system, and MartixX for automatic code generation. The use of off-the-shelf tools and equipment helps reduce development time and enables software reuse. The open architecture allows for technology insertion, while the distributed modular elements allow for expansion to increased redundancy levels to meet the higher reliability goals of future RLVs.

Reichenfeld, Curtis J.↗

NASA NTRSDate not supplied

Artemis I Liftoff Measurements Issues and Corrections

The SLS rocket was instrumented to collect liftoff environment data during Artemis I launch. The instruments were microphones and pressure transducers. Most data were acceptable for analysis, but required corrections for port resonance, mean signal drift, data system delays, and data spikes. The data were all transmitted via telemetry and in this process some of the measurements experienced unexpectedly long gaps in the data stream. A time validated reconstruction algorithm failed when encountering the long gaps and required use of data from a simpler reconstruction process, with manually inserted data delay corrections. This paper discusses the issues and the corrections that were necessary for the launch data to determine the true physics of the acoustics occurring during launch.

environments↗

NASA NTRSDate not supplied

Artemis I Liftoff Measurements Issues and Corrections

environments↗

DOE OSTI2022

Deploying a Model Predictive Traffic Signal Control Algorithm - A Field Deployment Experiment Case Study: Preprint

This paper presents a field deployment experiment of a real-time traffic signal control algorithm. We implemented the Model Predictive Control (MPC) algorithm based on Virtual Phase-Link (VPL) model. We selected the deployment locations and times based on an energy saving potential concept. We developed a set of experiment systems to enable the deployment including sensing, processing, and actuating components. We tested the systems rigorously before the experiment days. We reported the key procedures on the experiment days including the steps took, real-time control procedure, and the monitoring of the experiment. We evaluated the impact of the deployment with the changes in delay and energy consumption.

deployment↗

NASA NTRS2010

Real-Time On-Board Processing Validation of MSPI Ground Camera Images

The Earth Sciences Decadal Survey identifies a multiangle, multispectral, high-accuracy polarization imager as one requirement for the Aerosol-Cloud-Ecosystem (ACE) mission. JPL has been developing a Multiangle SpectroPolarimetric Imager (MSPI) as a candidate to fill this need. A key technology development needed for MSPI is on-board signal processing to calculate polarimetry data as imaged by each of the 9 cameras forming the instrument. With funding from NASA's Advanced Information Systems Technology (AIST) Program, JPL is solving the real-time data processing requirements to demonstrate, for the first time, how signal data at 95 Mbytes/sec over 16-channels for each of the 9 multiangle cameras in the spaceborne instrument can be reduced on-board to 0.45 Mbytes/sec. This will produce the intensity and polarization data needed to characterize aerosol and cloud microphysical properties. Using the Xilinx Virtex-5 FPGA including PowerPC440 processors we have implemented a least squares fitting algorithm that extracts intensity and polarimetric parameters in real-time, thereby substantially reducing the image data volume for spacecraft downlink without loss of science information.

Earth Sciences Decadal Survey↗

NASA NTRS1999

Signal Prediction With Input Identification

A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.

Juang, Jer-Nan↗

DOE OSTI2025

Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform

Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.

42 ENGINEERING↗

DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗

DOE OSTI2015

$xy$ Position Reconstruction in DarkSide-50

The DarkSide-50 experiment seeks to directly detect dark matter in a liquid argon time projection chamber. In this dissertation, I present an algorithm of my design that determines the position of particle interactions with the liquid argon. This position reconstruction algorithm will be used by DarkSide-50 to reject backgrounds, particularly backgrounds from radioactive elements on the detector surface. The position reconstruction algorithm functions by constructing light response functions (LRFs) that map locations in the detector to the expected distribution of signal in DarkSide-50's 38 photomultiplier tubes. Accurate LRFs cannot be produced by simulations of DarkSide-50's optics because such simulations are known to be awed. Instead, this algorithm constructs LRFs using an iterative process driven by data. Initial, awed LRFs are produced using simulated events but then used to produce new LRFs from data events. Multiple generations of LRFs are created from data with each generation driven to better satisfy a known feature of the detector: the dominant argon-39 background is uniformly distributed. I also discuss a method of discriminating against surface background as an alternative to the common approach of ducialization. This method considers the di erence in goodnessof- t between the best- t reconstructed position and the best- t position at the detector's surface. I conclude by presenting results on the performance and validity of this algorithm, including some discussion of reconstruction errors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1977

Design of redundant systems

Algorithmic approach is useful for analysis of systems with noisy inputs and when outputs are required in terms of statistical quantities and probabilities of signal excursions beyond desired levels. Procedure can be used with circuits, chemical processes, material design, and other systems with known transfer functions and parameter tolerances.

Doty, L. F.↗