SEARCH · Search NASA

Results for “soft errors”

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.

SourceResearch connectionFrom yearThrough year

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

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Feasibility of MRI-only treatment planning for proton therapy in brain and prostate cancers: Dose calculation accuracy in substitute CT images

Purpose: Magnetic resonance imaging (MRI) is increasingly used for radiotherapy target delineation, image guidance, and treatment response monitoring. Recent studies have shown that an entire external x-ray radiotherapy treatment planning (RTP) workflow for brain tumor or prostate cancer patients based only on MRI reference images is feasible. This study aims to show that a MRI-only based RTP workflow is also feasible for proton beam therapy plans generated in MRI-based substitute computed tomography (sCT) images of the head and the pelvis. Methods: The sCTs were constructed for ten prostate cancer and ten brain tumor patients primarily by transforming the intensity values of in-phase MR images to Hounsfield units (HUs) with a dual model HU conversion technique to enable heterogeneous tissue representation. HU conversion models for the pelvis were adopted from previous studies, further extended in this study also for head MRI by generating anatomical site-specific conversion models (a new training data set of ten other brain patients). This study also evaluated two other types of simplified sCT: dual bulk density (for bone and water) and homogeneous (water only). For every clinical case, intensity modulated proton therapy (IMPT) plans robustly optimized in standard planning CTs were calculated in sCT for evaluation, and vice versa. Overall dose agreement was evaluated using dose–volume histogram parameters and 3D gamma criteria. Results: In heterogeneous sCTs, the mean absolute errors in HUs were 34 (soft tissues: 13, bones: 92) and 42 (soft tissues: 9, bones: 97) in the head and in the pelvis, respectively. The maximum absolute dose differences relative to CT in the brain tumor clinical target volume (CTV) were 1.4% for heterogeneous sCT, 1.8% for dual bulk sCT, and 8.9% for homogenous sCT. The corresponding maximum differences in the prostate CTV were 0.6%, 1.2%, and 3.6%, respectively. The percentages of dose points in the head and pelvis passing 1% and 1 mm gamma index criteria were over 91%, 85%, and 38% with heterogeneous, dual bulk, and homogeneous sCTs, respectively. There were no significant changes to gamma index pass rates for IMPT plans first optimized in CT and then calculated in heterogeneous sCT versus IMPT plans first optimized in heterogeneous sCT and then calculated on standard CT. Conclusions: This study demonstrates that proton therapy dose calculations on heterogeneous sCTs are in good agreement with plans generated with standard planning CT. An MRI-only based RTP workflow is feasible in IMPT for brain tumors and prostate cancers.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1991

Explosive Transient Camera (ETC) Program

Since the inception of the ETC program, a wide range of new technologies was developed to support this astronomical instrument. The prototype unit was installed at ETC Site 1. The first partially automated observations were made and some major renovations were later added to the ETC hardware. The ETC was outfitted with new thermoelectrically-cooled CCD cameras and a sophisticated vacuum manifold, which, together, made the ETC a much more reliable unit than the prototype. The ETC instrumentation and building were placed under full computer control, allowing the ETC to operate as an automated, autonomous instrument with virtually no human intervention necessary. The first fully-automated operation of the ETC was performed, during which the ETC monitored the error region of the repeating soft gamma-ray burster SGR 1806-21.

Ricker, George↗

NASA NTRS1999

Low Density Parity Check Codes Based on Finite Geometries: A Rediscovery and More

Low density parity check (LDPC) codes with iterative decoding based on belief propagation achieve astonishing error performance close to Shannon limit. No algebraic or geometric method for constructing these codes has been reported and they are largely generated by computer search. As a result, encoding of long LDPC codes is in general very complex. This paper presents two classes of high rate LDPC codes whose constructions are based on finite Euclidean and projective geometries, respectively. These classes of codes a.re cyclic and have good constraint parameters and minimum distances. Cyclic structure adows the use of linear feedback shift registers for encoding. These finite geometry LDPC codes achieve very good error performance with either soft-decision iterative decoding based on belief propagation or Gallager's hard-decision bit flipping algorithm. These codes can be punctured or extended to obtain other good LDPC codes. A generalization of these codes is also presented.

Kou, Yu↗

NASA NTRS2011

The Gravity and Extreme Magnetism Small Explorer (GEMS)

The Gravity and Extreme Magnetism Small Explorer (GEMS) was selected by NASA for flight in 2014 to make a sensitive search for X-ray polarization from a wide set of source classes, including stellar black holes, Seyfert galaxies and quasars, blazars, rotation and accretion-powered pulsars, magnetars, shell supernova remnants and pulsar wind nebulae. Among the primary scientific objectives are determining the effects of the spin of black holes and the geometry of supermassive black hole accretion, determining the configurations of the magnetic fields and the X-ray emission of magnetars, and determining the magnetic structure of the supernova shocks in which cosmic rays are accelerated. GEMS will observe 23 targets during a 16 month prime mission, in observations that will be able to reach predicted levels of polarization. The mission can be extended to provide a guest observer phase. The GEMS instrument has time projection chamber polarimeters with high 2-10 keV efficiency at the focus of thin foil mirrors. The 4.5 m focal length mirrors will be deployed on an extended boom. The spacecraft with the instrument is rotated with a period of about 10 minutes to enable measurement and correction of systematic errors. A small Bragg reflection soft X-ray experiment takes advantage of this rotation to obtain a measurement at 0.5 keV. The design of the GEMS instrument and the mission, the expected performance and the planned science program will be discussed.

Kallman, T. R.↗

NASA NTRS1983

The impact of mismatch on the performance of coded narrow-band FM with limiter/discriminator detection

An examination of the impact of mismatch on the performance of convolutionally encoded/Viterbi decoded narrow-band FM with limiter/discriminator detection is presented. Attention was given to the potential gain available by the combination of this type of system in terms of hard and soft decision decoding. Soft decision decoding was demonstrated to offer only approximately 0.3 dB better performance than hard decision coding. It was also shown, through a technique involving the number of clicks occurring in each detection interval, that both soft and hard decision decoding bit error probability performance could be improved. It is concluded that the mismatch between the coding channel and the decoding metric of the Viterbi algorithm is responsible for reducing the difference between hard and soft decoding metrics.

Simon, M. K.↗

NASA NTRS2013

Closed-Loop Analysis of Soft Decisions for Serial Links

We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

Lansdowne, Chatwin A.↗

NASA NTRS2013

Soft Decision Analyzer

Lansdowne, Chatwin↗

DOE OSTI2017

Accuracy of first-principles interatomic interactions and predictions of ferroelectric phase transitions in perovskite oxides: Energy functional and effective Hamiltonian

While first-principles density functional theory (DFT)-based models have been effective in capturing the physics of ferroelectric phase transitions in BaTiO 3 , PbTiO 3 , and KNbO 3 , quantitative estimates of the transition temperatures (T C ) have errors that are believed to originate from the errors in estimating lattice constants obtained within the local density approximation (LDA) and generalized gradient approximation (GGA) of DFT. The recently developed strongly constrained and appropriately normed (SCAN) meta-GGA functional has been shown to be quite accurate in the estimation of lattice constants. Here, we present a quantitative analysis of the estimates of ferroelectric ground-state properties of eight perovskite oxides and transition temperatures of BaTiO 3 , PbTiO 3 , and KNbO 3 obtained with molecular dynamics simulations using an effective Hamiltonian derived from the SCAN meta-GGA-based DFT. Relative to LDA, we find an improvement in the estimates of T C , which arises from the changes in the calculated strain-phonon, anharmonic coupling constants, and strength of ferroelectric instabilities, i.e., frequencies of the soft modes. We also assess the errors in T C originating from approximately integrating out the high-energy phonons during construction of the model Hamiltonian through estimates of the effects of fourth-order couplings between the soft mode and higher-energy modes of BaTiO 3 , PbTiO 3 , and KNbO 3 . We find that inclusion of these anharmonic couplings results in deeper double-well energy functions of ferroelectric distortions and further improvement in the estimates of transition temperatures. Consistently improved estimates of lattice constants and transition temperatures with the SCAN meta-GGA calculations augur well for their use in simulations of superlattices or heterostructures of perovskite oxides, in which the effects of lattice matching are critical.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Soft syndrome iterative decoding of quantum LDPC codes and hardware architectures

In practical quantum error correction implementations, the measurement of syndrome information is an unreliable step—typically modeled as a binary measurement outcome flipped with some probability. However, the measured syndrome is in fact a discretized value of the continuous voltage or current values obtained in the physical implementation of the syndrome extraction. In this paper, we use this “soft” or analog information to benefit iterative decoders for decoding quantum low-density parity-check (QLDPC) codes. Syndrome-based iterative belief propagation decoders are modified to utilize the soft syndrome to correct both data and syndrome errors simultaneously. We demonstrate the advantages of the proposed scheme not only in terms of comparison of thresholds and logical error rates for quasi-cyclic lifted-product QLDPC code families but also with faster convergence of iterative decoders. Additionally, we derive hardware (FPGA) architectures of these soft syndrome decoders and obtain similar performance in terms of error correction to the ideal models even with reduced precision in the soft information. The total latency of the hardware architectures is about 600 ns (for the QLDPC codes considered) in a 20 nm CMOS process FPGA device, and the area overhead is almost constant—less than 50% compared to min-sum decoders with noisy syndromes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1980

Voltage controller/current limiter for ac

Circuit protects ac power systems for overload failures, limits power surge and short-circuit currents to 150 percent of steady state level, regulates ac output voltage, and soft starts loads. Limiter generates dc error signal in response to line fluctuations and dumps power when overload is reached. Device is inserted between ac source and load.

Wu, T. T.↗

NASA NTRS1998

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes: The Map and Related Decoding Algirithms - Part 3

In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.

Lin, Shu↗

NASA NTRS1998

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed.

Lin, Shu↗

DOE OSTI2022

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

Sabelhaus, Andrew P.↗

NASA NTRS1995

Hologic QDR 2000 whole-body scans: a comparison of three combinations of scan modes and analysis software

This study reports on the short-term in vivo precision and absolute measurements of three combinations of whole-body scan modes and analysis software using a Hologic QDR 2000 dual-energy X-ray densitometer. A group of 21 normal, healthy volunteers (11 male and 10 female) were scanned six times, receiving one pencil-beam and one array whole-body scan on three occasions approximately 1 week apart. The following combinations of scan modes and analysis software were used: pencil-beam scans analyzed with Hologic's standard whole-body software (PB scans); the same pencil-beam analyzed with Hologic's newer "enhanced" software (EPB scans); and array scans analyzed with the enhanced software (EA scans). Precision values (% coefficient of variation, %CV) were calculated for whole-body and regional bone mineral content (BMC), bone mineral density (BMD), fat mass, lean mass, %fat and total mass. In general, there was no significant difference among the three scan types with respect to short-term precision of BMD and only slight differences in the precision of BMC. Precision of BMC and BMD for all three scan types was excellent: < 1% CV for whole-body values, with most regional values in the 1%-2% range. Pencil-beam scans demonstrated significantly better soft tissue precision than did array scans. Precision errors for whole-body lean mass were: 0.9% (PB), 1.1% (EPB) and 1.9% (EA). Precision errors for whole-body fat mass were: 1.7% (PB), 2.4% (EPB) and 5.6% (EA). EPB precision errors were slightly higher than PB precision errors for lean, fat and %fat measurements of all regions except the head, although these differences were significant only for the fat and % fat of the arms and legs. In addition EPB precision values exhibited greater individual variability than PB precision values. Finally, absolute values of bone and soft tissue were compared among the three combinations of scan and analysis modes. BMC, BMD, fat mass, %fat and lean mass were significantly different between PB scans and either of the EPB or EA scans. Differences were as large as 20%-25% for certain regional fat and BMD measurements. Additional work may be needed to examine the relative accuracy of the scan mode/software combinations and to identify reasons for the differences in soft tissue precision with the array whole-body scan mode.

NASA Discipline Musculoskeletal↗

DOE OSTI2021

Encoder–decoder neural network for solving the nonlinear Fokker–Planck–Landau collision operator in XGC

An encoder–decoder neural network has been used to examine the possibility for acceleration of a partial integro-differential equation, the Fokker–Planck–Landau collision operator. This is part of the governing equation in the massively parallel particle-in-cell code XGC, which is used to study turbulence in fusion energy devices. The neural network emphasizes physics-inspired learning, where it is taught to respect physical conservation constraints of the collision operator by including them in the training loss, along with the ℓ 2 loss. In particular, network architectures used for the computer vision task of semantic segmentation have been used for training. A penalization method is used to enforce the ‘soft’ constraints of the system and integrate error in the conservation properties into the loss function. During training, quantities representing the particle density, momentum and energy for all species of the system are calculated at each configuration vertex, mirroring the procedure in XGC. This simple training has produced a median relative loss, across configuration space, of the order of 10 –4 , which is low enough if the error is of random nature, but not if it is of drift nature in time steps. The run time for the current Picard iterative solver of the operator is O(n 2 ), where n is the number of plasma species. As the XGC1 code begins to attack problems including a larger number of species, the collision operator will become expensive computationally, making the neural network solver even more important, especially since its training only scales as O(n). Here, a wide enough range of collisionality has been considered in the training data to ensure the full domain of collision physics is captured. An advanced technique to decrease the losses further will be subject of a subsequent report. Eventual work will include expansion of the network to include multiple plasma species.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Flexible Electronics toward Wearable Sensing

Wearable sensors play a crucial role in realizing personalized medicine, as they can continuously collect data from the human body to capture meaningful health status changes in time for preventive intervention. However, motion artifacts and mechanical mismatches between conventional rigid electronic materials and soft skin often lead to substantial sensor errors during epidermal measurement. Because of its unique properties such as high flexibility and conformability, flexible electronics enables a natural interaction between electronics and the human body. Here, we summarize our recent studies on the design of flexible electronic devices and systems for physical and chemical monitoring. Material innovation, sensor design, device fabrication, system integration, and human studies employed toward continuous and noninvasive wearable sensing are discussed. A flexible electronic device typically contains several key components, including the substrate, the active layer, and the interface layer. The inorganic-nanomaterials-based active layer (prepared by a physical transfer or solution process) is shown to have good physicochemical properties, electron/hole mobility, and mechanical strength. Flexible electronics based on the printed and transferred active materials has shown great promise for physical sensing. For example, integrating a nanowire transistor array for the active matrix and a conductive pressure-sensitive rubber enables tactile pressure mapping; tactile-pressure-sensitive e-skin and organic light-emitting diodes can be integrated for instantaneous pressure visualization. Such printed sensors have been applied as wearable patches to monitor skin temperature, electrocardiograms, and human activities. In addition, liquid metals could serve as an attractive candidate for flexible electronics because of their excellent conductivity, flexibility, and stretchability. Liquid-metal-enabled electronics (based on liquid-liquid heterojunctions and embedded microchannels) have been utilized to monitor a wide range of physiological parameters (e.g., pulse and temperature). Despite the rapid growth in wearable sensing technologies, there is an urgent need for the development of flexible devices that can capture molecular data from the human body to retrieve more insightful health information. We have developed a wearable and flexible sweat-sensing platform toward real-time multiplexed perspiration analysis. An integrated iontophoresis module on a wearable sweat sensor could enable autonomous and programmed sweat extraction. A microfluidics-based sensing system was demonstrated for sweat sampling, sensing, and sweat rate analysis. Roll-to-roll gravure printing allows for mass production of high-performance flexible chemical sensors at low cost. These wearable and flexible sweat sensors have shown great promise in dehydration monitoring, cystic fibrosis diagnosis, drug monitoring, and noninvasive glucose monitoring. Future work in this field should focus on designing robust wearable sensing systems to accurately collect data from the human body and on large-scale human studies to determine how the measured physical and chemical information relates to the individual's specific health conditions. Further research in these directions, along with the large sets of data collected via these wearable and flexible sensing technologies, will have a significant impact on future personalized healthcare.

47 OTHER INSTRUMENTATION↗

NASA NTRS1993

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated.

Cao, Tiehua↗

NASA NTRS1986

Evidence for explosive chromospheric evaporation in a solar flare observed with SMM

SMM soft X-ray data and Sacramento Peak Observatory H-alpha observations are combined in a study of the impulsive phase of a solar flare. A blue asymmetry, indicative of upflow motions, was observed in the coronal Ca XIX line during the soft X-ray rise phase. H-alpha redshifts, indicative of downward motions, were observed simultaneously in bright flare kernels during the period of hard X-ray emission. It is shown that, to within observational errors, the impulsive phase momentum transported by the upflowing soft X-ray plasma is equivalent to that of the downward moving chromospheric material.

Zarro, D. M.↗