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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Signal Processing of Multiplexed Optical PWM Signals for Sensor Arrays in Nuclear Environments

Safe and effective generation of terrestrial nuclear power greatly benefits from the actionable data provided by the array of sensors located throughout a plant to provide a holistic online indication of reactor operation. This array includes sensors for monitoring coolant flow and pressure, temperature and heat transfer, radiation levels, structure health monitoring, and other critical parameters for reactor operation. While sensors capable of measuring these parameters have been developed, the electronics used in the pre-amplification and analog-to-digital conversion of the small signals they produce are extremely sensitive and susceptible to damage by high-temperatures and radiation environments nuclear reactors encounter while generating power. The small signals from sensors in nuclear power plants (NPPs) are transmitted over long cable runs which introduce dispersion artifacts into the signals of interest as well as electromagnetic interference (EMI) from lighting fixtures, pumps, mains electricity, and other equipment. To overcome these challenges, a front-end digitization (FREND) platform has been developed to use radiation-tolerant electronics to multiplex, amplify, and optically encode signals from an array of sensors for transmission over an optical fiber to mitigate dispersion and EMI artifacts from long runs of electrical cabling. To recover the optically transmitted data, a signal processing scheme based on 1-dimensional template matching to an indexing channel is described herein and demonstrated to have an effective bit-depth of 9.2 bits (1%). This scheme has been validated in proof-of-concept, non-nuclear testing and preliminary experimental results show good agreement between the measured optical output and and sensor input signals. The FREND system represents a low-loss data link between sensors in nuclear environments and data acquisition hardware which is aimed at improving the signal-to-noise ratio of the data acquired from these sensors to provide better information to operators and researchers.

Sweeney, Dan↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals

Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. Here, this work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.

Industrial Internet of Things↗
DOE OSTI2020

Strong intracellular signal inactivation produces sharper and more robust signaling from cell membrane to nucleus

For a chemical signal to propagate across a cell, it must navigate a tortuous environment involving a variety of organelle barriers. In this work we study mathematical models for a basic chemical signal, the arrival times at the nuclear membrane of proteins that are activated at the cell membrane and diffuse throughout the cytosol. Organelle surfaces within human B cells are reconstructed from soft X-ray tomographic images, and modeled as reflecting barriers to the molecules’ diffusion. We show that signal inactivation sharpens signals, reducing variability in the arrival time at the nuclear membrane. Inactivation can also compensate for an observed slowdown in signal propagation induced by the presence of organelle barriers, leading to arrival times at the nuclear membrane that are comparable to models in which the cytosol is treated as an open, empty region. In the limit of strong signal inactivation this is achieved by filtering out molecules that traverse non-geodesic paths.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Moderate hypothermia protects increased neuronal autophagy via activation of extracellular signal-regulated kinase signaling pathway in a rat model of early brain injury in subarachnoid hemorrhage

Highlights: • Moderate hypothermia (MH) treatment has neuroprotective effect on SAH rats. • Moderate hypothermia can upregulate SAH-induced autophagy. • SAH-induced autophagy upregulated by moderate hypothermia depends on ERK signaling pathways. Moderate hypothermia (MH) used as treatment for neurological diseases has a protective effect; however, its mechanism remains unclear. Neuronal autophagy is a fundamental pathological process of early brain injury in subarachnoid hemorrhage (SAH). We found that moderate activation of autophagy can reduce nerve cells damage. In this study, We found that MH can moderately increase the level of autophagy in nerve cells and improve the neurological function in rats. This type of autophagy activation is dependent on extracellular signal-regulated kinase (ERK) signaling pathways. The level of neuronal autophagy was down-regulated significantly by using U0126, an ERK signaling pathway inhibitor. In summary, these results suggest that MH can moderately activate neuronal autophagy through ERK signaling pathway, reduce nerve cell death, and produce neuroprotective effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Chloroplast Stress Signals: Control of Retrograde Signaling, Chloroplast Turn-Over, and Cell Fate Decisions

Chloroplasts (photosynthetic plastids) are semiautonomous organelles that contain their own small genomes. The proteomes of chloroplasts, however, are a mixture of plastid and nuclear-encoded proteins. Chloroplasts perform photosynthesis, which is prone to damaging the organelles, leading to the production of reactive oxygen species (ROS) that damage the cell under environmental stresses. Thus, for the cell to maintain proper chloroplast function, efficient photosynthesis, and avoid ROS damage, it relies on complex crosstalk between the chloroplast, the nucleus, other organelles within the cell, and the cytoplasm in between. This communication involves retrograde signals from chloroplasts to control nuclear gene expression, programmed cell death (PCD), and chloroplast degradation. Here we review these signals with an emphasis on the roles of the ROS singlet oxygen ( 1 O 2 ) and plastid gene expression. We cover (1) recent work on understanding how multiple 1 O 2 signaling pathways can be initiated within stressed chloroplasts, (2) how individualized post-translational regulatory systems allow chloroplasts to control their proteomes and degradation, and (3) how chloroplast signals ultimately control cell fate decisions, such as PCD, senescence, and vacuole-mediated degradation of chloroplasts (chloroplast quality control). Overall, this chapter discusses how chloroplasts can act as environmental sensors for the cell and allow plants to acclimate to stress and thrive in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adaptive Urban Traffic Signal Control for Multiple Intersections: An LQR Approach

Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.

adaptive LQR control↗
DOE OSTI2023

Model Predictive Control for Urban Traffic Signals with Stability Guarantees

Traditional traffic signal control focuses more on the optimization aspects whereas the stability and robustness of the closed-loop system are less studied. This paper aims to establish the stability properties of traffic signal control systems through the analysis of a practical model predictive control (MPC) scheme, which models the traffic network with the conservation of vehicles based on a store-and forward model and attempts to balance the traffic densities. More precisely, this scheme guarantees the exponential stability of the closed-loop system under state and input constraints when the inflow is feasible and traffic demand can be fully accessed. Practical exponential stability is achieved in case of small uncertain traffic demand by a modification of the previous scheme. Simulation results of a small-scale traffic network validate the theoretical analysis.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2018

VEGFR-3 signaling is regulated by a G-protein activator, activator of G-protein signaling 8, in lymphatic endothelial cells

Highlights: • AGS8 knockdown inhibited VEGFC-mediated tube formation, growth, and migration of LECs. • AGS8 knockdown inhibited phosphorylation of VEGFR-3 and its downstream molecules. • VEGFR-3 formed a complex including AGS8 and Gβγ in cells. • AGS8 regulated the trafficking of VEGFR-3 to the plasma membrane. Vascular endothelial growth factor C (VEGFC) and its cognate receptor VEGFR-3 play a key role in lymphangiogenesis. We previously reported that an ischemia-inducible Gβγ signal regulator, activator of G-protein signaling 8 (AGS8), regulated the subcellular distribution of vascular endothelial growth factor receptor-2 (VEGFR-2) and influenced VEGFA-induced signaling in vascular endothelial cells. Here, we report that AGS8 regulates VEGFR-3, which is another subtype of the VEGF receptor family, and mediates VEGFC signaling in human dermal lymphatic endothelial cells (HDLECs). VEGFC stimulated the proliferation of HDLECs and tube formation by HDLECs, which were inhibited by knocking down AGS8 by small interfering RNA (siRNA). AGS8 siRNA inhibited VEGFC-mediated phosphorylation of VEGFR-3 and its downstream molecules, including ERK1/2 and AKT. Analysis of fluorescence-activated cell sorting and immunofluorescence staining demonstrated that AGS8 knockdown was associated with a reduction of VEGFR-3 at the cell surface. Endocytosis inhibitors did not rescue the decrease of cell-surface VEGFR-3, suggesting that AGS8 regulated the trafficking of VEGFR-3 to the plasma membrane. An immunoprecipitation assay indicated that VEGFR-3 formed a complex including AGS8 and Gβγ in cells. These data suggest the novel regulation of VEGFC-VEGFR-3 by AGS8 in HDLECs and a potential role for AGS8 in lymphangiogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Structures of TGF-β with betaglycan and signaling receptors reveal mechanisms of complex assembly and signaling

Abstract Betaglycan (BG) is a transmembrane co-receptor of the transforming growth factor-β (TGF-β) family of signaling ligands. It is essential for embryonic development, tissue homeostasis and fertility in adults. It functions by enabling binding of the three TGF-β isoforms to their signaling receptors and is additionally required for inhibin A (InhA) activity. Despite its requirement for the functions of TGF-βs and InhA in vivo, structural information explaining BG ligand selectivity and its mechanism of action is lacking. Here, we determine the structure of TGF-β bound both to BG and the signaling receptors, TGFBR1 and TGFBR2. We identify key regions responsible for ligand engagement, which has revealed binding interfaces that differ from those described for the closely related co-receptor of the TGF-β family, endoglin, thus demonstrating remarkable evolutionary adaptation to enable ligand selectivity. Finally, we provide a structural explanation for the hand-off mechanism underlying TGF-β signal potentiation.

Science & Technology - Other Topics↗
DOE OSTI2020

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2024

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗
DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM's existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

batteries↗
DOE OSTI2019

A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment

This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics. As an example, results are shown for 3.2 fb –1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. Furthermore, no significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

UCMS - A new signal parameter measurement system using digital signal processing techniques

The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

Choi, H. J.↗
NASA NTRS1990

Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

Ultrasonic inspection of thick and attenuating materials is hampered by the reduce amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low signal to noise ratio (S/N), a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. The correlator is described, and it is compared to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

Kishoni, Doron↗
NASA NTRS1989

Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

Ultrasonic inspection of thick and attenuating materials is hampered by the reduced amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low Signal to Noise (S/N) ratio, a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. This paper describes the correlator, and compares it to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

Kishoni, Doron↗