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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 451 records · Page 25
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Estimating Bidirectional Reflectance and Monitoring Stability of SNPP-VIIRS Reflective Solar Bands Using A Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System project provides the scientific community with observed top-of-atmosphere shortwave and longwave fluxes for climate monitoring and climate model validation. To provide consistent VIIRS cloud retrievals, the CERES Imager and Geostationary Calibration Group (IGCG) must understand and quantify the stability of the VIIRS instruments. To achieve this, the IGCG utilizes tropical deep convective clouds (DCCs) as invariant targets. Proper seasonal characterization of the DCC bidirectional reflectance distribution function (BRDF) is key to the success of DCC-based calibration methods, particularly for shortwave infrared (SWIR) bands. This article proposes the use of a deep neural network (DNN) to characterize VIIRS solar reflective band BRDF reflectance, with which individual channel trends are isolated by manipulating the DNN time input. Initial results show that the DNN method can extract statistically significant SNPP-VIIRS band trends, using only SNPP-VIIRS inputs, that are correlative to and match the magnitude of significant trends determined using methods that rely on an external angular distribution model. It may be possible to apply this approach to actively monitor the stability of new instruments without the need for predetermined seasonal BRDF corrections.

Benjamin Scarino↗
DOE OSTI2022

Seismic monitoring of CO 2 geosequestration using multi-well 4D DAS VSP: Stage 3 of the CO2CRC Otway project

An important part of any CO 2 geosequestration project is to ensure CO 2 containment and conformance in the subsurface. This is generally done by implementing a comprehensive, risk-based Measurement, Monitoring and Verification plan, a key element of which is active time-lapse seismic monitoring. However, high cost and environmental impact of the standard surface seismic monitoring dictate the need for a cost-effective and environmentally friendly alternative. An opportunity to develop such method emerges with advances in distributed acoustic sensing (DAS) technology, which turns an optical fibre into a seismic sensor with dense spatial sampling. DAS can be permanently deployed in multiple wells across the geosequestration site providing a robust and non-intrusive network of seismic receivers. This approach was developed and tested in the CO2CRC Otway project, where injection of 15 kt of CO 2 at 1.5 km depth was monitored with a 4D vertical seismic profiling (VSP) using five borehole DAS arrays and mobile vibroseis sources. The 4D DAS VSP in each of the five wells provides broadly consistent images of the CO 2 plume with some differences due to different illumination of the target horizon, lateral variation of velocities, and seismic anisotropy. When the newly injected CO 2 reaches a CO 2 plume created as a result of an earlier injection into the same formation ~600 m updip, 4D DAS VSP shows a change in reflectivity in that area and beyond. Furthermore, this shows a potential of 4D DAS VSP for monitoring gas injection into gas-saturated reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Young but fading radio sources: searching for remnants among compact steep-spectrum radio sources

The incidence of young but fading radio sources provides important information on the life cycle of radio emission in radio-loud active galactic nuclei. Despite its importance for constraining the models of radio source evolution, there are no systematic studies of remnants in complete samples of young radio sources. We report results of the study of 18 compact steep-spectrum (CSS) radio sources, selected from the statistically complete B3-VLA (Very Large Array) CSS sample, characterized by a steep optically thin spectrum (α ≥ 1.0) and no core detection in earlier studies. Our deep multifrequency VLA, pc-scale Very Long Baseline Array, and enhanced Multi Element Remotely Linked Interferometer Network (e-MERLIN) observations allowed us to locate the core component in 10 objects. In three CSS sources, there is no clear evidence of present-time active regions, suggesting that they are likely in a remnant phase. Among sources with core detection, we find three objects that have no clear active regions (hotspots) at the edges of the radio structure, suggesting that the radio emission may have just restarted. Our results support a power-law distribution of the source ages, although the poor statistics prevents us from setting solid constraints on the percentage of remnants and restarted sources in subpopulations of radio sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Robust Frequency and Voltage-Constrained Networked Microgrid Restoration

Here, this paper proposes a safe soft actor-critic reinforcement learning (RL) algorithm–based controller for networked microgrid restoration. It formulates the post black-start start as a finite-horizon constrained Markov decision process. The RL agent co-optimizes real and reactive power set-points for both grid-forming and grid-following inverters under explicit voltage and frequency constraints, while enforcing proper power sharing via the Mean Active Power Sharing Index (MPSI) and Mean Reactive Power Sharing Index (MQSI). Numerical results obtained on the IEEE 123-bus distribution system show that the proposed method achieves a mean voltage build-up time of 0.01 s without breaching the 5% sharing-violation budget under various load scenarios, considering MPSI and MQSI indices. These findings demonstrate that the proposed method yields fast and safe black-start schedules without resorting to heuristic penalties.

Selim, Alaa [Dartmouth College, Hanover, NH (Unite↗
DOE OSTI2023

Control of energy storage to reduce electric power system off-nominal frequency deviations

A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.

Vartanian, Charles K.↗
DOE OSTI2024

Deciphering the Cofilin Oligomers via Intermolecular Disulfide Bond Formation: A Coarse-Grained Molecular Dynamics Approach to Understanding Cofilin’s Regulation on Actin Filaments

Cofilin, a key actin-binding protein, orchestrates the dynamics of the actomyosin network through its actin-severing activity and by promoting the recycling of actin monomers. Recent experimental work suggests that cofilin also forms functionally distinct oligomers through thiol post-translational modification (PTM) that encourages actin nucleation and assembly. Despite these advances, the structural conformations of cofilin oligomers that modulate actin activity remain elusive because there are combinatorial ways to oxidize thiols in cysteines to form disulfide bonds rapidly. This study employs molecular dynamics simulations to investigate human cofilin 1 as a case study for exploring cofilin dimers via disulfide bond formation. Using the free energy profiling, our simulations unveil a range of probable cofilin dimer structures not represented in current Protein Data Bank entries. These candidate dimers are characterized by their distinct population distributions and relative free energies. Of particular note is a dimer featuring an interface between cysteines 139 and 147 residues, which demonstrates stable free energy characteristics and intriguingly symmetrical geometry. In contrast, the experimentally proposed dimer structure exhibits a less stable free energy profile. Here, we also evaluate frustration quantification based on the energy landscape theory in the protein-protein interactions at the dimer interfaces. Notably, the 39-39 dimer configuration emerges as a promising candidate for forming cofilin tetramers, as substantiated by frustration analysis. Additionally, docking simulations with actin filaments further evaluate the stability of these cofilin dimer-actin complexes. Our findings thus offer a computational framework for understanding the role of thiol post-translational modification cofilin proteins in regulating oligomerization, and the subsequent cofilin-mediated actin dynamics in the actomyosin network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

A novel method to reconstruct the energy of hadronic showersin the CMS High Granularity Calorimeter (HGCAL) is presented. TheHGCAL is a sampling calorimeter with very fine transverse andlongitudinal granularity. The active media are silicon sensors andscintillator tiles readout by SiPMs and the absorbers are acombination of lead and Cu/CuW in the electromagnetic section, andsteel in the hadronic section. The shower reconstruction method isbased on graph neural networks and it makes use of a dynamicreduction network architecture. It is shown that the algorithm isable to capture and mitigate the main effects that normally hinderthe reconstruction of hadronic showers using classicalreconstruction methods, by compensating for fluctuations in themultiplicity, energy, and spatial distributions of the shower'sconstituents. The performance of the algorithm is evaluated usingtest beam data collected in 2018 prototype of the CMS HGCALaccompanied by a section of the CALICE AHCAL prototype. Thecapability of the method to mitigate the impact of energy leakagefrom the calorimeter is also demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

Monitoring of the MU radar antenna pattern by Satellite Ohzora (EXOS-C)

As the first attempt among MST (mesosphere stratosphere troposphere) type radars, the MU (middle and upper atmosphere) radar features an active phased array system. Unlike the conventional large VHF radars, in which output power of a large vacuum tube is distributed to individual antenna elements, each of 475 solid state power amplifier feeds each antenna element. This system configuration enables very fast beam steering as well as various flexible operations by dividing the antenna into independent subarrays, because phase shift and signal division/combination are performed at a low signal level using electronic devices under control of a computer network. The antenna beam can be switched within 10 microsec to any direction within the zenith angle of 30 deg. Since a precise phase alignment of each element is crucial to realize the excellent performance of this system, careful calibration of the output phase of each power amplifier and antenna element was carried out. Among various aircraft which may be used for this purpose artificial satellites have an advantage of being able to make a long term monitoring with the same system. An antenna pattern monitoring system for the MU radar was developed using the scientific satellite OHZORA (EXOS-C). A receiver named MUM (MU radar antenna Monitor) on board the satellite measures a CW signal of 100 to 400 watts transmitted from the MU radar. The principle of the measurement and results are discussed.

Sato, T.↗
DOE OSTI2025

Braxton Marlatt Intern Poster

The Internet of Things (IoT) encompasses a vast network of interconnected devices embedded with software, sensors, and network connectivity, enabling data collection and exchange. While IoT technology revolutionizes various industries, it also introduces significant security challenges. This research focuses on enhancing IoT security through the implementation of Zero Trust Architecture concepts, specifically targeting the Network and Device pillars of the Cybersecurity and Infrastructure Security Agency’s Zero Trust Maturity Model. By generating Codified Attack Surfaces (CAS) using custom Structured Threat Information eXpression bundles, this project aims to provide enhanced visibility into network communications, detect vulnerabilities in device firmware, and improve the overall security posture for IoT devices and networks. The methodology involves defining custom STIX schema and objects, collecting data from intra-IoT traffic, external network traffic, and firmware analysis, and automating the conversion and correlation of this data into STIX bundles. The automated generation of attack surfaces offers comprehensive insights into activity, vulnerabilities, and anomalies within an IoT environment, enabling proactive threat identification and mitigation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

MODIS algorithm development and data visualization using ACTS

The study of the Earth as a system will require the merger of scientific and data resources on a much larger scale than has been done in the past. New methods of scientific research, particularly in the development of geographically dispersed, interdisciplinary teams, are necessary if we are to understand the complexity of the Earth system. Even the planned satellite missions themselves, such as the Earth Observing System, will require much more interaction between researchers and engineers if they are to produce scientifically useful data products. A key component in these activities is the development of flexible, high bandwidth data networks that can be used to move large amounts of data as well as allow researchers to communicate in new ways, such as through video. The capabilities of the Advanced Communications Technology Satellite (ACTS) will allow the development of such networks. The Pathfinder global AVHRR data set and the upcoming SeaWiFS Earthprobe mission would serve as a testbed in which to develop the tools to share data and information among geographically distributed researchers. Our goal is to develop a 'Distributed Research Environment' that can be used as a model for scientific collaboration in the EOS era. The challenge is to unite the advances in telecommunications with the parallel advances in computing and networking.

Abbott, Mark R.↗
NASA NTRS2011

Design of Refractory Metal Heat Pipe Life Test Environment Chamber, Cooling System, and Radio Frequency Heating System

A series of 16 Mo-44.5%Re alloy/sodium heat pipes will be experimentally tested to examine heat pipe aging. To support this evaluation, an environmental test chamber and a number of auxiliary subsystems are required. These subsystems include radio frequency (RF) power supplies/inductive coils, recirculation water coolant loops, and chamber gas conditioning. The heat pipes will be grouped, based on like power and gas mixture requirements, into three clusters of five units each, configured in a pentagonal arrangement. The highest powered heat pipe will be tested separately. Test chamber atmospheric purity is targeted at <0.3 ppb oxygen at an approximate operating pressure of 76 torr (.1.5 psia), maintained by active purification (oxygen level is comparable to a 10(exp -6) torr environment). Treated water will be used in two independent cooling circuits to remove .85 kW. One circuit will service the RF hardware while the other will maintain the heat pipe calorimetry. Initial procedures for the startup and operation of support systems have been identified. Each of these subsystems is outfitted with a variety of instrumentation, integrated with distributed real-time controllers and computers. A local area network provides communication between all devices. This data and control network continuously monitors the health of the test hardware, providing warning indicators followed by automatic shutdown should potentially damaging conditions develop. During hardware construction, a number of checkout tests.many making use of stainless steel prototype heat pipes that are already fabricated.will be required to verify operation.

Martin, J. J.↗
DOE OSTI2022

Hydrological Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.

(ICON) principles to address↗
DOE OSTI2021

Restoration Strategy for Active Distribution Systems Considering Endogenous Uncertainty in Cold Load Pickup

Cold load pickup (CLPU) phenomenon is identified as the persistent power inrush upon a sudden load pickup after an outage. Under the active distribution system (ADS) paradigm, where distributed energy resources (DERs) are extensively installed, the decreased outage duration can induce a strong interdependence between CLPU pattern and load pickup decisions. In this paper, we propose a novel modelling technique to tractably capture the decision-dependent uncertainty (DDU) inherent in the CLPU process. Subsequently, a two-stage stochastic decision-dependent service restoration (SDDSR) model is constructed, where first stage searches for the optimal switching sequences to decide step-wise network topology, and the second stage optimizes the detailed generation schedule of DERs as well as the energization of switchable loads. Further, to tackle the computational burdens introduced by mixed-integer recourse, the progressive hedging algorithm (PHA) is utilized to decompose the original model into scenario-wise subproblems that can be solved in parallel. The numerical test on modified IEEE 123-node test feeders has verified the efficiency of our proposed SDDSR model and provided fresh insights into the monetary and secure values of DDU quantification.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Bimetallic Ir x Pb nanowire networks with enhanced electrocatalytic activity for the oxygen evolution reaction

Metallic nanowire networks (MNNs) have attracted increasing attention due to their high surface area and tunable compositions. Although enormous efforts have been devoted to preparing noble metal MNNs with different compositions, the composition optimization and the formation mechanism of Ir-based MNNs have not been thoroughly investigated. Here, this work presents a facile method for synthesizing robust Ir-based bimetallic MNNs by chemical reduction. As unveiled by our characterization, the network structure is constructed by ultrafine nanowires evolved from aggregated nanoparticles. The element analysis confirms the even distribution of Pb and Ir elements. The introduction of Pb is found to be beneficial to the stable formation of Ir x Pb MNNs in the sol–gel process. By tuning the precursor ratio of Ir and Pb, the optimized Ir x Pb catalyst delivers an enhanced oxygen evolution reaction (OER) performance in acid media (307 mV at 10 mA cm −2 ), which is superior to that of the commercial IrO 2 catalyst. Besides, due to the robust structure of the Ir x Pb MNNs, excellent OER durability is observed in the accelerated durability test (ADT) (2000 cycles).

Bimetallic↗
NASA NTRS1997

A Scalable Distributed Approach to Mobile Robot Vision

This paper documents our progress during the first year of work on our original proposal entitled 'A Scalable Distributed Approach to Mobile Robot Vision'. We are pursuing a strategy for real-time visual identification and tracking of complex objects which does not rely on specialized image-processing hardware. In this system perceptual schemas represent objects as a graph of primitive features. Distributed software agents identify and track these features, using variable-geometry image subwindows of limited size. Active control of imaging parameters and selective processing makes simultaneous real-time tracking of many primitive features tractable. Perceptual schemas operate independently from the tracking of primitive features, so that real-time tracking of a set of image features is not hurt by latency in recognition of the object that those features make up. The architecture allows semantically significant features to be tracked with limited expenditure of computational resources, and allows the visual computation to be distributed across a network of processors. Early experiments are described which demonstrate the usefulness of this formulation, followed by a brief overview of our more recent progress (after the first year).

Kuipers, Benjamin↗
NASA NTRS2012

NASA In Situ Data Needs to Support the Operational Calibration and Validation of Ocean Color Satellite Data Products

Calibrating ocean color satellite instruments and validating their data products requires temporal and spatial abundances of high quality in situ oceanographic data. The Consortium for Ocean Leadership Ocean Observing Initiative (OOl) is currently implementing a distributed array of in-water sensors that could provide a significant contribution to future ocean color activities. This workshop will scope the optimal way to use and possibly supplement the planned OOl infrastructure to maximize its utility and relevance for calibration and validation activities that support existing and planned NASA ocean color missions. Here, I present the current state of the art of NASA validation of ocean color data products, with attention to autonomous time-series (e.g., the AERONET -OC network of above-water radiometers), and outline NASA needs for data quality assurance metrics and adherence to community-vetted data collection protocols

Werdel, P. Jeremy↗
NASA NTRS2012

Particle Filtering for Model-Based Anomaly Detection in Sensor Networks

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.

Solano, Wanda↗
DOE OSTI2024

Transcriptomic and Proteomic Insights into Host Immune Responses in Pediatric Severe Malarial Anemia: Dysregulation in HSP60-70-TLR2/4 Signaling and Altered Glutamine Metabolism

Severe malarial anemia (SMA, Hb < 6.0 g/dL) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission zones. This study explored the entire expressed human transcriptome in whole blood from 66 Kenyan children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25), focusing on host immune response networks. RNA-seq analysis revealed 6862 differentially expressed genes, with equally distributed up-and down-regulated genes, indicating a complex host immune response. Deconvolution analyses uncovered leukocytic immune profiles indicative of a diminished antigenic response, reduced immune priming, and polarization toward cellular repair in SMA. Weighted gene co-expression network analysis revealed that immune-regulated processes are central molecular distinctions between non-SMA and SMA. A top dysregulated immune response signaling network in SMA was the HSP60-HSP70-TLR2/4 signaling pathway, indicating altered pathogen recognition, innate immune activation, stress responses, and antigen recognition. Validation with high-throughput gene expression from a separate cohort of Kenyan children (n = 50) with varying severities of malarial anemia (n = 38 non-SMA and n = 12 SMA) confirmed the RNA-seq findings. Proteomic analyses in 35 children with matched transcript and protein abundance (n = 19 non-SMA and n = 16 SMA) confirmed dysregulation in the HSP60-HSP70-TLR2/4 signaling pathway. Additionally, glutamine transporter and glutamine synthetase genes were differentially expressed, indicating altered glutamine metabolism in SMA. This comprehensive analysis underscores complex immune dysregulation and novel pathogenic features in SMA.

Microbiology↗