Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “network reduction”

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.

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

At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Latent code-based fusion: A Volterra neural network approach

We propose a deep structure encoder using Volterra Neural Networks (VNNs) to seek a latent representation of multi-modal data whose features are jointly captured by a union of subspaces. The so-called self-representation embedding of the latent codes leads to a simplified fusion which is driven by a similarly constructed decoding. The Volterra Filter architecture achieved reduction in parameter complexity is primarily due to controlled non-linearities being introduced by the higher-order convolutions in lieu of generalized activation functions. Experimental results on two different datasets have shown a significant improvement in the clustering performance for VNNs auto-encoder over conventional Convolutional Neural Networks (CNNs) auto-encoder. In addition, we also show that the proposed approach demonstrates a much-improved sample complexity over CNN-based auto-encoder with a robust classification performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Robotic Lunar Landers for Science and Exploration

NASA Marshall Space Flight Center and The Johns Hopkins University Applied Physics Laboratory has been conducting mission studies and performing risk reduction activities for NASA s robotic lunar lander flight projects. In 2005, the Robotic Lunar Exploration Program Mission #2 (RLEP-2) was selected as a Exploration Systems Mission Directorate precursor robotic lunar lander mission to demonstrate precision landing and definitively determine if there was water ice at the lunar poles; however, this project was canceled. Since 2008, the team has been supporting NASA s Science Mission Directorate designing small lunar robotic landers for diverse science missions. The primary emphasis has been to establish anchor nodes of the International Lunar Network (ILN), a network of lunar science stations envisioned to be emplaced by multiple nations. This network would consist of multiple landers carrying instruments to address the geophysical characteristics and evolution of the moon. Additional mission studies have been conducted to support other objectives of the lunar science community and extensive risk reduction design and testing has been performed to advance the design of the lander system and reduce development risk for flight projects. This paper describes the current status of the robotic lunar mission studies that have been conducted by the MSFC/APL Robotic Lunar Lander Development team, including the ILN Anchor Nodes mission. In addition, the results to date of the lunar lander development risk reduction efforts including high pressure propulsion system testing, structure and mechanism development and testing, long cycle time battery testing and combined GN&C and avionics testing will be addressed. The most visible elements of the risk reduction program are two autonomous lander test articles: a compressed air system with limited flight durations and a second version using hydrogen peroxide propellant to achieve significantly longer flight times and the ability to more fully exercise flight sensors and algorithms. Robotic Lunar Lander design and development will have significant feed-forward to other missions to the Moon and, indeed, to other airless bodies such as Mercury, asteroids, and Europa, to which similar science and exploration objectives are applicable.

Cohen, B. A.↗
DOE OSTI2016

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach

Here, this paper considers the problem of high-dimensional signal detection in a large distributed network whose nodes can collaborate with their one-hop neighboring nodes (spatial collaboration). We assume that only a small subset of nodes communicate with the fusion center (FC). We design optimal collaboration strategies which are universal for a class of deterministic signals. By establishing the equivalence between the collaboration strategy design problem and sparse principal component analysis (PCA), we solve the problem efficiently and evaluate the impact of collaboration on detection performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO 2 Reduction

Bimetallic catalysts are promising for the most difficult thermal and electrochemical reactions, but modeling the many diverse active sites on polycrystalline samples is an open challenge. Here, we present a general framework for addressing this complexity in a systematic and predictive fashion. Active sites for every stable low-index facet of a bimetallic crystal are enumerated and cataloged, yielding hundreds of possible active sites. The activity of these sites is explored in parallel using a neural-network-based surrogate model to share information between the many density functional theory (DFT) relaxations, resulting in activity estimates with an order of magnitude fewer explicit DFT calculations. Sites with interesting activity were found and provide targets for follow-up calculations. This process was applied to the electrochemical reduction of CO 2 on nickel gallium bimetallics and indicated that most facets had similar activity to Ni surfaces, but a few exposed Ni sites with a very favorable on-top CO configuration. This motif emerged naturally from the predictive modeling and represents a class of intermetallic CO 2 reduction catalysts. These sites rationalize recent experimental reports of nickel gallium activity and why previous materials screens missed this exciting material. Most importantly these methods suggest that bimetallic catalysts will be discovered by studying facet reactivity and diversity of active sites more systematically.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Quantifying Microstructure Variability in Laser Powder Bed Fusion 316 L Stainless Steel Microstructures with Spatial Statistics

Here, we have explored data-driven methods for material microstructure quantification that improve sensitivity to microstructural changes compared to traditional approaches. The methods integrate multiple microstructural properties, including grain morphology, crystallographic orientation, and material phase information. The simpler method employs maps of the Euclidean distance transformation metric to evaluate the morphology of grain boundary networks. The more intensive approach employs generalized spherical harmonic mapping for crystallographic orientations, per-pixel phase information, and a variational auto-encoder for dimensionality reduction and results in a multidimensional clustering of by microstructure similarity. Applied to an experimental dataset of additively manufactured steel, both methods detected slight variations in samples produced under nominally identical processing conditions. Both methods were able to distinguish between samples from multiple (nominally identical) builds, while the generalized spherical harmonics-based method could additionally cluster data samples rotated at two orientations on the build plate. The improved sensitivity of the methods, demonstrated through comparison with traditional microstructure characterization techniques, offers advantages for microstructure quantification and comparisons in advanced manufacturing applications.

SS316L↗
DOE OSTI2016

Redox-Active Supramolecular Polymer Binders for Lithium–Sulfur Batteries That Adapt Their Transport Properties in Operando

π-Stacked perylene bisimide (PBI) molecules are implemented here as highly networked, redox-active supramolecular polymer binders in sulfur cathodes for lightweight and energy-dense Li-S batteries. We show that the in operando reduction and lithiation of these PBI binders sustainably reduces Li-S cell impedance relative to nonredox active conventional polymer binders. This lower impedance enables high-rate cycling in Li-S cells with excellent durability, a critical step toward unlocking the full potential of Li-S batteries for electric vehicles and aviation.

25 ENERGY STORAGE↗
DOE OSTI2021

Hydrogen Bonding and Its Effect on the Orientational Dynamics of Water Molecules inside Polyelectrolyte Brush-Induced Soft and Active Nanoconfinement

Despite being the most ubiquitous compound on Earth, the fundamental properties of water are not fully understood, especially in nanoconfinement. Densely grafted polyelectrolyte (PE) molecules attain the configuration of a “brush”: these PE brushes, due to their ability to form hydrogen bonds (HBs) with water via the PE functional groups, act as a source of soft and active nanoconfinement for the brush-trapped water molecules. In this paper, we study the effects of PE brush-induced confinement on the structure, dynamics and energetics of the water-water and water-PE HBs. Our results indicate a significant weakening of the HBs from bulk to sparsely grafted to densely grafted brushes. i.e., by increasing the degree of brush-induced nanoconfinement. We explain that this weakening of water-water HBs is caused by the disruption of the extended network of water molecules within the brush-induced nanoconfinement. This is confirmed by performing a ring structure analysis of the water molecules, which yields a reduction in the average ring size at higher degrees of brush-induced nanoconfinement (i.e., at higher brush grafting densities). Furthermore, we investigate the role of HB on the orientational dynamics of the water molecules. Here, we observe that the rotational motion of the water molecules becomes sluggish inside the PE brushes. Recent findings have indicated that the water and counterions trapped in brush-induced nanoconfinement demonstrate structures (in combination with the PE functional group) analogous to that in “water-in-salt” electrolytes that have seen extensive recent uses for Li-ion battery applications. However, the rotational dynamics of water molecules inside the brush-induced nanoconfinement is found to be distinctly different from that of conventional “water-in-salt” electrolytes in absence of any confinement; therefore, the present study will provide the necessary platform towards conceptualizing polymer-based nanoconfinement for battery applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Ripple Effects: Bed Form Morphodynamics Cascading Into Hyporheic Zone Biogeochemistry

The water quality and ecosystem health of river corridors depend on the biogeochemical processes occurring in the hyporheic zones (HZs) of the beds and banks of rivers. HZs in riverbeds often form because of bed forms. Despite widespread and persistent variation in river flow, how the discharge- and grain size-dependent geometry of bed forms and how bed form migration collectively and systematically affects hyporheic exchange flux, solute transport, and biogeochemical reaction rates are unknown. As such, we investigated these linked processes through morphodynamically consistent multiphysics numerical simulation experiments. Several realistic ripple geometries based on bed form stability criteria using mean river flow velocity and median sediment grain size were designed. Ripple migration rates were estimated based primarily on the river velocity. The ripple geometries and migration rates were used to drive hyporheic flow and reactive transport models which quantified HZ nitrogen transformation. Results from fixed bed form simulations were compared with matching migrating bed form scenarios. We found that the turnover exchange due to ripple migration has a large impact on reactant supply and reaction rates. The nitrate removal efficiency increased asymptotically with Damköhler number for both mobile and immobile ripples, but the immobile ripple always had a higher nitrate removal efficiency. Since moving ripples remove less nitrogen, and may even be net nitrifying at times, consideration for bed form morphodynamics may therefore lead to reduction of model-based estimates of denitrification. The connection between nitrate removal efficiency and Damköhler number can be integrated into frameworks for quantifying transient, network-scale, HZ nitrate dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy-Covariance Observations

Although there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy-covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi-arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non-linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep-rooted plants when only using surface-layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Targeted Energy Management System Toolset

TEMST integrates advanced sensor systems with advanced computational intelligence, e.g. neural networks and fuzzy arithmetic, to enable effective energy management while minimizing negative human comfort consequences and promoting improved occupant satisfaction. Preliminary work suggests that energy cost reductions above ten percent are easily achievable. In addition to optimizing existing Energy Management Systems (EMS), the proposed toolset will be both resilient and secure in order to proactively maintain a safe level of operational normalcy in response to anomalies and malicious actions.

Rieger, CraigG.↗
DOE OSTI2020

Applying Waveform Correlation to Mining Blasts Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment that uses waveform templates recorded by multiple International Monitoring System stations of the Comprehensive Nuclear-Test-Ban Treaty for up to 10 years prior to detect and identify mining blasts that occur during single weeks of study. We discuss approaches for template selection, threshold setting, and event detection that are specialized for mining blasts and a sparse, global network. We apply the approaches to two different weeks of study for each of two geographic regions, Wyoming and Scandinavia, to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to develop an intuition about potential reduction in analyst workload.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Applying Waveform Correlation to Mining Blasts Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment that uses waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization for up to 10 years prior to the time period of interest to detect and identify mining blasts that occur during single weeks of study. We discuss approaches for template selection, threshold setting, and event detection that are specialized for mining blasts and a sparse, global network. We apply the approaches to two different weeks of study for each of two geographic regions, Wyoming and Scandinavia, to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to develop an intuition about potential reduction in analyst workload.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

Applying Waveform Correlation to Aftershock Sequences Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize earthquake aftershock sequences to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in detecting similar seismic waveforms from repeating earthquakes, including aftershock sequences. We report the results of an experiment that uses waveform templates recorded by multiple stations of the Comprehensive Nuclear-Test-Ban Treaty International Monitoring System during the first twelve hours after a mainshock to detect and identify aftershocks that occur during the subsequent week. We discuss approaches for station and template selection, threshold setting, and event detection that are specialized for aftershock processing for a sparse, global network. We apply the approaches to three aftershock sequences to evaluate the potential for establishing a set of standards for aftershock waveform correlation processing that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Center to develop an intuition about potential reduction in analyst workload.

58 GEOSCIENCES↗
NASA NTRS1995

High energy collimating fine grids

The objective of this project was to demonstrate the fabrication of extremely tight tolerance collimating grids using a high-Z material, specifically tungsten. The approach taken was to fabricate grids by a replication method involving the coating of a silicon grid substrate with tungsten by chemical vapor deposition (CVD). A negative of the desired grid structure was fabricated in silicon using highly wafering techniques developed for the semiconductor industry and capable of producing the required tolerances. Using diamond wafering blades, a network of accurately spaced slots was machined into a single-crystal silicon surface. These slots were then filled with tungsten by CVD, via the hydrogen reduction of tungsten hexafluoride. Following tungsten deposition, the silicon negative was etched away to leave the tungsten collimating grid structure. The project was divided into five tasks: (1) identify materials of construction for the replica and final collimating grid structures; (2) identify and implement a micromachining technique for manufacturing the negative collimator replicas (performed by NASA/JPL); (3) develop a CVD technique and processing parameters suitable for the complete tungsten densification of the collimator replicas; (4) develop a chemical etching technique for the removal of the collimator replicas after the tungsten deposition process; and (5) fabricate and deliver tungsten collimating grid specimens.

Arrieta, Victor M.↗
NASA NTRS1993

Precision X-band Doppler and ranging navigation for current and future Mars exploration missions

This paper describes a navigation error covariance analysis of two scenarios derived from the Mars Observer mission and the planned Mars Environmental SURvey (MESUR) Pathfinder mission, respectively. The analysis was performed to establish the potential navigational performance of the X-band tracking system in NASA's Deep Space Network, and to evaluate the sensitivity of the predicted performance to variations in the quantity of data acquired, the ground system error modeling assumptions, and data reduction schemes. The simulated data arcs used in the analysis are representative of the actual data arcs that will be used to predict the aim point for the Mars orbit insertion maneuver, in the case of Mars Observer, and the interplanetary trajectory aim point corresponding to the target Mars landing site in the case of MESUR Pathfinder. The results indicate that with a suitable sequential data reduction scheme and accurate calibrations of instrumentation, transmission media, and platform model parameters, navigation accuracies of 5 to 15 km (1 sigma) can be achieved, equivalent to 15 to 40 nrad in geocentric angle uncertainty.

Estefan, Jeffrey A.↗
NASA NTRS2014

Modeling Increased Complexity and the Reliance on Automation: FLightdeck Automation Problems (FLAP) Model

This paper highlights the development of a model that is focused on the safety issue of increasing complexity and reliance on automation systems in transport category aircraft. Recent statistics show an increase in mishaps related to manual handling and automation errors due to pilot complacency and over-reliance on automation, loss of situational awareness, automation system failures and/or pilot deficiencies. Consequently, the aircraft can enter a state outside the flight envelope and/or air traffic safety margins which potentially can lead to loss-of-control (LOC), controlled-flight-into-terrain (CFIT), or runway excursion/confusion accidents, etc. The goal of this modeling effort is to provide NASA's Aviation Safety Program (AvSP) with a platform capable of assessing the impacts of AvSP technologies and products towards reducing the relative risk of automation related accidents and incidents. In order to do so, a generic framework, capable of mapping both latent and active causal factors leading to automation errors, is developed. Next, the framework is converted into a Bayesian Belief Network model and populated with data gathered from Subject Matter Experts (SMEs). With the insertion of technologies and products, the model provides individual and collective risk reduction acquired by technologies and methodologies developed within AvSP.

Ancel, Ersin↗
NASA NTRS1993

Precision X-Band Doppler and Ranging Navigation For Current and Future Mars Exploration Missions

This paper describes a navigation error convariance analysis of two scenarios derived from the Mars Observer mission and the planned Mars Environmental Survey (MESUR) Pathfinder mission, respectively. The analysis was performed to establish the potential navigational performance of the X-band tracking system in NASA's Deep Space Network, and to evaluate the sensitivity of the Predicted performance to variations in the quantity of data acquired, the ground system error modeling assumptions, and data reduction schemes.

Precision↗
DOE OSTI2018

3D electron tomographic and biochemical analysis of ER, Golgi and trans Golgi network membrane systems in stimulated Venus flytrap (Dionaea muscipula) glandular cells

The insect-trapping leaves of Dionaea muscipula provide a model for studying the secretory pathway of an inducible plant secretory system. The leaf glands were induced with bovine serum albumin to secrete proteases that were characterized via zymogram activity gels over a 6-day period. The accompanying morphological changes of the endoplasmic reticulum (ER) and Golgi were analyzed using 3D electron tomography of glands preserved by high-pressure freezing/freeze substitution methods. Secretion of multiple cysteine and aspartic proteases occurred biphasically. The majority of the Golgi was organized in clusters consisting of 3–6 stacks surrounded by a cage-like system of ER cisternae. In these clusters, all Golgi stacks were oriented with their cis-most C1 cisterna facing an ER export site. The C1 Golgi cisternae varied in size and shape consistent with the hypothesis that they form de novo. Following induction, the number of ER-bound polysomes doubled, but no increase in COPII vesicles was observed. Golgi changes included a reduction in the number of cisternae per stack and a doubling of cisternal volume without increased surface area. Polysaccharide molecules that form the sticky slime cause swelling of the trans and trans Golgi network (TGN) cisternae. Peeling of the trans-most cisternae gives rise to free TGN cisternae. One day after gland stimulation, the free TGNs were frequently associated with loose groups of oriented actin-like filaments which were not seen in any other samples. These findings suggest that the secretory apparatus of resting gland cells is “overbuilt” to enable the cells to rapidly up-regulate lytic enzyme production and secretion in response to prey trapping.

59 BASIC BIOLOGICAL SCIENCES↗