Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network interaction”

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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗
DOE OSTI2016

H 2 -saturation of high affinity H 2 -oxidizing bacteria alters the ecological niche of soil microorganisms unevenly among taxonomic groups

Soil microbial communities are continuously exposed to H 2 diffusing into the soil from the atmosphere. N 2 -fixing nodules represent a peculiar microniche in soil where H 2 can reach concentrations up to 20,000 fold higher than in the global atmosphere (0.530 ppmv). In this study, we investigated the impact of H 2 exposure on soil bacterial community structure using dynamic microcosm chambers simulating soil H 2 exposure from the atmosphere and N 2 -fixing nodules. Biphasic kinetic parameters governing H 2 oxidation activity in soil changed drastically upon elevated H 2 exposure, corresponding to a slight but significant decay of high affinity H 2 -oxidizing bacteria population, accompanied by an enrichment or activation of microorganisms displaying low-affinity for H 2 . In contrast to previous studies that unveiled limited response by a few species, the relative abundance of 958 bacterial ribotypes distributed among various taxonomic groups, rather than a few distinct taxa, was influenced by H 2 exposure. Furthermore, correlation networks showed important alterations of ribotype covariation in response to H 2 exposure, suggesting that H 2 affects microbe-microbe interactions in soil. Taken together, our results demonstrate that H 2 -rich environments exert a direct influence on soil H 2 -oxidizing bacteria in addition to indirect effects on other members of the bacterial communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measuring the Electronic Bandgap of Carbon Nanotube Networks in Non-Ideal p-n Diodes

The measurement of the electronic bandgap and exciton binding energy in quasi-one-dimensional materials such as carbon nanotubes is challenging due to many-body effects and strong electron–electron interactions. Unlike bulk semiconductors, where the electronic bandgap is well known, the optical resonance in low-dimensional semiconductors is dominated by excitons, making their electronic bandgap more difficult to measure. In this work, we measure the electronic bandgap of networks of polymer-wrapped semiconducting single-walled carbon nanotubes (s-SWCNTs) using non-ideal p-n diodes. We show that our s-SWCNT networks have a short minority carrier lifetime due to the presence of interface trap states, making the diodes non-ideal. We use the generation and recombination leakage currents from these non-ideal diodes to measure the electronic bandgap and excitonic levels of different polymer-wrapped s-SWCNTs with varying diameters: arc discharge (~1.55 nm), (7,5) (0.83 nm), and (6,5) (0.76 nm). Our values are consistent with theoretical predictions, providing insight into the fundamental properties of networks of s-SWCNTs. The techniques outlined here demonstrate a robust strategy that can be applied to measuring the electronic bandgaps and exciton binding energies of a broad variety of nanoscale and quantum-confined semiconductors, including the most modern nanoscale transistors that rely on nanowire geometries.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Space time neural networks for tether operations in space

A space shuttle flight scheduled for 1992 will attempt to prove the feasibility of operating tethered payloads in earth orbit. due to the interaction between the Earth's magnetic field and current pulsing through the tether, the tethered system may exhibit a circular transverse oscillation referred to as the 'skiprope' phenomenon. Effective damping of skiprope motion depends on rapid and accurate detection of skiprope magnitude and phase. Because of non-linear dynamic coupling, the satellite attitude behavior has characteristic oscillations during the skiprope motion. Since the satellite attitude motion has many other perturbations, the relationship between the skiprope parameters and attitude time history is very involved and non-linear. We propose a Space-Time Neural Network implementation for filtering satellite rate gyro data to rapidly detect and predict skiprope magnitude and phase. Training and testing of the skiprope detection system will be performed using a validated Orbital Operations Simulator and Space-Time Neural Network software developed in the Software Technology Branch at NASA's Lyndon B. Johnson Space Center.

Lea, Robert N.↗
DOE OSTI2016

CMCSN: Structure and dynamics of water and aqueous solutions in materials science

This award has contributed to build a network of scientists interested in the structure and dynamics of water. Such network extends well beyond the PI and the co-PIs and includes both theoreticians and experimentalists. Scientific interactions within this community have been fostered by three workshops supported by the grant. The first workshop was held at Princeton University on December 6-8, 2010. The second workshop was held at the Talaris Conference Center in Seattle on February 10-12, 2012. The third workshop was held at UC Davis on June 19-22, 2013. Each workshop had 40-50 participants and about 20 speakers. The workshops have been very successful and stimulated ongoing discussions within the water community. This debate is lasting beyond the time frame set by the grant. The following events are just a few examples: (i) the month long activity on "Water: the most anomalous liquid" organized at NORDITA (Stockholm) in October- November 2014 by A. Nilsson and L. Petterson who participated in all the three CMCSN sponsored workshops; (ii) the workshop on "ice nucleation" organized by R. Car, P. Debenedetti and F. Stillinger at the Princeton Center for Theoretical Science in April 23- 24 2015; (iii) the 10 days workshop on water organized by R. Car and F. Mallamace at the E. Maiorana Centre in Erice (Sicily) in July 2016, an activity that will morph into a regular summer school of the E. Maiorana Centre in the years to come under the directorship of R. Car, F. Mallamace (U. Messina), A. Nilsson (U. Stockholm) and L. Xu (Beijing U.). All these activities were stimulated by the scientific discussions within the network initiated by this CMCSN grant.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Hydrogen Bonded Arrays: The Power of Multiple Hydrogen Bonds

Hydrogen bond interactions in small covalent model compounds (i.e. deprotonated polyhydroxy alcohols) were measured by negative ion photoelectron spectroscopy. The experimentally determined vertical and adiabatic electron detachment energies for (HOCH2CH2)2CHO (2a), (HOCH2CH2) 3CO (3a) and (HOCH2CH2CH(OH)CH2)3CO (4a) reveal that hydrogen-bonded networks can provide enormous stabilizations, and that a single charge center not only can be stabilized by up to 3 hydrogen bonds but it can increase the interaction energy between non-charged OH groups by 5.8 kcal mol1 or more per hydrogen bond. This can lead to pKa values that are very different than in water, and provide some of the impetus for catalytic processes.

08 HYDROGEN↗
DOE OSTI2017

Effect of ring rotation upon gas adsorption in SIFSIX-3-M (M = Fe, Ni) pillared square grid networks

The study of the mobility/rotation of the organic linkers in porous metal-organic frameworks could provide a valuable information about the guest/framework interaction and the factors control the kinetics of adsorption. Here, we analyzed the dynamics of pyrazine ring rotation in a series of pillared square grid frameworks, namely SIFSIX-3-M (M = Fe, Ni). It was found that the rotation of pyrazine ring is influenced by the variation of metal cation, temperature and the guest molecule. The Fe-analogue, [Fe(pz)2(SiF6)2] (pz= Pyrazine), , showed no pronounced ring rotation and exhibited a high affinity toward Xe gas over Kr as exemplified by the sharp Xe uptake at low loading (~0.1 bar) and its high isosteric heat of adsorption (Qst~ 27.4 kJmol-1) compared to the current benchmark materials. The Ni analogue, on the contrary, showed a two-regime adsorption isotherm for Xe with a temperature-dependent inflection point. However, this behavior is not observed with the other gases such as CO2, N2, and Kr which showed one-step adsorption isotherms without any inflection. Using molecular models and simulations, we hypothesize that the inflection point is due to a disordered to ordered transition of the rotational configurations of the pz rings in SIFSIX-3-Ni. These results further support the impact of tuning the pore size and chemistry on the adsorption behavior of porous materials.

Elsaidi, Sameh K.↗
DOE OSTI2024

Avian Activity Classification Using Recurrent Networks to Fuse Videos with Metadata on Imbalanced Datasets

Activity classification plays a crucial role in various real-life scenarios involving both humans and animals. There is an increasing need for precise activity classification focused on avian-solar interactions, as the usage of solar energy facilities, such as photovoltaic array power stations, has been observed to impact bird species richness, behavior, and activity. However, there has been no work to develop an automated system to monitor and classify these avian-solar interactions. All current methods rely on human observers, which is time and human resources costly and subject to errors related to searcher efficiency. With the recent success of Deep Learning models in activity classification problems, this paper develops a recurrent neural network-based model to automatically classify six avian activities around solar energy facilities. Our proposed model integrates critical feature engineering metadata with video frame data, enabling improved learning and more accurate activity classification. Furthermore, we address the challenge of data imbalance during training and demonstrate the efficacy of our model in detecting and classifying different activities within video tracks. Additionally, we analyze the saliency/backpropagation map of the trained proposed model and validate its decision-making rationale.

Avian activity classification; bidirectional LSTM;↗
DOE OSTI2024

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Unique (3,8)-connected lanthanide arenedisulfonate metal-organic frameworks containing benzimidazole-5,6-dicarboxylic acid co-ligand: Syntheses, structures and luminescence

Two isostructural 3D lanthanide arenedisulfonate metal-organic frameworks (MOFs) [Ln(Hbidc)(nds){sub 0.5}(H{sub 2}O)]{sub n}(Ln=Eu(1), La(2)) have been successfully synthesized by the hydrothermal reaction of lanthanide oxide with 2,6-naphthalenedisulfonate sodium (Na{sub 2}nds) and an auxiliary ligand, 1H-benzimidazole-5,6-dicarboxylic acid (H{sub 3}bidc). The two complexes are both constructed from 2D [Ln(Hbidc)]{sup +} double layers pillared by nds{sup 2−} ligands to generate 3D (3, 8)-connected open-framework structures with 1D long narrow channels running along the a axis. From topological point of view, the 3D framework is a (3, 8)-connected tfz-d net. The weak interactions including N–H⋯O, O–H⋯O hydrogen bonds and π–π stacking are observed in 1. The 2D IR correlation spectroscopy was applied to study the molecular interactions induced by thermal perturbation. The emission spectra of 1 exhibit the characteristic transition of {sup 5}D{sub 0}→{sup 7}F{sub J}(J=0–4) of Eu(III). - Graphical abstract: Two isostructural 3D (3,8)-connected lanthanide arenedisulfonates were hydrothermally synthesized. The 2D IR correlation spectroscopy was applied to study the molecular interactions induced by thermal perturbation. Display Omitted - Highlights: • The first lanthanide arenedisulfonates incorporating fused-ring aromatic carboxylic acid. • Three-dimensional (3,8)-connected framework with tfz-d network topology. • The emission spectra of 1 exhibit the characteristic transition of {sup 5}D{sub 0}→{sup 7}F{sub J} (J=0–4) of Eu(III). • The 2D IR correlation spectroscopy was applied to study the molecular interactions.

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

Cosolvent-tuned interactions in ionic liquids: A vibrational and quantum-chemical study of ethylene glycol ratio effects

Ionic liquids (ILs) are attractive media for CO 2 capture but remain limited by viscosity and cost. Blending ILs with ethylene glycol (EG) is a practical route to mitigate these constraints, yet the molecular origins of cosolvent effects and their dependence on composition are not well resolved. We combine Fourier-transform infrared (FT-IR) spectroscopy with quantum-chemical (DFT) analysis to elucidate how the IL:EG molar ratio modulates intermolecular interactions and electronic structure. Computed vibrational frequencies enable mode assignment and deconvolution of overlapping bands, revealing systematic, ratio-dependent shifts and broadenings in (i) EG O–H stretching, (ii) cation and EG C–H stretchings (imidazolium C2–H, C4–H, C5–H, methyl and ethyl groups, -CH2 of EG), (iii) anion signature modes (e.g., CN motifs), and (iv) EG C–O and C–C stretchings, consistent with the redistribution of hydrogen-bonding networks. Molecular electrostatic potential (MESP) maps quantify attenuation of extreme potential regions with increasing EG, indicating progressive screening of cation–anion electrostatic interactions. Quantum Theory of Atoms in Molecules (QTAIM) identifies emergent bond critical points between EG and the IL ions, while Reduced Density Gradient–Noncovalent Interaction (RDG–NCI) analysis differentiates strong directional hydrogen bonds from dispersive contacts across compositions. Together, these results show that EG fraction controls a switch from predominantly ion–ion to mixed ion–EG coordination, altering local polarity and polarizability that underlie the observed FT-IR trends. The framework provides composition–structure–spectrum relationships that can guide rational selection of IL:EG ratios to balance favorable molecular interactions with practical performance targets in scalable CO 2 capture systems.

DAC↗
NASA NTRS1993

A distributed system for visualizing and analyzing multivariate and multidisciplinary data

THe Linked Windows Interactive Data System (LinkWinds) is being developed with NASA support. The objective of this proposal is to adapt and apply that system in a complex network environment containing elements to be found by scientists working multidisciplinary teams on very large scale and distributed data sets. The proposed three year program will develop specific visualization and analysis tools, to be exercised locally and remotely in the LinkWinds environment, to demonstrate visual data analysis, interdisciplinary data analysis and cooperative and interactive televisualization and analysis of data by geographically separated science teams. These demonstrators will involve at least two science disciplines with the aim of producing publishable results.

Jacobson, Allan S.↗
DOE OSTI2017

Water‐Restructuring Mutations Can Reverse the Thermodynamic Signature of Ligand Binding to Human Carbonic Anhydrase

Abstract This study uses mutants of human carbonic anhydrase (HCAII) to examine how changes in the organization of water within a binding pocket can alter the thermodynamics of protein–ligand association. Results from calorimetric, crystallographic, and theoretical analyses suggest that most mutations strengthen networks of water‐mediated hydrogen bonds and reduce binding affinity by increasing the enthalpic cost and, to a lesser extent, the entropic benefit of rearranging those networks during binding. The organization of water within a binding pocket can thus determine whether the hydrophobic interactions in which it engages are enthalpy‐driven or entropy‐driven. Our findings highlight a possible asymmetry in protein–ligand association by suggesting that, within the confines of the binding pocket of HCAII, binding events associated with enthalpically favorable rearrangements of water are stronger than those associated with entropically favorable ones.

Fox, Jerome M.↗
DOE OSTI2017

Water-Restructuring Mutations Can Reverse the Thermodynamic Signature of Ligand Binding to Human Carbonic Anhydrase

In this study we use mutants of human carbonic anhydrase (HCAII) to examine how changes in the organization of water within a binding pocket can alter the thermodynamics of protein–ligand association. Results from calorimetric, crystallographic, and theoretical analyses suggest that most mutations strengthen networks of water-mediated hydrogen bonds and reduce binding affinity by increasing the enthalpic cost and, to a lesser extent, the entropic benefit of rearranging those networks during binding. The organization of water within a binding pocket can thus determine whether the hydrophobic interactions in which it engages are enthalpy-driven or entropy-driven. Our findings highlight a possible asymmetry in protein–ligand association by suggesting that, within the confines of the binding pocket of HCAII, binding events associated with enthalpically favorable rearrangements of water are stronger than those associated with entropically favorable ones.

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

Unlocking High Capacity and Reversible Alkaline Iron Redox Using Silicate-Sodium Hydroxide Hybrid Electrolytes

Alkaline iron (Fe) batteries are attractive due to the high abundance, low cost, and multiple valent states of Fe but show limited columbic efficiency and storage capacity when forming electrochemically inert Fe 3 O 4 on discharging and parasitic H 2 on charging. Herein, sodium silicate is found to promote Fe(OH) 2 /FeOOH against Fe(OH) 2 /Fe 3 O 4 conversions. Electrochemical experiments, operando X-ray characterization, and atomistic simulations reveal that improved Fe(OH) 2 /FeOOH conversion originates from (i) strong interaction between sodium silicate and iron oxide and (ii) silicate-induced strengthening of hydrogen-bond networks in electrolytes that inhibits water transport. Furthermore, the silicate additive suppresses hydrogen evolution by impairing energetics of water dissociation and hydroxyl de-sorption on iron surfaces. In conclusion, this new silicate-assisted redox chemistry mitigates H 2 and Fe 3 O 4 formation, improving storage capacity (199 mAh g -1 in half-cells) and coulombic efficiency (94 % after 400 full-cell cycles), paving a path to realizing green battery systems built from earth-abundant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

How Many Trip Requests Could We Support? An Activity-Travel Based Vehicle Scheduling Approach

In a world of ever-changing travel behavior and ever-increasing modal options, is vital to have integrated models that could capture the interactions between supply and demand layers of travel. Addressing this need, we propose three different versions of network representation and mathematical models for the activity-based vehicle routing problem to connect activity-travel graphs of passengers (demand layer) to spatio-temporal networks of vehicles (supply layer). Versions I and II are arc-based, while version III is path-based. In version I, we introduce the concept of activity-travel graphs for passengers. For vehicles, we construct space–time networks and add a new dimension, called “under-service state”, to track the execution status of trip requests at any location and time. In version II, we reduce the complexity of the network structure by eliminating the state dimension and some other modifications in the structure of the passengers’ and vehicles’ network. Although both versions can capture various behavioral constraints of the activity-based vehicle routing problem (e.g., mandatory and optimal activities, duration of activities, chain of activities, preferred starting and ending times of activities), due to the high level of complexity of the network structure, both versions can only solve small-sized problems. To tackle the computational complexity, we propose a path-based network representation in version III, and to make a balance between the disutility of passengers and vehicles, we present a tolled user equilibrium problem. Mathematical models are coded in C and GAMS and implemented on real-world Phoenix regional transportation network with more than 39 million trip requests, which demonstrate the effectiveness of the proposed solution for the original and restricted master problems.

33 ADVANCED PROPULSION SYSTEMS↗