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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Microstencils to generate defined, multi-species patterns of bacteria

Microbial communities are complex heterogeneous systems that are influenced by physical and chemical interactions with their environment, host, and community members. Techniques that facilitate the quantitative evaluation of how microscale organization influences the morphogenesis of multispecies communities could provide valuable insights into the dynamic behavior and organization of natural communities, the design of synthetic environments for multispecies culture, and the engineering of artificial consortia. In this work, we demonstrate a method for patterning microbes into simple arrangements that allow the quantitative measurement of growth dynamics as a function of their proximity to one another. The method combines parylene-based liftoff techniques with microfluidic delivery to simultaneously pattern multiple bacterial species with high viability using low-cost, customizable methods. Furthermore, quantitative measurements of bacterial growth for two competing isolates demonstrate that spatial coordination can play a critical role in multispecies growth and structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Evaluating the Impact of Power Outages on Occupancy Patterns During the 2021 Texas Power Crisis

Large-scale power outages, such as those caused by extreme weather events, have a big impact on human behavior. A short power outage is merely a nuisance for most, and may not change people's locations. An outage that lasts for a few hours can result in spoiled food and medical supplies, and people will have to restock spoiled items. Long outages result in temperatures outside tolerable levels in homes, and may prompt people to acquire supplies, such as generators and gas, or change location. The long outages during Winter Storm Uri in Texas resulted in millions of dollars in property damage due to freezing pipes. This level of damage is expected to result in a sharp increase in supply runs and contractor activity. In this paper, we present a tool to explore differences in visiting patterns before, during, and after power outages. It allows to compare different points of interest like medical facilities, grocery stores, hardware stores, and other types of businesses.

big data↗
DOE OSTI2017

Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs

The concept of motifs provides a fresh perspective for studying local patterns, which is useful for understanding the essence of a network structure. However, few previous studies have focused on the evolutionary characteristics of weighted motifs while further considering participants’ differences. We study how information connections differ among multiple investors. The evolutionary 10-year trend of weighted 3-motifs in China’s energy stock markets is explored for the networks of co-holding behaviors among shareholders, who are classified as companies, funds and individuals. Our works allow us to detect the preferential local patterns distributed among different agents as their fluctuate involvement in networks. We find that the diversity of shareholders contributes to the statistical significance of local patterns, while homophily always exist among individuals. Modules of information connections are stable among reserved investors, which is especially apparent among companies. Individuals prefer to keep their connections with companies and funds. Unsteady modules happen owing to strengthen links among funds during the time that they are main participants in stock markets. More details about multiple investors informationally connected in evolutionary local patterns can be detected by our work.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Systematic coarse-grained modeling of complexation between small interfering RNA and polycations

All-atom molecular dynamics simulations can provide insight into the properties of polymeric gene-delivery carriers by elucidating their interactions and detailed binding patterns with nucleic acids. However, to explore nanoparticle formation through complexation of these polymers and nucleic acids and study their behavior at experimentally relevant time and length scales, a reliable coarse-grained model is needed. Here, we systematically develop such a model for the complexation of small interfering RNA (siRNA) and grafted polyethyleneimine copolymers, a promising candidate for siRNA delivery. We compare the predictions of this model with all-atom simulations and demonstrate that it is capable of reproducing detailed binding patterns, charge characteristics, and water release kinetics. Since the coarse-grained model accelerates the simulations by one to two orders of magnitude, it will make it possible to quantitatively investigate nanoparticle formation involving multiple siRNA molecules and cationic copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

New water soluble heterometallic complex showing unpredicted coordination modes of EDTA

A mesoporous 3D polymeric complex (I) having formula ([Zr(IV)O-μ{sup 3}-(EDTA)Fe(III)OH]·H{sub 2}O){sub n} has been crystallized and characterized by various techniques. Single-crystal X-ray diffraction analysis revealed that complex (I) crystallized in chiral monoclinic space group Cc (space group no. 9) with unexpected coordination modes of EDTA and mixture of two transition metal ions. In this complex, the coordination number of Zr(IV) ion is seven where four carboxylate oxygen atoms, two nitrogen atoms, one oxide atom are coordinating with Zr(IV). Fe(III) is four coordinated and its coordination environment is composed of three different carboxylic oxygen atoms from three different EDTA and one oxygen atom of –OH group. The structure consists of 4-c and 16-c (2-nodal) net with new topology and point symbol for net is (3{sup 36}·4{sup 54}·5{sup 30})·(3{sup 6}). TGA study and XRPD pattern showed that the coordination polymer is quite stable even after losing water molecule and –OH ion. Quenching behavior in fluorescence of ligand is observed by complexation with transition metal ions is due to n–π⁎ transition. The SEM micrograph shows the morphology of complex (I) exhibits spherical shape with size ranging from 50 to 280 nm. The minimum N{sub 2} (S{sub BET}=8.7693 m{sup 2}/g) and a maximum amount of H{sub 2} (high surface area=1044.86 m{sup 2}/g (STP)) could be adsorbed at 77 K. From DLS study, zeta potential is calculated i.e. −7.94 shows the negative charges on the surface of complex. Hirshfeld surface analysis and fingerprint plots revealed influence of weak or non bonding interactions in crystal packing of complex. - Graphical abstract: The complex (I) crystallized with unexpected coordination modes of EDTA having 4-c, 16-c net with new topology and point symbol is (3{sup 36}·4{sup 54}·5{sup 30})·(3{sup 6}). TGA study and XRPD pattern proved its stability with high preference of H{sub 2} uptake by complex. - Highlights: • 3D complex having unexpected coordination modes of EDTA with Zr(IV) and Fe(III). • The structure consists of 4-c and 16-c (2-nodal) net with new topology. • Reasonable S{sub BET} (8.7693 m{sup 2}/g) but high H{sub 2} uptake (1044.86 m{sup 2}/g) due to limited pore size. • Quenching behavior due to n–π⁎ transition by complexation with transition metal ions. • From DLS study, zeta potential value is −7.94.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Universal trend of charge radii of even-even Ca–Zn nuclei

Radii of nuclear charge distributions carry information about the strong and electromagnetic forces acting inside the atomic nucleus. Whereas the global behavior of nuclear charge radii is governed by the bulk properties of nuclear matter, their local trends are affected by quantum motion of proton and neutron nuclear constituents. The measured differential charge radii δ$\langle$$r^{2}_{c}$$\rangle$ between neutron numbers N = 28 and N = 40 exhibit a universal pattern as a function of n = N – 28 that is independent of the atomic number. In this work, we analyze this remarkable behavior in even-even nuclei from calcium to zinc using two state-of-the-art theories based on quantified nuclear interactions: the ab initio coupled cluster theory and nuclear density functional theory. Both theories reproduce the smooth rise of differential charge radii and their weak dependence on the atomic number. By considering a large set of isotopic chains, we show that this trend can be captured by just two parameters: the slope and curvature of δ$\langle$$r^{2}_{c}$$\rangle$(n). We demonstrate that these parameters show appreciable model dependence, and the statistical analysis indicates that they are not correlated with any single model property, i.e., they are impacted by both bulk nuclear properties as well as shell structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Label Assist: Personalized Travel Models for Longitudinal Data Collection

Understanding travel behavior is crucial to transportation decarbonization. OpenPATH is an open-source mobility platform which collects and analyzes human travel behavior at the individual level. The mobile application passively senses trips and prompts users to label them. However, users find the labeling process burdensome; less than half the trips are typically labeled, making much of the data unusable in aggregate analyses of mobility patterns. Prior work has addressed the response fatigue challenge through automated mode inference using sensor data, but sensors cannot capture all aspects of travel behavior. We explore an alternative approach in which we leverage prior user input to predict travel choices in novel trips. We first explore trip clustering methods and develop a novel two-step pipeline using DBSCAN and SVMs to extract realistic geospatial clusters. We then propose two strategies to predict trip labels: (i) clustering trips and extrapolating labels for similar trips, and (ii) random forest classification. The random forest approach is able to achieve - $70-80% accuracy (purpose: 72%, mode: 79%, replaced mode: 81%). These novel approaches to trip classification allow us to increase the rate of user labeling by suggesting predicted labels to be verified by the user. Unlabeled trips can also contribute to aggregate analyses, using label predictions and their associated confidences as a substitute. While there exist other travel survey apps with the ability to infer travel choices, to our knowledge, this is the first paper to describe such a supervised system and rigorously evaluate it.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
NASA NTRS1998

A Search for Giant Convection Cells on the Sun

Giant convection cells (slow, long-lived cellular flows in the Sun's convection zone with typical diameters greater than about 100,000 km) have been the subject of many searches over the last 30 years. If such flows exist, they should play a key role in structuring the Sun's large scale magnetic field and in driving the large scale axisymmetric flows: the differential rotation and meridional circulation. Detailed observations of the flows in these cells may also allow us to better predict future magnetic field configurations and the solar activity associated with them. Line-of-sight velocity data from the Michelson Doppler Interferometer on the ESA/NASA Solar and Heliospheric Observatory provides us with new opportunities to search for giant cells. This data is free of any atmospheric distortion and has been obtained continuously without any day/night gaps for more than two months at a time. These two-month datasets are important because giant cells are expected to have lifetimes somewhat longer that the Sun's 27 day rotation period. Any reappearance of a flow pattern after 27 days would be an important confirmation of the existence of these cells. The approach taken in this search is to separate the giant cell velocity signal from the other, stronger velocity signals by using a spherical harmonic representation of the spatial structures and a fourier decomposition of the temporal behavior. Any giant cell signal should be characterized by low spatial wavenumbers with temporal frequencies appropriate to the solar rotation of these patterns.

Hathaway, David H.↗
DOE OSTI2023

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗
NASA NTRS1993

NASA/DoD Aerospace Knowledge Diffusion Research Project. Paper 31: The information-seeking behavior of engineers

Engineers are an extraordinarily diverse group of professionals, but an attribute common to all engineers is their use of information. Engineering can be conceptualized as an information processing system that must deal with work-related uncertainty through patterns of technical communications. Throughout the process, data, information, and tacit knowledge are being acquired, produced, transferred, and utilized. While acknowledging that other models exist, we have chosen to view the information-seeking behavior of engineers within a conceptual framework of the engineer as an information processor. This article uses the chosen framework to discuss information-seeking behavior of engineers, reviewing selected literature and empirical studies from library and information science, management, communications, and sociology. The article concludes by proposing a research agenda designed to extend our current, limited knowledge of the way engineers process information.

Pinelli, Thomas E.↗
DOE OSTI2022

XMM-Newton and TESS observations of the highly variable polar V496 UMa

We studied the temporal and spectral behavior of V496 UMa from the optical to the X-ray regimes. Methods. We used archival XMM-Newton and TESS observations obtained in 2017 and 2019, respectively, to perform a spectral and timing analysis of the highly variable magnetic CV. Results. The light curves of the TESS and XMM-Newton satellites reveal a double-humped pattern modulated with the periodicity of 91.058467 ± 0.00001 min. V496 UMa displays a two-pole accretion geometry in the high accretion state. X-ray spectra from these regions are composed of thermal plasma radiation and soft blackbody components with almost identical temperatures and a total accretion rate of $\dot{M}$ = 1.4(8) × 10 -11 M ⊙ yr -1 . The X-ray centers of the humps show longitudinal shifts of -18° and 4°, and shifts around photometric phase zero of -172° and -186°, for the main hump and second hump, respectively. The long-term ZTF light curves reveal high and low accretions states. Low-state ZTF and SDSS photometric data are consistent with an 0.8 M ⊙ white dwarf at 10 000 K and a main-sequence donor star with a spectral type of M5.0 at a Gaia determined distance of 758 pc. Conclusions. V496 UMa is a very bright polar in X-rays when it is in the high state. Due to its unusual geometric structure, mass accretion onto the second accretion pole is interrupted occasionally. This discontinuous behavior does not follow a certain pattern in time and has been observed so far only in the high state. The X-ray light curves display clear evidence of an accretion stream at the photometric phase of φ = 0.81, which does not show up in optical light curves. An accurate period was derived using the combined TESS and XMM-Newton data, which differs by 3.8 σ from published results.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Ionospheric convection response to slow, strong variations in a Northward interplanetary magnetic field: A case study for January 14, 1988

We analyze ionospheric convection patterns over the polar regions during the passage of an interplanetary magnetic cloud on January 14, 1988, when the interplanetary magnetic field (IMF) rotated slowly in direction and had a large amplitude. Using the assimilative mapping of ionospheric electrodynamics (AMIE) procedure, we combine simultaneous observations of ionspheric drifts and magnetic perturbations from many different instruments into consistent patterns of high-latitude electrodynamics, focusing on the period of northward IMF. By combining satellite data with ground-based observations, we have generated one of the most comprehensive data sets yet assembled and used it to produce convection maps for both hemispheres. We present evidence that a lobe convection cell was embedded within normal merging convection during a period when the IMF B(sub y) and B(sub z) components were large and positive. As the IMF became predominantly northward, a strong reversed convection pattern (afternoon-to-morning potential drop of around 100 kV) appeared in the southern (summer) polar cap, while convection in the northern (winter) hemisphere became weak and disordered with a dawn-to-dust potential drop of the order of 30 kV. These patterns persisted for about 3 hours, until the IMF rotated significantly toward the west. We interpret this behavior in terms of a recently proposed merging model for northward IMF under solstice conditions, for which lobe field lines from the hemisphere tilted toward the Sun (summer hemisphere) drape over the dayside magnetosphere, producing reverse convection in the summer hemisphere and impeding direct contact between the solar wind and field lines connected to the winter polar cap. The positive IMF B(sub x) component present at this time could have contributed to the observed hemispheric asymmetry. Reverse convection in the summer hemisphere broke down rapidly after the ratio absolute value of B(sub y)/B(sub z) exceeded unity, while convection in the winter hemisphere strengthened. A dominant dawn-to-dusk potential drop was established in both hemispheres when the magnitude of B(sub y) exceeded that of B(sub z) with potential drops of the order of 100 kV, even while B(sub z) remained northward. The latter transition to southward B(sub z) produced a gradual intensification of the convection, but a greater qualitative change occurred at the transition through absolute value of B(sub y)/B(sub z) = 1 than at at the transition through B(sub z) = 0. The various convection patterns we derive under northward IMF conditions illustrate all possibilities previously discussed in the literature: nearly single-cell and multicell, distorted and symmetric, ordered and unordered, and sunward and antisunward.

Knipp, D. J.↗
DOE OSTI2025

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2015

Direct fabrication of thin layer MoS{sub 2} field-effect nanoscale transistors by oxidation scanning probe lithography

Thin layer MoS{sub 2}-based field effect transistors (FET) are emerging candidates to fabricate very fast and sensitive devices. Here, we demonstrate a method to fabricate very narrow transistor channel widths on a single layer MoS{sub 2} flake connected to gold electrodes. Oxidation scanning probe lithography is applied to pattern insulating barriers on the flake. The process narrows the electron path to about 200 nm. The output and transfer characteristics of the fabricated FET show a behavior that is consistent with the minimum channel width of the device. The method relies on the direct and local chemical modification of MoS{sub 2}. The straightforward character and the lack of specific requirements envisage the controlled patterning of sub-100 nm electron channels in MoS{sub 2} FETs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1989

A design philosophy for multi-layer neural networks with applications to robot control

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Vadiee, Nader↗
NASA NTRS2012

Modeling Off-Nominal Behavior in SysML

Fault Management is an essential part of the system engineering process that is limited in its effectiveness by the ad hoc nature of the applied approaches and methods. Providing a rigorous way to develop and describe off-nominal behavior is a necessary step in the improvement of fault management, and as a result, will enable safe, reliable and available systems even as system complexity increases... The basic concepts described in this paper provide a foundation to build a larger set of necessary concepts and relationships for precise modeling of off-nominal behavior, and a basis for incorporating these ideas into the overall systems engineering process.. The simple FMEA example provided applies the modeling patterns we have developed and illustrates how the information in the model can be used to reason about the system and derive typical fault management artifacts.. A key insight from the FMEA work was the utility of defining failure modes as the "inverse of intent", and deriving this from the behavior models.. Additional work is planned to extend these ideas and capabilities to other types of relevant information and additional products.

Soil Moisture Active-Passive (SMAP) Mission↗