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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A Role for MST Neurons in Heading Estimation

A template model of human visual self-motion perception, which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions. We tested the model detectors with stimuli used by others in single-unit studies. The detectors showed emergent properties similar to those of MST neurons: (1) Sensitivity to non-preferred flow; Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow, and (2) Position invariance; The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields. It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Stone, L. S.↗
NASA NTRS2004

Petri Nets as Modeling Tool for Emergent Agents

Emergent agents, those agents whose local interactions can cause unexpected global results, require a method of modeling that is both dynamic and structured Petri Nets, a modeling tool developed for dynamic discrete event system of mainly functional agents, provide this, and have the benefit of being an established tool. We present here the details of the modeling method here and discuss how to implement its use for modeling agent-based systems. Petri Nets have been used extensively in the modeling of functional agents, those agents who have defined purposes and whose actions should result in a know outcome. However, emergent agents, those agents who have a defined structure but whose interaction causes outcomes that are unpredictable, have not yet found a modeling style that suits them. A problem with formally modeling emergent agents that any formal modeling style usually expects to show the results of a problem and the results of problems studied using emergent agents are not apparent from the initial construction. However, the study of emergent agents still requires a method to analyze the agents themselves, and have sensible conversation about the differences and similarities between types of emergent agents. We attempt to correct this problem by applying Petri Nets to the characterization of emergent agents. In doing so, the emergent properties of these agents can be highlighted, and conversation about the nature and compatibility of the differing methods of agent creation can begin.

Bergman, Marto↗
NASA NTRS2013

Unifying Human Centered Design and Systems Engineering for Human Systems Integration

Despite the holistic approach of systems engineering (SE), systems still fail, and sometimes spectacularly. Requirements, solutions and the world constantly evolve and are very difficult to keep current. SE requires more flexibility and new approaches to SE have to be developed to include creativity as an integral part and where the functions of people and technology are appropriately allocated within our highly interconnected complex organizations. Instead of disregarding complexity because it is too difficult to handle, we should take advantage of it, discovering behavioral attractors and the emerging properties that it generates. Human-centered design (HCD) provides the creativity factor that SE lacks. It promotes modeling and simulation from the early stages of design and throughout the life cycle of a product. Unifying HCD and SE will shape appropriate human-systems integration (HSI) and produce successful systems.

Boy, Guy A.↗
NASA NTRS2013

PROcess Based Diagnostics PROBE

Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

PROBE↗
NASA NTRS2018

Engineering Elegant Systems: Postulates, Principles, and Hypotheses of Systems Engineering

Definition: System Engineering is the engineering discipline which integrates the system functions, system environment, and the engineering disciplines necessary to produce and/or operate an elegant system; Elegant System - A system that is robust in application, fully meeting specified and adumbrated intent, is well structured, and is graceful in operation. Primary Focus: System Design and Integration: Identify system couplings and interactions; Identify system uncertainties and sensitivities; Identify emergent properties; Manage the effectiveness of the system. Engineering Discipline Integration: Manage flow of information for system development and/or operations; Maintain system activities within budget and schedule. Supporting Activities: Process application and execution.

Watson, Michael D.↗
NASA NTRS2019

Ongoing Breakthroughs in Convective Parameterization

While the increase of computer power mobilizes a part of the community towards models with explicit convection or based on machine learning, we review the part of the literature dedicated to convective parameterization development for large-scale forecast and climate models. Recent findings: Many developments are underway to overcome endemic limitations of traditional convective parameterizations, either in unified or multi-object frameworks: scale-aware and stochastic approaches, new prognostic equations or representations of new components such as cold pools. Understanding their impact on the emergent properties of a model remains challenging, due to subsequent tuning of parameters and the limited understanding given by traditional metrics. Summary: Further effort still needs to be dedicated to the representation of the life cycle of convective systems, in particular their mesoscale organization and associated cloud cover. The development of more process-oriented metrics based on new observations is also needed to help quantify model improvement and better understand the mechanisms of climate change.

parameterizations for large-scale models↗
NASA NTRS2022

Laser Patterning Assisted Devitrification and Domain Engineering of Amorphous and Nanocrystalline Alloys

We have investigated laser-patterning and devitrification as a novel method to realize emergent properties in modified regions at the ribbon surface consisting of periodic localized laser spots thermally treated under rapid heating and cooling conditions. Fe-based amorphous ribbons were annealed for systematically varied laser power. Extremely high heating and cooling rates on the order of 10(exp 8)-10(exp 10)K/s have been estimated by finite element analysis simulations. Observations suggest surface melting followed by rapid solidification fast enough to quench and form an amorphous structure upon cooling. Diffusion of heat occurs from the laser irradiated surface region so that a finite volume of material surrounding this region rises in temperature above the crystallization temperature relevant for conventional isothermal annealing experiments. The underlying mechanism of laser annealing and consequences of heat transients involved are discussed in terms of impacts upon micro/nanostructure, residual stresses, and magnetic domain structure surrounding the laser irradiated region. The study illustrates the potential to exploit spatially optimized phase transformations in a scalable manufacturing process of amorphous and nanocrystalline alloys to locally access otherwise inaccessible extreme heating and cooling rates.

Amorphous ribbons↗
NASA NTRS2022

Should’ve Could’ve: Progress in the Systems Engineering of the Mars2020 On-Board Planner

Mars rover operations has traditionally controlled behavior using meticulously compiled, so-called “Master” sequences that enforce deterministic timing and ordering of activities. While the approach is effective at managing risk and complexity, it can also be inefficient. Extended operations of the Mars2020 rover envisions a fundamentally different scheduling and execution approach. Atomic activities are constrained by mission operators in time, resource usage, and a structure of dependencies. The rover flight software will create and re-create schedules, responding to available energy, data volume, actual activity durations and execution status, observed temperatures, and other on-board state. Schedules are expected to change substantially in the course of execution. The solution space is prohibitively large and probabilistic in nature. A range of emergent behavior is accessible depending on the interaction between actual on-board state and a given formulation of constraints. For years, the specification and implementation of this capability have been considered and refined, as testing and analysis have mapped the contours of the system. Many concepts that could have been adopted were rejected, and in some cases, emergent properties have been exposed and beaten back with approaches to steer the behavior. This paper discusses some of the design history and underlying reasoning in the systems engineering of the first autonomous activity planner on Mars.

Kuhn, Stephen R↗
NASA NTRSDate not supplied

Foundation AI Models for Science

Foundation Models (FM) are AI models that are designed to replace a task or an application specific model. These FM can be applied to many different downstream applications. These FM are trained using self supervised techniques and can be built on any type of sequence data. The use of self supervised learning removes the hurdle for developing a large labeled dataset for training. Most FM use transformer architecture utilizes the notion of self attention which allows the network to model the influence of distant data points to each other both in space and time. The FM models exhibit emergent properties that are induced from the data. FM can be an important tool for science. The scale of these models results in better performance for different downstream applications and these applications show better accuracy over models built from scratch. FM drastically reduces the cost of entry to build different downstream applications both in time and effort. FM for selected science datasets such as optical satellite data, can accelerate applications ranging from data quality monitoring, feature detection and prediction. FM can make it easier to infuse AI into scientific research by removing the training data bottleneck and increasing the use of science data.

Manil Maskey↗
NASA NTRS2024

Experimentally Modeling the Emergence of Prebiotically Plausible Phospholipid Vesicles

The prebiotic emergence of protocells is an important part of any origins of life scenario. Although fatty-acid-based vesicles are well studied, how they transitioned to phospholipid vesicles is uncertain. Herein, we show that cyclic-phospholipids formed from fatty acids and glycerol could have played a role by generating a heterogeneous library of vesicles with diverse morphologies and tolerance to a range of metal ions, temperature, and pH. The cyclic phosphate moiety facilitates the natural emergence of vesicles composed of diacyl-phospholipids to become part of the chemical evolutionary process. Competing emergent properties of the various systems (facilitated by additives) could have led to an early preference of the sn-1,2-acyl-substitution on the glycerol backbone coincidental with extant biology. Thus, cyclic-phospholipids could have played a significant role not only in early prebiotic protocellular chemistry but also in facilitating the chemical evolution of protocells from the structurally simple to the functionally more complex.

Sunil Pulletikurti↗
NASA NTRSDate not supplied

A Safety-Driven Approach to Exploring and Comparing Air Traffic Management Concepts for Enabling Urban Air Mobility

There is broad recognition that the high tempo and density of Urban Air Mobility (UAM) operations will require identifying new Air Traffic Management (ATM) concepts to safely integrate UAM air traffic into the airspace alongside existing air traffic. However, the simulation models used to compare ATM concepts today are difficult to apply during the early stages of concept development and do not offer enough support in identifying potential new concepts. In addition, they have limited ability to evaluate ATM concepts in terms of safety, security, and other key emergent properties. Instead of using simulation to evaluate ATM concepts, this paper demonstrates how a safety-driven systems engineering approach based on Systems-Theoretic Accident Model and Processes (STAMP) can be used to design properties such as safety into an ATM system from the earliest stages of development. Using a hazard analysis technique called Systems-Theoretic Process Analysis (STPA), system requirements and the desired ATM behavior are derived. As an example, two possible ATM concepts to implement that behavior are compared to identify their safety-related benefits and tradeoffs. This new approach enables (1) systematic exploration of alternative ATM concepts and (2) identification of the safety-related tradeoffs between concepts as early as possible in the development process.

system safety↗
NASA NTRSDate not supplied

State of the Art and Practice for Equity in Urban Air Mobility

Traditionally, new modes of transportation in the United States have benefited upper social classes at the expense of underrepresented and lower socioeconomic classes. Several recent studies in transportation have explored this disparity, and research has highlighted factors that contribute to transportation equity. In this effort, we will examine this previous work as it applies to the broader, current transportation system. We will use our literature search to highlight and educate the current emerging aviation stakeholders on equity strategies that are directly applicable to these novel operations. We will also use our literature research to make informed recommendations for experiments and data collection that will increase our understanding about how these new aviation concepts can be encouraged to provide equity as an emergent property.

transportation equity↗
DOE OSTI2025

A Measurement of the Neutron Electromagnetic Form Factor Ratio from a Rosenbluth Technique with Simultaneous Detection of Neutrons and Protons

The internal structure of protons and neutrons provides insight into both the dynamical behavior of the constitute quarks and gluons, and emergent properties of the nucleons (such as mass, spin, and electromagnetic distributions). Elastic electron-nucleon scattering can probe the elastic electromagnetic form factors of the nucleon. The electric and magnetic form factors, respectively, encode information about the internal charge and magnetization distributions within the nucleon. Precision data for these form factors, over a broad range of the four-momentum transfer squared, Q^2, can benchmark theoretical models describing the strong interaction of nuclear physics. The Super BigBite Spectrometer (SBS) program in Hall A at Jefferson Lab, is a series of high-precision experiments which seek to significantly extend the Q^2 reach of previous data for the nucleon electromagnetic form factors. The first two experiments of this program are known as G_M^n and the neutron Two Photon Exchange (nTPE) and the data were collected from October 2021 to February 2022. Both experiments were conducted with the simultaneous measurement of D(e,e'n) and D(e,e'p) reactions for quasi-elastic electron-deuteron scattering. The scattered electrons were detected in the BigBite Spectrometer, which features multiple large-acceptance Gas Electron Multiplier (GEM) detectors. The Super BigBite Spectrometer provided simultaneous detection of scattered nucleons, and utilized a large acceptance dipole magnet and Hadron Calorimeter (HCal). The G_M^n experiment provides precision measurements of the neutron magnetic form factor, via the ratio method, over a Q^2 range of 3.0 to 13.5 (GeV/c)2. From this data analysis, preliminary values for G_M^n/µ_n G_D are extracted. For Q^2=4.48 (GeV/c)2 we find G_M^n/µ_n G_D=0.9546±0.0132 and for Q^2=4.476 (GeV/c)2 we find G_M^n/µ_n G_D=0.9563±0.0110. These preliminary G_M^n/µ_n G_D values are more precise than existing world data in this Q^2 regime and are consistent with the most recent parameterization of the G_M^n/µ_n G_D world data. The nTPE experiment provides a first measurement of the neutron Rosenbluth Slope and seeks to quantify the two-photon exchange(TPE) contribution to elastic electron-neutron scattering at a fixed Q^2=4.5 (GeV/c)2 with two different beam energies and scattering angle values. For data of the proton form factor ratio, µ_p G_E^p/G_M^p, significant discrepancies exist between values obtained from Rosenbluth Separation and polarization transfer measurement, particularly at large Q^2, and TPE contributions are thought to resolve this discrepancy. The impacts of TPE contributions have not yet been experimentally established for the neutron. From the data analysis presented in this dissertation, a preliminary result for the neutron Rosenbluth Slope is found as S^n=(G_E^n )^2/t_n (G_M^n )^2=0.0916±0.0476 for Q^2=4.48 (GeV/c)2. This value of the neutron Rosenbluth Slope is consistent with the world data extrapolation and the absence of large TPE corrections.

Wertz, Ezekiel [Thomas Jefferson National Accelera↗
DOE OSTI2025

Two-dimensional hydrodynamic viscous electron flow in annular Corbino rings

The concept of fluidic viscosity is ubiquitous in condensed-matter systems hosting a continuum where macroscopic properties can emerge. While an important property of liquids and some solids, only recently was the viscosity of an electron shown to play a role in electronic transport experiments. In this Letter, we present nonlocal electronic transport measurements in concentric annular rings formed in high-mobility two-dimensional electron gases, and the resulting data show that viscous hydrodynamic flow can occur far away from the source-drain current region. Our conclusion of viscous electronic transport is further corroborated by simulations of the Navier-Stokes equations that are found to be in agreement with our measurements below T = 1 K . Finally, this work emphasizes the key role played by viscosity via electron-electron ( e − e ) interaction even when the electronic transport is restricted radially, and for which it should have played no major role. Published by the American Physical Society 2025

Vijayakrishnan, Sujatha (ORCID:0009000080933182)↗
NASA NTRS2020

High Spectral Resolution Datasets of in Situ Aquatic Inherent and Apparent Optical Properties

Light emerging from natural water bodies and measured by remote sensing radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities to characterize aquatic ecosystems. Such upcoming missions include NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem PACE Mission; the NASA Surface Biology and Geology observable mission; and NASA Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) - Next Generation airborne missions. In anticipation of these missions, we present a dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP/AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland water, estuaries and oceans. Specific in situ measurements include particulate absorption, particulate attenuation, non-algal particulate or detritus absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, total backscatter, remote sensing reflectance, and irradiance reflectance. The dataset can be downloaded from PANGAEA: (https://www.pangaea.de/TBD ).

K A Casey↗
DOE OSTI2021

Dynamic Mixing Behaviors of Ionically Tethered Polymer Canopy of Nanoscale Hybrid Materials in Fluids of Varying Physical and Chemical Properties

An emerging area of sustainable energy and environmental research is focused on the development of novel electrolytes that can increase the solubility of target species and improve subsequent reaction performance. Electrolytes with chemical and structural tunability have allowed for significant advancements in flow batteries and CO 2 conversion integrated with CO 2 capture. Liquid-like nanoparticle organic hybrid materials (NOHMs) are nanoscale fluids that are composed of inorganic nanocores and an ionically tethered polymeric canopy. NOHMs have been shown to exhibit enhanced conductivity making them promising for electrolyte applications, though they are often challenged by high viscosity in the neat state. In this study, a series of binary mixtures of NOHM-I-HPE with five different secondary fluids, water, chloroform, toluene, acetonitrile, and ethyl acetate, were prepared to reduce the fluid viscosity and investigate the effects of secondary fluid properties (e.g., hydrogen bonding ability, polarity, and molar volume) on their transport behaviors, including viscosity and diffusivity. We report our results revealed that the molecular ratio of secondary fluid to the ether groups of Jeffamine M2070 ($λ_{\text{SF}}$) was able to describe the effect that secondary fluid has on transport properties. Our findings also suggest that in solution, the Jeffamine M2070 molecules exist in different nanoscale environments, where some are more strongly associated with the nanoparticle surface than others, and the conformation of the polymer canopy was dependent on the secondary fluid. This understanding of the polymer conformation in NOHMs can allow for the better design of an electrolyte capable of capturing and releasing small gaseous or ionic species.

25 ENERGY STORAGE↗
DOE OSTI2023

US National Institutes of Health Prioritization of SARS-CoV-2 Variants

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. Here, the group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

60 APPLIED LIFE SCIENCES↗