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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Do Dominant Ants Affect Secondary Productivity, Behavior and Diversity in a Guild of Woodland Ants?

The degree to which competition by dominant species shapes ecological communities remains a largely unresolved debate. In ants, unimodal dominance–richness relationships are common and suggest that dominant species, when very abundant, competitively exclude non-dominant species. However, few studies have investigated the underlying mechanisms by which dominant ants might affect coexistence and the maintenance of species richness. In this study, we first examined the relationship between the richness of non-dominant ant species and the abundance of a dominant ant species, Formica subsericea, among forest ant assemblages in the eastern US. This relationship was hump-shaped or not significant depending on the inclusion or exclusion of an influential observation. Moreover, we found only limited evidence that F. subsericea negatively affects the productivity or behavior of non-dominant ant species. For example, at the colony-level, the size and productivity of colonies of non-dominant ant species were not different when they were in close proximity to dominant ant nests than when they were away and, in fact, was associated with increased productivity in one species. Additionally, the number of foraging workers of only one non-dominant ant species was lower at food sources near than far from dominant F. subsericea nests, while the number of foragers of other species was not negatively affected. However, foraging activity of the non-dominant ant species was greater at night when F. subsericea was inactive, suggesting a potential mechanism by which some non-dominant species avoid interactions with competitively superior species. Gaining a mechanistic understanding of how patterns of community structure arise requires linking processes from colonies to communities. Our study suggests the negative effects of dominant ant species on non-dominant species may be offset by mechanisms promoting coexistence.

Formicidae↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling the non-Schmid crystallographic slip in MAX phases

We present a crystal plasticity constitutive relation for the description of experimentally observed non-Schmid crystallographic slip in a class of ternary carbides and nitrides commonly referred to as MAX phases. In the constitutive relation, we assume that the evolution of the slip system strength in MAX phases has two components – a classical component that depends on the Taylor cumulative shear strain and a non-Schmid component that depends on the stress normal to the slip plane. The non-Schmid crystal plasticity constitutive relation is then used to carry out finite element simulations of micropillar compression of single crystals of two MAX phases, Ti 2 AlC and Ti 3 AlC 2 . The finite element simulations not only quantitatively predict the stress – strain response of a wide range of crystallographic orientations of the micropillars but also rationalize the non-uniform deformation and the deformed shape of the micropillars observed in the experiments for the two materials. As a result, parametric studies are also carried out to quantify the role of the non-Schmid effect and understand the effects of key experimental parameters on the stress – strain response of the micropillars of the two MAX phases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microscopic Imprints of Learned Solutions in Tunable Networks

In physical networks trained using supervised learning, physical parameters are adjusted to produce desired responses to inputs. An example is an electrical contrastive local learning network of nodes connected by edges that adjust their conductances during training. When an edge conductance changes, it upsets the current balance of every node. In response, physics adjusts the node voltages to minimize the dissipated power. Learning in these systems is therefore a coupled double-optimization process, in which the network descends both a cost landscape in the high-dimensional space of edge conductances and a physical landscape—the power dissipation—in the high-dimensional space of node voltages. Because of this coupling, the physical landscape of a trained network contains information about the learned task. Here, we derive a structure-function relation for trained tunable networks and demonstrate that all the physical information relevant to the trained input-output relation can be captured by a tuning susceptibility, an experimentally measurable quantity. We supplement our theoretical results with simulations to show that the tuning susceptibility is correlated with functional importance and that we can extract physical insight into how the system performs the task from the conductances of highly susceptible edges. Our analysis is general and can be applied directly to mechanical networks, such as networks trained for protein-inspired function such as allostery.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of temperature and concentration on flow behaviour of reconstituted lactose and protein–rich dairy powders

To help with designing the drying process, this study investigated the flow behaviour of lactose and protein-rich reconstituted dairy powders at 25°C and 50°C. Lactose-rich samples, 50% dried whey (DW) and 60% whey protein concentrate (WPC35) did not follow the Herschel–Bulkley model because of presence of lactose crystals. Reconstituted 50% skim milk powder (SMP) and protein-rich dairy powders exhibited shear-thinning behaviour (n < 0.3). With increasing concentration, whey protein concentrate/isolate (WPC80/WPI) and micellar casein concentrate high-solid dispersions exhibited more shear-thinning behaviour (n < 0.4). Furthermore, understanding shear-thinning behaviour of lactose-rich and protein-rich reconstituted dairy powders will provide basis for optimising drying parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Data Repository for Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks.

These data support the manuscript "Multi-Objective Urban Observational Strategies: A risk-based framework for expanding flood sensor networks." These data are generated to allow water managers to reason about optimal locations to expand a flood observation system from multiple perspectives, specifically focusing on flood hazards, and population exposure to flooding. The data included are a) a shapefile of individual sensor locations b) a shapefile of river reach catchments, c) raster of FEMA flood likelihood layers d) shapefile of population locations and population socioeconomic characteristics. The code is written in R and includes all files necessary to generate the figures for the associated manuscript. Interactive maps of the final calculated maps of hazard, vulnerability, exposure, and risk are also included as html files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Foundational Science to Accelerate Nuclear Energy Innovation [Brochure]

The foundational science gaps inhibiting the advancement of nuclear energy technologies are identified and tackled in five priority research opportunities. These opportunities pave the way to accelerate the development and ultimately the adoption of new nuclear energy systems. They include the fundamental aspects of ion-electron interactions; novel properties of next-generation coolants and solvents; interfacial dynamics, not only in solids, but in other aspects of nuclear reactors; novel operando and in-situ monitoring and sensing; and artificial intelligence to accelerate condensed phases discovery. Building on the foundation established by previous BES workshops, these opportunities encompass recent advances in fundamental knowledge and focus on the experimental and computational methods needed to resolve major technical challenges for nuclear energy technologies. Through developing fundamental scientific insight as well as pushing the frontiers of modeling complex systems and probing the operation of materials and chemical systems in extreme environments, research motivated by the priorities identified here will further develop the promise, potential, and utilization of nuclear energy for a clean energy future. The PROs are as follows: (1) Master complex electronic structures to tailor thermochemical reactivity, transport, and microstructural evolution; (2) Interrogate and direct the physics and chemistry underpinning next-generation coolants and solvents; (3) Elucidate and control the underlying physics and chemistry of interfaces in complex nuclear environments; (4) Bridge multi-fidelity multi-resolution experiments, computational modeling, and data science to control dynamic behavior; and (5) Harness artificial intelligence to design inherently resilient condensed phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Deformation mechanisms of nanotwinned Al and binary Al alloys

The objective of this proposal is to investigate, at a fundamental level, the deformation mechanisms of nanotwinned (NT) Al alloys with high density twin boundaries (TBs) and stacking faults (SFs). Nanotwinned metals with low stacking fault energy (SFE), such as Cu and Ag, have shown outstanding strength and tensile ductility. Twin boundaries play a critical role to enhance the strength and work hardening ability of these metals and alloys, and thus lead to significant plasticity. Al alloys have ultra-high stacking fault energy, and thus are often considered to be nearly free from growth twins and SFs. However, our recent studies show that a significant number of nanotwins and 9R phase can be introduced in Al and certain Al alloys, and lead to high flow stresses.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Comparative Modal Analysis of Sieve Hardware Designs

The CMTB Thwacker hardware operates as a testbed analogue for the Flight Thwacker and Sieve components of CHIMRA, a device on the Curiosity Rover. The sieve separates particles with a diameter smaller than 150 microns for delivery to onboard science instruments. The sieving behavior of the testbed hardware should be similar to the Flight hardware for the results to be meaningful. The elastodynamic behavior of both sieves was studied analytically using the Rayleigh Ritz method in conjunction with classical plate theory. Finite element models were used to determine the mode shapes of both designs, and comparisons between the natural frequencies and mode shapes were made. The analysis predicts that the performance of the CMTB Thwacker will closely resemble the performance of the Flight Thwacker within the expected steady state operating regime. Excitations of the testbed hardware that will mimic the flight hardware were recommended, as were those that will improve the efficiency of the sieving process.

flight hardware↗
DOE OSTI2020

Data analysis and modeling pipelines for controlled networked social science experiments

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

People are like plutonium

An analogy is drawn between the study of human behavior and the study of plutonium to demonstrate that soft and hard sciences are more similar than different, making the distinction moot and unproductive. The studies of human behavior and plutonium follow a common scientific research cycle that aligns with Thomas Kuhn’s views of scientific change. This common research cycle provides evidence that the thought processes and methodologies required for success are congruent in the soft and hard sciences. The primary implication from this analogy is that scientists in all disciplines should eradicate the distinction between soft and hard sciences. Focusing on similarities rather than differences among researchers from different disciplines is necessary to enhance collective intelligence and the type of transdisciplinary collaboration required to tackle difficult sociotechnical problems. CCS Concepts: • Social and professional topics • User characteristics • Cultural characteristics.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1992

Human behavior and human performance: Psychomotor demands

The results of several experiments are presented in abstract form. These studies are critical for the interpretation and acceptance of flight based science to be conducted by the Behavior and Performance project. Some representative titles are as follow: External audio for IBM/PC compatible computers; A comparative assessment of psychomotor performance (target prediction by humans and macaques); Response path (a dependent measure for computer maze solving and other tasks); Behavioral asymmetries of psychomotor performance in Rhesus monkey (a dissociation between hand preference and skill); Testing primates with joystick based automated apparatus; and Environmental enrichment and performance assessment for ground or flight based research with primates;

Source record↗
NASA NTRSDate not supplied

Firesense: Supporting Operational Partners Through Co-Development

Fire is a natural disturbance and fundamental to many ecosystems, but, across the United States and many areas globally, fires have become more common, larger and more likely to occur at the same time. This has the potential to challenge resource allocation and response and requires coordinated integration of technology and tools at the spatial and temporal scales required by practitioners who make wildland fire management decisions. In the US wildfire is currently managed across state, federal, and tribal agencies who leverage various datasets to guide management decisions. FireSense, a NASA Science Mission Directorate project, aims to develop and deliver trailblazing technology and tools for use before, during, and after wildland fires by working together with land managers and practitioners. FireSense is focused on turning information into solutions by expanding partnerships and collaborations with operational agencies to inform and deliver data and technology to support decisions for wildland fire management. Through implementation across the US and with campaign activities in a variety of landscapes, coordinated research and development work will build upon adaptive and use-inspired approaches that can be put into operation. By leveraging and complementing partner activities through coordinated investment, we support a more comprehensive and cohesive response that can advance fire science to better understand fire behavior and effects through integrated measurement, monitoring and modeling. We present updates from in-progress technology development and field campaigns within the US which include sampling and application across scales with information from multiple sensors collocated with field measurements and highlighting the importance of cross-scale observations during the fire lifecycle. Coordinated investment in new science and technology for the complete fire lifecycle supports a comprehensive and cohesive fire response that help to overcome barriers and anticipate and manage the new reality of extreme fires in a warming world.

Jacquelyn Shuman↗