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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Emerging technologies and radical collaboration to advance predictive understanding of watershed hydrobiogeochemistry

Increasing population and resource-intensive lifestyles are driving enhanced demands for clean water, food, and energy. In parallel, land-use change, climate change, and perturbations—including drought, floods, fires, and early snowmelt—are significantly reshaping interactions within watersheds throughout the world. While watersheds are the Earth's key functional unit for assessing and managing water resources, hydrological processes in watersheds also mediate biogeochemical interactions that support terrestrial life on Earth (Kaushal, Gold, Bernal, & Tank, 2018; National Research Council, 2012). Although society is dependent upon clean water availability, tractable prediction of watershed hydrobiogeochemical behavior, including watershed response to perturbations, remains a challenge. Central to the challenge are complex, multiscale interactions between plants, microorganisms, organic matter, minerals, dissolved constituents, and migrating fluids, which occur within and across bedrock-to-canopy compartments and along extensive lateral gradients of a watershed. Several recent community reports have synthesized formidable challenges associated with watershed science and technology (AGU, 2018; Blöschl et al., 2019). Here, we discuss emerging technologies and collaboration modes that are critical for developing generalizable insights about and predictive understanding of complex watershed hydrobiogeochemical behavior, which are important for underpinning optimized natural resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗
DOE OSTI2020

Real-Time Implementation of Smart Wireless Charging of On-Demand Shuttle Service for Demand Charge Mitigation

This paper presents a smart charge management strategy for an on-demand electric shuttle operating at the National Renewable Energy Laboratory (NREL) campus and supported by an inductive charger at the vehicle's waiting spot. A new control algorithm has been proposed for mitigating the demand charges incurred from the wireless charger. It monitors the shuttle, wireless charger, renewable energy generation, and other loads and regulates charging behavior for demand charge mitigation. Within the control algorithm, an energy prediction is made to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller is designed and optimized using a Simulink model for the entire system. It is then implemented and tested in real time at the NREL campus using online cloud services. Two vehicle-use cases' charge-sustaining and charge-depletion operation' are tested under different campus power profiles and drive cycles to assess the controller's performance. In this work, the proposed controller showed a robust performance under different driving scenarios, with high correlation between simulation and experimental data. The results show that proper demand response can be achieved, with an average of 94% reduction of charging loads during peak demand events.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Supernova Explosions of the Lowest-mass Massive Star Progenitors

Abstract We here focus on the behavior of supernovae that technically explode in 1D (spherical symmetry). When simulated in 3D, however, the outcomes of representative progenitors of this class are quite different in almost all relevant quantities. In 3D, the explosion energies can be 2 to 10 times higher, and there are correspondingly large differences in the 56 Ni yields. These differences between the 3D and 1D simulations reflect in part the relative delay to explosion of the latter and in the former the presence of protoneutron star convection that boosts the driving neutrino luminosities by as much as ∼50% at later times. In addition, we find that the ejecta in 3D models are more neutron-rich, resulting in significant weak r -process and 48 Ca yields. Furthermore, we find that in 3D the core is an interesting, though subdominant, source of acoustic power. In summary, we find that though a model might be found theoretically to explode in 1D, one must perform supernova simulations in 3D to capture most of the associated observables. The differences between 1D and 3D models are just too large to ignore.

Astronomy & Astrophysics↗
DOE OSTI2026

Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study

Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries. To unravel the coupled chemomechanical processes that govern fracture in LLZO under external loading, we carry out large-scale molecular-dynamics simulations with a validated machine-learning force field. Our results demonstrate that triaxial stresses at crack flanks trigger a localized cubic-to-tetragonal phase transformation, which is accompanied by Li-ion rearrangement. The emergent tetragonal domains feature lattice contraction normal to the fracture plane, imposing coherent misfit strains that provide an additional driving force for further crack propagation. Crucially, introducing Li deficiencies stabilizes the cubic phase, postponing the phase transition and thereby delaying fracture initiation. These findings highlight the role of intrinsic phase instability in dictating LLZO's fracture resistance and its critical connection to local Li concentration. This chemomechanical coupling points toward targeted strategies to enhance the mechanical robustness of garnet electrolytes, including tuning Li content, ensuring dopant homogeneity, and refining processing protocols.

Materials science↗
DOE OSTI2023

High-frequency phonons drive large phonon-drag thermopower in semiconductors at high carrier density

It has been well established that (i) the thermopower of semiconductors can be enhanced through a phe- nomenon known as the drag effect, and (ii) the drag enhancement involves only low-frequency acoustic phonons and benefits from low electron densities and low temperatures. Using first-principles calculations we show that large drag enhancements to the thermopower are possible at high carrier density even at room temperature and arise from high-frequency acoustic phonons. A fascinating example is cubic boron arsenide (BAs) for which the calculated room temperature drag enhancement of the thermopower exceeds an order of magnitude at a high hole density of 10 21 cm –3 . This remarkable behavior stems from the simultaneously weak phonon-phonon and phonon-hole scattering of the high-frequency phonons in BAs that become drag active at high carrier densities through electron-phonon interactions. Furthermore, this work advances our understanding of coupled electron-phonon nanoscale transport and introduces an unexpected paradigm for achieving large thermopowers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effect of microstructure on fatigue crack propagation in additive manufactured nickel-based superalloy Haynes 282: an experiment and crystal plasticity study

Haynes 282 is a γ' precipitation-strengthened nickel-based superalloy known for its exceptional high-temperature creep resistance and excellent fabricability. Recent advancements in powder-bed fusion-based additive manufacturing (PBF-AM) have enabled the fabrication of Haynes 282 with accurate, site-specific control of the grain orientation and morphology at the microscale. This ability opens up new avenues for microstructure design, to improve the material’s fatigue crack resistance and service life. This paper investigates the fatigue crack growth behavior of hybrid microstructure Haynes 282 fabricated via PBF-AM. Previous experiments revealed a higher crack propagation rate in the coarse columnar-grained microstructural regions when compared against fine-grained areas. Here, a strain gradient crystal plasticity model was adapted to study the fracture-related mechanical fields at the crack tip in the two microstructures. The simulation results showed a consistent influence of grain structure and texture on crack propagation, as was seen in the experiment. The model analysis revealed higher crack propagation driving force along crack direction in the coarse-grained sharply textured microstructure and higher driving force for crack kinking in fine-grained more diffusely textured microstructure, which is ascribed to the combined effect of yield stress, hardening rate, texture and grain morphology. The presented modeling approach will facilitate the development of the AM-based accurate microstructure design by deepening the fundamental study in AM-specific microstructure-properties relations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Upper-Hybrid Waves Driven by Meandering Electrons Around Magnetic Reconnection X Line

Magnetic reconnection is a fundamental process in collisionless space plasma environment, and plasma waves relevant to the kinetic interactions can have a significant impact on the multiscale behavior of reconnection. Here, we present Magnetospheric Multiscale (MMS) observations during an encounter of an X line of symmetric magnetic reconnection in the magnetotail. The X line is characterized by reversals of ion and electron jets and electromagnetic fields, agyrotropic electron velocity distribution functions (VDFs), and an electron-scale current sheet. MMS observe large-amplitude nonlinear upper-hybrid (UH) waves on both sides of the neutral line, and the wave amplitudes have highly localized distribution along the normal direction. Here, the inbound meandering electrons drive the UH waves, releasing the free energy stored from the reconnection electric field along the meandering trajectories. The interaction between the meandering electrons and the UH waves may modify the balance of the reconnection electric field around the X line.

58 GEOSCIENCES↗
DOE OSTI2026

Reverse segregation and self-organization in inclined chute flows of bidisperse granular mixtures

In the usual segregation scenario for stable inclined chute flows of bidisperse mixtures of fine and coarse spherical particles, coarse particles rise toward the free surface, forming a coarse-rich region atop the flowing pile. Beyond a threshold coarse-to-fine diameter ratio of approximately 4, conversely, the weight of the coarse particles exceeds the segregation driving forces, causing individual coarse particles to sink within the pile and producing a reversed segregation state. However, an understanding of the collective evolution of the pile structure is still lacking when the particle diameter ratio exceeds 4 and the coarse-particle mass fraction is appreciable. To explore this broadly bidisperse limit, we perform discrete element method simulations considering mean particle diameter ratios of up to 8 and coarse-particle mass fractions spanning 0.1 to 0.9. The steady-state flow profiles reveal several intriguing behaviors that depend on the diameter ratio and mass fraction. These include a previously identified transition from usual to reverse segregation and a newfound tendency to self-organize into alternating coarse- and fine-rich particle layers stacked along the shear gradient direction, with layer thickness dictated by the coarse-particle diameter. A fuller understanding of segregation at this scale could pave the way for enhanced mixing or demixing techniques at the commercial scale.

granular flow↗
DOE OSTI2021

Elucidating and predicting the dynamic evolution of water and land systems due to natural and energy-related forcings

Focal Area(s): 3. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI; & 1. Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: Interactions between water, land, and energy systems are complex and occur on a variety of scales, ranging from local to basinal to regional. Accurately predicting the behavior of ground water and surface water systems for 5-10 years and beyond requires an understanding of the current system and the ability to model both the natural system at scale and human-induced forcings related to energy and other activities. Artificial intelligence and machine learning (AI/ML) combined with modern compilation and integration efforts for U.S. groundwater and surface water systems present potential solutions to bolstering detailed physics-based models of these systems. Big data tied with ML and physics-based modeling can drive breakthroughs in understanding the earth system, but research is often impeded by data access (e.g., privacy issues), quality, formats, gaps, multi-source, multi-scale, integration, and spatiotemporal challenges. Effective integration of real data and simulated (synthetic) data that fill gaps is critical. Overcoming these complex data and model integration challenges will enable a transformational approach to acquiring enhanced understanding of environmental systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

An interacting loop model for solar flare bursts

A schematic model is presented which attempts to explain the quasi-periodic behavior (on a timescale of less than or approximately equal to 10 s) frequency observed in solar hard X-ray bursts. It is shown how, as a result of the strong heating produced during a solar flare burst, the local gas pressure can transiently attain very large values in regions corresponding to the upper preflare chromosphere. The effectiveness of the surrounding magnetic field at confining this high pressure plasma is therefore reduced and the flaring loop becomes free to expand laterally. In so doing it may drive magnetic field lines into neighboring, non-flaring, loops in the same active region, causing magnetic reconnection to take place and triggering another flare burst. The features of this interacting loop model are found to be in good agreement with the energetics and time structure of flare-associated solar hard X-ray bursts.

Emslie, A. G.↗
NASA NTRSDate not supplied

Numerical analysis of Microgravity Bubble Separation in Open Channels with ISS Bemchmarks

Spacecraft fluid systems often require specific considerations to operate in a manner similar to those on Earth. For instance, an open wedge shaped channel can serve as a pathway for passively separating bubbles from a liquid in a two phase flow, analogous to buoyancy effects on Earth. As the bubbles merge within the channel, they become increasingly confined in the wedge, driving them upwards and outwards toward the free surface due to capillary forces. These same forces ensure coalescence and allow the bubbles to escape through the free surface. However, in low gravity environments, a challenge arises when bubbles are not sufficiently large. Under such conditions, the bubbles tend to follow trajectories near their inscribed elevations, never fully leaving the liquid. Such unseparated bubbles can lead to downstream pump failure, cavitation, flow instabilities, dryout, and other adverse effects aboard spacecraft. Understanding and exploiting the underlying mechanisms behind this behavior is crucial for enhancing the reliability of passive capillary fluids management in space applications, including cryogenic and storable fuels transport, thermal fluids circulation, water recycling for life support, plant watering systems, and more. The joint German Aerospace Center (DLR) and NASA Capillary Channel Flow (CCF) experiment conducted on the International Space Station has provided an extensive publicly available database documenting such phenomena (https://science.nasa.gov/physical sciences informatics psi). Leveraging this resource, we aim to establish benchmarks for our numerical investigation of zero gravity bubbly two phase flow in open wedge channels. Specifically, we seek to quantitatively understand the mechanisms governing ‘inscribed’ bubble motion, considering the apparent interplay of two competing forces: Saffman lift (causing upward/outward motion) and the Magnus effect (causing downward/inward motion). Our cross cutting findings directly inform the development of robust passive phase separation methods within spacecraft plumbing systems.

bubble↗
NASA NTRS1999

Dynamical and Chemical Behavior of the Lower Stratosphere and Interactions with the Troposphere

Equivalent-barotropic calculations, in tandem with Lagrangian analyses, reveal how changes of total ozone follow from vertical and horizontal transport by planetary waves. Those calculations also throw light on how diabatic motions comprising the Brewer-Dobson circulation develop from quasi-horizontal advection by planetary waves. Potential temperature along a material surface indicates organized subsidence inside the polar-night vortex, resembling tracer observations from UARS. Lagrangian histories illustrate that this sinking motion follows in large part from parcels being driven out of thermodynamic equilibrium by planetary waves, especially at high latitudes. Irreversible heat transfer then produces a net drift of air across isentropic surfaces as parcels orbit about the displaced vortex. By driving mean-meridional overturning in the stratosphere, this downward drift is ultimately responsible for transferring ozone from the tropics to the extratropical lower stratosphere. It also introduces horizontal structure into the distribution of total ozone, which surfaces clearly in ozone trends. High-resolution global cloud imagery constructed from 6 satellites simultaneously observing the Earth was used to investigate the spectrum of equatorial waves generated by tropical convection and propagating vertically into the stratosphere. The results indicate that temperature variability is dominated by planetary-scale equatorial waves like the Kelvin mode, which agrees with satellite observations of the tropical stratosphere. However, the Kelvin mode accounts for only about 30 - 50% of the eastward momentum flux radiating into the stratosphere, the remainder coming from gravity waves. An algorithm was developed to determine 3-dimensional atmospheric motion from satellite tracer measurements. Based on Lagrangian constraints, the algorithm circumvents limitations of the traditional scheme for inferring motion from temperature measurements and determines the circulation in the tropics as reliably as elsewhere. A study of deep convection revealed that the highest towers (those penetrating into stratospheric air and controlling tropopause height and composition through convective mixing) occur in close association with the diurnal cycle of convection. Clouds colder than 220 K develop almost entirely in association with the diurnal cycle of convection over tropical landmasses and substantially in association with it even over maritime regions.

Salby, Murry L.↗
DOE OSTI2025

Microstructure and mechanical behavior of laser remelted amorphous Al-Ni-La welds

To explore the feasibility of using laser powder bed fusion systems to print bulk amorphous Al alloys, a single autogenous weld produced by laser remelting on a cast Al-5La-9Ni (at.%) alloy was studied for its microstructure and mechanical behavior. The solidification rates experienced by material within the welds were high enough to produce entirely amorphous regions within the welds. Welds were characterized using SEM, STEM, and APT and were found to contain Ni-rich amorphous clusters. Micropillar compression tests were used to assess mechanical properties of the welds and found that all of the amorphous regions exhibited yield strengths around 1 GPa. In conclusion, these results are discussed in the context of diffusivity of Ni and rare earth elements in liquid, glass forming ability, thermodynamic driving force for phase formation during solidification, free volume concentrations in bulk metallic glasses, and cluster-related softening.

APT↗
DOE OSTI2021

Chaotic Dynamics Driven by Particle-Core Interactions

High-intensity beams in modern linacs are frequently encircled by diffuse halos, which drive sustained particle losses and result in gradual degradation of accelerating structures. In large part, the growth of halos is facilitated by internal space-charge forces within the beams, and detailed characterization of this process constitutes an active area of ongoing research. A partial understanding of dynamics that ensue within space-charge dominated beams is presented by the particle-core interaction paradigm – a mathematical model wherein single particle dynamics, subject to the collective potential of the core, are treated as a proxy for the broader behavior of the beam. In this work, we investigate the conditions for the onset of large-scale chaos within the framework of this model, and demonstrate that the propensity towards stochastic evolution is strongly dependent upon the charge distribution of the beam. In particular, we show that while particle motion within a uniformly charged beam is dominantly regular, rapid deterministic chaos readily arises within space-charge dominated Gaussian beams. Importantly, we find that for sufficiently high values of the beam’s space charge and beam pulsation amplitude, enhanced chaotic mixing between the core and the halo can lead to an enhanced radial diffusion of charged particles. We explain our results from analytic grounds by demonstrating that chaotic motion is driven by the intersection of two principal resonances of the system, and derive the relevant overlap conditions. Additionally, our analysis illuminates a close connection between the mathematical formulation of the particle-core interaction model and the Andoyer family of integrable Hamiltonians

43 PARTICLE ACCELERATORS↗
NASA NTRS2006

The Sugar Model: Autocatalytic Activity of the Triose-Ammonia Reaction

Reaction of triose sugars with ammonia under anaerobic conditions yielded autocatalytic products. The autocatalytic behavior of the products was examined by measuring the effect of the crude triose-ammonia reaction product on the kinetics of a second identical triose-ammonia reaction. The reaction product showed autocatalytic activity by increasing both the rate of disappearance of triose and the rate formation of pyruvaldehyde, the product of triose dehydration. This synthetic process is considered a reasonable model of origin-of-life chemistry because it uses plausible prebiotic substrates, and resembles modern biosynthesis by employing the energized carbon groups of sugars to drive the synthesis of autocatalytic molecules.

Weber, Arthur L.↗
NASA NTRS2016

Predictive Simulation of Gas Adsorption in Fixed-Beds and Limitations due to the Ill-Posed Danckwerts Boundary Condition

The 1-D axially dispersed plug flow model is a mathematical model widely used for the simulation of adsorption processes. Lumped mass transfer coefficients such as the Glueckauf linear driving force (LDF) term and the axial dispersion coefficient are generally obtained by fitting simulation results to the experimental breakthrough test data. An approach is introduced where these parameters, along with the only free parameter in the energy balance equations, are individually fit to specific test data that isolates the appropriate physics. It is shown that with this approach this model provides excellent simulation results for the C02 on zeolite SA sorbent/sorbate system; however, for the H20 on zeolite SA system, non-physical deviations from constant pattern behavior occur when fitting dispersive experimental results with a large axial dispersion coefficient. A method has also been developed that determines a priori what values of the LDF and axial dispersion terms will result in non-physical simulation results for a specific sorbent/sorbate system when using the one-dimensional axially dispersed plug flow model. A relationship between the steepness of the adsorption equilibrium isotherm as indicated by the distribution factor, the magnitude of the axial dispersion and mass transfer coefficient, and the resulting non-physical behavior is derived. This relationship is intended to provide a guide for avoiding non-physical behavior by limiting the magnitude of the axial dispersion term on the basis of the mass transfer coefficient and distribution factor.

Knox, James Clinton↗
DOE OSTI2021

Evaluate the System-Level Impact of Connected and Automated Vehicles Coupled with Shared Mobility: An Agent-based Simulation Approach

With the rapid growth of information and communication technologies, Connected and Automated Vehicles (CAVs) are deemed to be disruptive with the potential to significantly improve overall transportation system efficiency, however, may bring Vehicle Miles Traveled (VMT) increase or other issues. Further, shared mobility systems are another disruptive force that is reshaping our travel patterns. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance and energy efficiency, we develop a mesoscopic simulation-based framework for mobility and energy efficiency evaluation considering the disruptive transportation technologies. Under this framework, we develop novel models for energy intensity and modal activity, and evaluated a variety of energy scenarios for different combinations of CAV applications, various levels of automation, roadway characteristics, and traffic conditions, while also varying different vehicle types and fuel/powertrain technologies. Based applying this modeling suite to a calibrated BEAM simulation network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes.

42 ENGINEERING↗