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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Comprehensive Approach to Measure the Efficiency of Freight Transport: Freight Mobility Energy Productivity (F-MEP) Metric

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement is critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregated in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance of freight systems. Addressing this research need, this paper presents the 'Freight Mobility Energy Productivity' metric to quantify freight performance of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight performance. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight efficiency as a result of vehicle powertrain technology improvement. Results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the efficiency of existing as well as future freight trends and technologies.

25 ENERGY STORAGE↗
DOE OSTI2020

Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting has been gaining pace in recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, and shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport: Preprint

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Near-edge beta induced Alfven eigenmode in DIII-D high bootstrap current fraction plasmas

In DIII-D high bootstrap current fraction plasmas heated solely by neutral beam injection, a fast ion-driven Beta-Induced Alfven Eigenmode (BAE) is frequently observed. The BAE peaks near the edge, suggesting the possibility of enhanced fast ion transport there and raising a potential concern for the first wall. Theoretical analysis and simulations show that the mode location is not fully determined by the fast-ion drive intensity, i.e. fast ion pressure gradient but is strongly related to the background unfavorable magnetic curvature drive near the edge, which is an intrinsic property of advanced scenarios that rely on a large radius internal transport barrier that exists for all the kinetic channels for performance improvement.

beta induced Alfven eigenmode↗
DOE OSTI2020

Analysis of Tempered Fractional Operators

Tempered fractional operators are useful in models for subsurface transport and diffusion due to their ability to capture anomalous diffusion: a behavior which the classical partial differential equation models cannot describe. We analyze tempered fractional operators within the nonlocal vector calculus framework in order to assimilate them to the rigorous mathematical structure developed for nonlocal models. First, we show they are special instances of generalized nonlocal operators in correspondence of a proper choice of nonlocal kernels. Then, we work towards showing tempered fractional operators are equivalent to truncated fractional operators. These truncated operators are useful because they are less computationally intensive than the tempered operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Life cycle assessment of coir fiber-reinforced composites for automotive applications

Past decades have seen an increasing prevalence of natural fiber-reinforced composites (NFRCs) due to growing conscientiousness around sustainability and a push towards vehicle lightweighting. The environmentally friendly and sustainable claims of NFRCs need to be validated due to their large variability and variety, particularly where material substitutions are concerned, such as in substituting glass fiber with natural fiber. Additionally, the objective of this work is to determine the cumulative energy demand (CED) and greenhouse gas emissions (GHG) associated with an automotive part (of volume 0.001 m3) made from 40 wt% coir fiber-reinforced polypropylene (PP) and compared with a similar part made from 40 wt% glass fiber reinforced PP. SimaPro v. 9.0.0.49 was used for the analysis, whereas inventory data were collected from databases, such as Ecoinvent 3, Transportation Energy Databook, Greet model 2022, and published papers. The results showed that CED and GHG associated with the coir fiber-reinforced composite part were lower than the glass fiber-reinforced composite part for both cradle-to-gate (~34–40%) and cradle-to-grave (excluding end-of-life) (~24%) analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational Analysis of Anode and Cathode Structuring Effects on Charge and Discharge in Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Structured electrodes (SEs) improve the rate capability of Lithium-ion batteries by engineering micrometer-scale electrolyte regions into the electrode, promoting rapid ionic transport. Prior research has focused on structuring one electrode (anode or cathode) with an analysis on either the charge or discharge performance. We present a holistic study using three-dimensional models to investigate the isolated effects of structuring either electrode and the combined effects of structuring both electrodes on the charge and discharge capacity of single-layer cells at 4 C and 6 C. Volumetric and gravimetric discharge energy density (Wh/L stack and Wh/kg stack ) and charge capacity (Ah/kg stack and Ah/L stack ) are evaluated for multi-layer pouch cell stacks. Pairing SE anodes with SE cathodes demonstrated improvements up to 15% in discharge Wh/kg stack and up to 33% in charge Ah/kg stack over a conventional cell; Energy required to charge per Ah/kg stack was improved by 13%–14%. SE cathodes paired with a conventional anode exhibited improvements of 0.3%–22% across all performance metrics evaluated. Conversely, pairing a SE anode with a conventional cathode demonstrated improved charge capacity up to 13% but showed a 2%–23% lower discharge energy density. The importance of aligning SEs in a cell from a performance and manufacturing perspective is also analyzed.

25 ENERGY STORAGE↗
DOE OSTI2025

Hazard and Operability Analysis for Operating, Refueling, and Maintenance of Fuel Cell Electric Buses

​​Since hydrogen vehicles can be implemented in heavy-duty transportation applications such as buses, it is important to understand safety hazards and risks of hydrogen fuel cell electric bus (FCEB) and refueling technology. We conducted a hazard and operability analysis for FCEB operation/driving, refueling, and maintenance/inspection. We identified failure modes and consequences and defined a qualitative risk metric as the product of the likelihood of a failure and the severity of the worst-ca

08 HYDROGEN↗
DOE OSTI2024

Theoretical and global simulation analysis of collisional microtearing modes

Microtearing modes (MTMs) are suggested as a candidate for anomalous thermal transport in tokamak H-mode discharges. This study investigates MTMs in tokamak plasmas, employing simulations in the BOUT++ framework. It simplifies and linearizes the governing equations in detailed linear simulations. The study meticulously evaluates various conductivity models under diverse plasma conditions and collision regimes. The research thoroughly assesses different conductivity models across a range of plasma conditions and collision regimes. A unified dispersion relation that includes both MTM and Drift-Alfvén Wave (DAW) instabilities is derived, showing that DAW and MTM instabilities occur at varying distances from the rational surface. Specifically, MTMs become unstable near the rational surface but stabilize farther away, while drift-Alfvén instability appears farther from the rational surface. The study also re-derives MTM dispersion relations using Ohm's law and the vorticity equation, providing a thorough analysis of electromagnetic and electrostatic interactions in tokamaks. Global simulations demonstrate an inverse correlation between MTM growth rates and collisionality, and a direct correlation with temperature gradients. The nonalignment of the rational surface with the peak ω*e stabilizes the MTMs. Nonlinear simulations highlight electron temperature relaxation as the primary saturation mechanism for MTMs, with magnetic flutter identified as the dominant mode of electron thermal transport.

Fan, K. (ORCID:0000000227518809)↗
DOE OSTI2025

Meeting in the Middle: Pooled Rideshare as Compelling Transportation Offering for Elders

Pooled ridesharing is an innovative new transportation offering with the potential to positively impact traffic and emissions. Through pooling, rideshare can aggregate demand, decreasing the number of vehicles required on the road, but also offering options to those without access to reliable means of transportation. In this study pooled ridesharing is explored in the context of its impacts on seniors. Through analysis of income, location, accessibility, and mode shares, pooled rideshare is demonstrated to offer a compelling middle ground for seniors looking for more affordable transportation than personal vehicles, but who are time sensitive or may not have access to public transportation. An efficient rideshare assignment strategy, which caters to discounts for riders' specific trips, is compared to a more basic heuristic. Results indicate that more riders utilize the service with catered discounts, despite increased wait and travel times over solo rideshare. Additionally, results indicate that although public transportation usage decreases when rideshare service offerings improve, there is not necessarily a direct shift in user base, as even pooled rideshare is still expensive enough to prevent seniors from the lowest household income quartiles from using the service.

Paul, Joseph↗
DOE OSTI2023

Driving mode analysis—How uncertain functional inputs propagate to an output

Abstract Driving mode analysis elucidates how correlated features of uncertain functional inputs jointly propagate to produce uncertainty in the output of a computation. Uncertain input functions are decomposed into three terms: the mean functions, a zero‐mean driving mode, and zero‐mean residual. The random driving mode varies along a single direction, having fixed functional shape and random scale. It is uncorrelated with the residual, and under linear error propagation, it produces an output variance equal to that of the full input uncertainty. Finally, the driving mode best represents how input uncertainties propagate to the output because it minimizes expected squared Mahalanobis distance amongst competitors. These characteristics recommend interpretation of the driving mode as the single‐degree‐of‐freedom component of input uncertainty that drives output uncertainty. We derive the functional driving mode, show its superiority to other seemingly sensible definitions, and demonstrate the utility of driving mode analysis in an application. The application is the simulation of neutron transport in criticality experiments. The uncertain input functions are nuclear data that describe how Pu reacts to bombardment by neutrons. Visualization of the driving mode helps scientists understand what aspects of correlated functional uncertainty have effects that either reinforce or cancel one another in propagating to the output of the simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sequential removal of cation/H + exchangers reveals their additive role in elemental distribution, calcium depletion and anoxia tolerance

Multiple Arabidopsis H + /Cation exchangers (CAXs) participate in high-capacity transport into the vacuole. Previous studies have analysed single and double mutants that marginally reduced transport; however, assessing phenotypes caused by transport loss has proven enigmatic. Here, in this study, we generated quadruple mutants (cax1-4: qKO) that exhibited growth inhibition, an 85% reduction in tonoplast-localised H + /Ca transport, and enhanced tolerance to anoxic conditions compared to CAX1 mutants. Leveraging inductively coupled plasma mass spectrometry (ICP-MS) and synchrotron X-ray fluorescence (SXRF), we demonstrate CAX transporters work together to regulate leaf elemental content: ICP-MS analysis showed that the elemental concentrations in leaves strongly correlated with the number of CAX mutations; SXRF imaging showed changes in element partitioning not present in single CAX mutants and qKO had a 40% reduction in calcium (Ca) abundance. Reduced endogenous Ca may promote anoxia tolerance; wild-type plants grown in Ca-limited conditions were anoxia tolerant. Sequential reduction of CAXs increased mRNA expression and protein abundance changes associated with reactive oxygen species and stress signalling pathways. Multiple CAXs participate in postanoxia recovery as their concerted removal heightened changes in postanoxia Ca signalling. This work showcases the integrated and diverse function of H + /Cation transporters and demonstrates the ability to improve anoxia tolerance through diminishing endogenous Ca levels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular dynamics study of carbon dioxide and nitrogen selectivity through poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) membrane

Here, a molecular dynamics simulation model was developed to comprehensively understand carbon dioxide over nitrogen (CO 2 /N 2 ) selectivity through polyphosphazene-based membrane comprising of poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) selective layer at the molecular level. The effects of temperature, pressure, and initial feed gas composition on the CO 2 transport on a polymer membrane were studied. The computed free energy and density profile of the permeating gas mixture exhibited that CO 2 molecules express higher interactions with the membrane than N 2 molecules, resulting in higher CO 2 /N 2 selectivity. Statistical analysis of gas molecules (CO 2 , water (H 2 O), and N 2 ) transportation suggested that hydro- and CO 2 -philic functional groups in the membrane significantly impact CO 2 permeability and CO 2 /N 2 selectivity. This study suggested that Lewis acid–base and hydrogen bonding combinations contribute to CO 2 permeation and CO 2 /N 2 selectivity. An equal CO 2 /N 2 selectivity was observed with and without water vapor in the feed gas suggesting that water does not hinder CO 2 transport through the membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fast Advective Water Flow through Nanochannels in Clay Interlayers: Implications for Moisture Transport in Soils and Unconventional Oil/Gas Production

Water flow in nanometer or sub-nanometer hydrophilic channels bears special importance in diverse fields of science and engineering. However, the nature of such water flow remains elusive. In this work, we report our molecular-modeling results on water flow in a sub-nanometer clay interlayer between two montmorillonite layers. We show that a fast advective flow can be induced by evaporation at one end of the interlayer channel, that is, a large suction pressure created by evaporation (~818 MPa) is able to drive the fast water flow through the channel (~0.88 m/s for a 46 Å-long channel). Scaled up for the pressure gradient to a 2 μm particle, the velocity of water is estimated to be about 95 μm/s, indicating that water can quickly flow through a μm-sized clay particle within seconds. The prediction seems to be confirmed by our thermogravimetric analysis of bentonite hydration and dehydration processes, which indicates that water transport at the early stage of the dehydration is a fast advective process, followed by a slow diffusion process. The possible occurrence of a fast advective water flow in clay interlayers prompts us to reassess water transport in a broad set of natural and engineered systems such as clay swelling/shrinking, moisture transport in soils, water uptake by plants, water imbibition/release in unconventional hydrocarbon reservoirs, and cap rock integrity of supercritical CO 2 storage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Amorphous oxyhalides have attracted significant attention due to their relatively high ionic conductivity (1 mS cm –1 ), excellent chemical stability, mechanical softness, and facile synthesis routes via standard solid‐state reactions. These materials exhibit an ionic conductivity that is almost independent of the underlying chemistry, in stark contrast to what occurs in crystalline conductors. In this work, we employ machine learning interatomic potentials to construct large‐scale molecular dynamics trajectories encompassing hundreds of nanoseconds to obtain statistically converged transport properties. We find that the amorphous state consists of chain fragments of metal‐anion tetrahedra of various lengths. By analyzing the residence time of alkali cations migrating around tetrahedrally‐coordinated metals, we find that oxygen anions limit alkali diffusion. By computing the full Einstein expression of the ionic conductivity, we demonstrate that the alkali transference number of these materials is strongly influenced by distinct‐particles correlations, while alkali transport is dictated by uncorrelated self‐diffusion. By extending this analysis to chemical compositions AMX 2.5 O 0.75 , spanning different alkaline (A = Li, Na, K), metallic (M = Al, Ga, In), and halogen (X = Cl, Br, I) species, we clarify why the diffusion properties of these materials remain largely insensitive to variations in atomic isovalent chemistry.

amorphous materials↗
DOE OSTI2024

In-Depth Proteome Profiling of the Hippocampus of LDLR Knockout Mice Reveals Alternation in Synaptic Signaling Pathway

The low-density lipoprotein receptor (LDLR) is a major apolipoprotein receptor that regulates cholesterol homeostasis. LDLR deficiency is associated with cognitive impairment by the induction of synaptopathy in the hippocampus. Despite the close relationship between LDLR and neurodegenerative disorders, proteomics research for protein profiling in the LDLR knockout (KO) model remains insufficient. Therefore, understanding LDLR KO-mediated differential protein expression within the hippocampus is crucial for elucidating a role of LDLR in neurodegenerative disorders. In this study, we conducted first-time proteomic profiling of hippocampus tissue from LDLR KO mice using tandem mass tag (TMT)-based MS analysis. LDLR deficiency induces changes in proteins associated with the transport of diverse molecules, and activity of kinase and catalyst within the hippocampus. Additionally, significant alterations in the expression of components in the major synaptic pathways were found. Furthermore, these synaptic effects were verified using a data-independent acquisition (DIA)-based proteomic method. In conclusion, our data will serve as a valuable resource for further studies to discover the molecular function of LDLR in neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A parallel discrete dislocation dynamics/kinetic Monte Carlo method to study non-conservative plastic processes

Non-conservative processes play a fundamental role in plasticity and are behind important macroscopic phenomena such as creep, dynamic strain aging, loop raft formation, etc. In the most general case, vacancy-induced dislocation climb is the operating unit mechanism. While dislocation/vacancy interactions have been modeled in the literature using a variety of methods, the approaches developed rely on continuum descriptions of both the vacancy population and its fluxes. However, there are numerous situations in physics where point defect populations display heterogeneous concentrations and/or non-smooth kinetics. Here, a kinetic Monte Carlo (kMC) approach for modeling vacancy transport in response to arbitrary stress fields is used. Vacancies are treated as point particles and are coupled to the dislocation substructure representing a deformed material via an advection term defined by the local stress gradients. The stress fields and the dislocation substructure are evolved using a discrete dislocation dynamics (DDD) module. To extend the coupled model to the treatment of large systems, we have implemented it in the massively-parallel DDD code ParaDiS. To avoid numerical incompatibilities associated with merging deterministic (DDD) and stochastic (kMC) integration algorithms, we cast the entire elasto-plastic-diffusive problem within a single stochastic framework, taking advantage of a parallel kMC algorithm to evolve the system as a single event-driven process. The large-scale implementation enables the study of the evolution of a variety of dislocation-defect scenarios governed by non-conservative transport kinetics. After carrying out an exhaustive numerical and computational analysis of our parallel algorithm, we show results that emphasize situations where inhomogeneous vacancy dynamics are of relevance, and compare discrete kinetics to continuum solutions for several cases.

36 MATERIALS SCIENCE↗