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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Multiple watershed alterations influence fish community structure in Great Plains prairie streams

Stream fish distributions are commonly linked to environmental disturbances affecting terrestrial landscapes. In Great Plains prairie streams, the independent and interactive effects of watershed impoundments and land cover changes remain poorly understood despite their prevalence and assumed contribution to declining stream fish diversity. We used structural equation models and fish community samples from third-order streams in the Kansas River and Arkansas River basins of Kansas, USA to test the simultaneous effects of geographic location, terrestrial landscape alteration, watershed impoundments and local habitat on species richness for stream-associated and impoundment-associated habitat guilds. Watershed impoundment density increased from west to east in both basins, while per cent altered terrestrial landscape (urbanisation + row-crop agriculture) averaged ~50% in the west, declined throughout the Flint Hills ecoregion and increased (Kansas River basin ~80%) or decreased (Arkansas River basin ~30%) to the east. Geographic location had the strongest effect on richness for both guilds across basins, supporting known zoogeography patterns. In addition to location, impoundment species richness was positively correlated with local habitat in both basins; whereas stream-species richness was negatively correlated with landscape alterations (Kansas River basin) or landscape alterations and watershed impoundments (Arkansas River basin). These findings suggest that convergences in the relative proportions of impoundment and stream species (i.e., community structure) in the eastern extent of both basins are related to positive effects of increased habitat opportunities for impoundment species and negative effects caused by landscape alterations (Kansas River basin) or landscape alterations plus watershed impoundments (Arkansas River basin) for stream species.

fish community↗
DOE OSTI2015

Canopy warming caused photosynthetic acclimation and reduced seed yield in maize grown at ambient and elevated [ CO 2 ]

Abstract Rising atmospheric CO 2 concentration ([ CO 2 ]) and attendant increases in growing season temperature are expected to be the most important global change factors impacting production agriculture. Although maize is the most highly produced crop worldwide, few studies have evaluated the interactive effects of elevated [ CO 2 ] and temperature on its photosynthetic physiology, agronomic traits or biomass, and seed yield under open field conditions. This study investigates the effects of rising [ CO 2 ] and warmer temperature, independently and in combination, on maize grown in the field throughout a full growing season. Free‐air CO 2 enrichment ( FACE ) technology was used to target atmospheric [ CO 2 ] to 200 μ mol mol −1 above ambient [ CO 2 ] and infrared heaters to target a plant canopy increase of 3.5 °C, with actual season mean heating of ~2.7 °C, mimicking conditions predicted by the second half of this century. Photosynthetic gas‐exchange parameters, leaf nitrogen and carbon content, leaf water potential components, and developmental measurements were collected throughout the season, and biomass and yield were measured at the end of the growing season. As predicted for a C 4 plant, elevated [ CO 2 ] did not stimulate photosynthesis, biomass, or yield. Canopy warming caused a large shift in aboveground allocation by stimulating season‐long vegetative biomass and decreasing reproductive biomass accumulation at both CO 2 concentrations, resulting in decreased harvest index. Warming caused a reduction in photosynthesis due to down‐regulation of photosynthetic biochemical parameters and the decrease in the electron transport rate. The reduction in seed yield with warming was driven by reduced photosynthetic capacity and by a shift in aboveground carbon allocation away from reproduction. This field study portends that future warming will reduce yield in maize, and this will not be mitigated by higher atmospheric [ CO 2 ] unless appropriate adaptation traits can be introduced into future cultivars.

Ruiz‐Vera, Ursula M.↗
DOE OSTI2014

A sweet new role for LCP enzymes in protein glycosylation

The peptidoglycan that surrounds Gram-positive bacteria is affixed with a range of macromolecules that enable the microbe to effectively interact with its environment. Distinct enzymes decorate the cell wall with proteins and glycopolymers. Sortase enzymes covalently attach proteins to the peptidoglycan, while LytRCpsA-Psr (LCP) proteins are thought to attach teichoic acid polymers and capsular polysaccharides. Ton-That and colleagues have discovered a new glycosylation pathway in the oral bacterium Actinomyces oris in which sortase and LCP enzymes operate on the same protein substrate. The A. oris LCP protein has a novel function, acting on the cell surface to transfer glycan macromolecules to a protein, which is then attached to the cell wall by a sortase. The reactions are tightly coupled, as elimination of the sortase causes the lethal accumulation of glycosylated protein in the membrane. Furthermore, since sortase enzymes are attractive drug targets, this novel finding may provide a convenient cell-based tool to discover inhibitors of this important enzyme family.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Mycorrhizal phenotypes and the L aw of the M inimum

Summary Mycorrhizal phenotypes arise from interactions among plant and fungal genotypes and the environment. Differences in the stoichiometry and uptake capacity of fungi and plants make arbuscular mycorrhizal ( AM ) fungi inherently more nitrogen (N) limited and less phosphorus (P) limited than their host plants. Mutualistic phenotypes are most likely in P‐limited systems and commensal or parasitic phenotypes in N‐limited systems. Carbon (C) limitation is expected to cause phenotypes to shift from mutualism to commensalism and even parasitism. Two experiments compared the influence of fertilizer and shade on mycorrhizas in A ndropogon gerardii across three naturally N‐limited or P‐limited grasslands. A third experiment examined the interactive effects of N and P enrichment and shade on A . gerardii mycorrhizas. Our experiments generated the full spectrum of mycorrhizal phenotypes. These findings support the hypothesis that mutualism is likely in P‐limited systems and commensalism or parasitism is likely in N‐limited systems. Furthermore, shade decreased C‐assimilation and generated less mutualistic mycorrhizal phenotypes with reduced plant and fungal biomass. Soil fertility is a key controller of mycorrhizal costs and benefits and the L aw of the M inimum is a useful predictor of mycorrhizal phenotype. In our experimental grasslands arbuscular mycorrhizas can ameliorate P‐limitation but not N‐limitation.

Johnson, Nancy Collins↗
DOE OSTI2024

An Approach to Realize Generalized Optimal Motion Primitives Using Physics Informed Neural Networks

Autonomous manipulation is a challenging problem in field robotics due to uncertainty in object properties, constraints, and coupling phenomenon with robot control systems. Humans learn motion primitives over time to effectively interact with the environment. We postulate that autonomous manipulation can be enabled by basic sets of motion primitives as well, but do not necessitate mimicking human motion primitives. Here, this work presents an approach to generalized optimal motion primitives using physics-informed neural networks. Our simulated and experimental results demonstrate that optimality is notionally maintained where the mean maximum observed final position percent error was 0.564% and the average mean error for all the trajectories was 1.53%. These results indicate that notional generalization is attained using a physics-informed neural network approach that enables near optimal real-time adaptation of primitive motion profiles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Decomposition of Aromatic Compounds Relevant to Organic Electronics under Exposure to Low-Energy Electrons

The persistence of molecules to destruction under the action of low-energy (0–15 eV) electrons is investigated for a representative series of aromatic compounds of interest to organic electronics and photonics. The energy regions of the most effective interaction of free electrons with isolated molecules, which leads to the dissociative decay of molecules due to the formation of short-lived negative molecular ions unstable to fragmentation, are determined using resonance electron capture negative ion mass spectrometry. The characteristic fragmentation channels for molecular ions are revealed for some groups of compounds, and the threshold energies of the most significant fragmentation processes are estimated. Polycyclic aromatic hydrocarbons and oligophenyls are stable to the action of electrons in the electron energy range ~0–3 eV, above which these compounds are decomposed into the single channel of hydrogen atom detachment. For compounds with heterocycles (oxadiazole and maleimide derivatives) in their structure, the stability range narrows down to ~0–1 eV. Electrons with energies exceeding this range initiate the decay of molecules (anions) via various channels among which the detachment of a cyanate anion from a heterocyclic nucleus is the most intense and destructive process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Photoproduction of $ \pi^{0}$-pairs off protons and off neutrons

Total cross sections, angular distributions, and invariant-mass distributions have been measured for the photoproduction of π 0 π 0 pairs off free protons and off nucleons bound in the deuteron. The experiments were performed at the MAMI accelerator facility in Mainz using the Glasgow photon tagging spectrometer and the Crystal Ball/TAPS detector. The accelerator delivered electron beams of 1508 and 1557MeV, which produced bremsstrahlung in thin radiator foils. The tagged photon beam covered energies up to 1400MeV. The data from the free proton target are in good agreement with previous measurements and were only used to test the analysis procedures. The results for differential cross sections (angular distributions and invariant-mass distributions) for free and quasi-free protons are almost identical in shape, but differ in absolute magnitude up to 15%. Thus, moderate final-state interaction effects are present. The data for quasi-free neutrons are similar to the proton data in the second resonance region (final-state invariant masses up to ≈1550 MeV), where both reactions are dominated by the N(1520)3/2 – →Δ(1232)3/2 + π decay. At higher energies, angular and invariant-mass distributions are different. A simple analysis of the shapes of the invariant-mass distributions in the third resonance region is consistent with strong contributions of an N*→Nσ decay for the proton, while the reaction is dominated by a sequential decay via a Δπ intermediate state for the neutron. Here, the data are compared to predictions from the Two-Pion-MAID model and the Bonn-Gatchina coupled-channel analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Measurement of the branching fraction of the ${{B} ^0} {\rightarrow }{{D} ^+_{s}} {{\pi } ^-} $ decay

A branching fraction measurement of the \({{B} ^0} {\rightarrow }{{D} ^+_{s}} {{\pi } ^-} \) decay is presented using proton–proton collision data collected with the LHCb experiment, corresponding to an integrated luminosity of \(5.0\,\text {fb} ^{-1} \) . The branching fraction is found to be \({\mathcal {B}} ({{B} ^0} {\rightarrow }{{D} ^+_{s}} {{\pi } ^-} ) =(19.4 \pm \) \(1.8\pm 1.3 \pm 1.2)\times 10^{-6}\) , where the first uncertainty is statistical, the second systematic and the third is due to the uncertainty on the \({{B} ^0} {\rightarrow }{{D} ^-} {{\pi } ^+} \) , \({{D} ^+_{s}} {\rightarrow }{{K} ^+} {{K} ^-} {{\pi } ^+} \) and \({{D} ^-} {\rightarrow }{{K} ^+} {{\pi } ^-} {{\pi } ^-} \) branching fractions. This is the most precise single measurement of this quantity to date. As this decay proceeds through a single amplitude involving a \(b{\rightarrow }u\) charged-current transition, the result provides information on non-factorisable strong interaction effects and the magnitude of the Cabibbo–Kobayashi–Maskawa matrix element \(V_{ub}\) . Additionally, the collision energy dependence of the hadronisation-fraction ratio \(f_s/f_d\) is measured through \({{\overline{B}} {}^0_{s}} {\rightarrow }{{D} ^+_{s}} {{\pi } ^-} \) and \({{B} ^0} {\rightarrow }{{D} ^-} {{\pi } ^+} \) decays.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

kynema-sgf [SWR-20-85]

Kynema-SGF (formerly AMR-Wind), wherein SGF stands for structured-grid fluid dynamics, is a massively parallel, block-structured adaptive-mesh, incompressible flow solver. The codebase was initiated in 2019 from incflo. The solver is built on top of the AMReX library. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. Kynema-SGF is actively developed and maintained by a dedicated multi-institutional team from Lawrence Berkeley National Laboratory, National Laboratory of the Rockies, and Sandia National Laboratories. The primary applications for Kynema-SGF are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver (e.g., Kynema-UGF) with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm. For offshore applications, the ability to model the air-sea interaction effects and its impact on the ABL characteristics is another focus for the code development effort. As with other codes in the Kynema ecosystem, Kynema-SGF shares the following objectives: *an open, well-documented implementation of the state-of-the-art computational models for modeling wind farm flow physics at various fidelities that are backed by a comprehensive verification and validation (V&V) process; *be capable of performing the highest-fidelity simulations of flow fields within wind farms; and *be able to leverage the high-performance leadership class computing facilities available at DOE national laboratories.

Ananthan, Shreyas↗
DOE OSTI2025

The Impact of Demographic Lifecycle States on Time to Vehicle Purchase: Insights from the Panel Study of Income Dynamics

This study examines the impact of demographic lifecycle stages on the timing of vehicle purchases, using data from the Panel Study of Income Dynamics from 1999 to 2021. Survival analysis was employed to model the duration until households purchase vehicles, incorporating key lifecycle variables such as age, employment status, marital status, childbirth, home ownership, and the presence of school-going children. The life table results indicate that early adulthood (ages 20–35) is the prime period for vehicle acquisition, with significant peaks around ages 25 to 30. Additionally, the instantaneous hazard of purchasing a vehicle is highest in the late 40s and early 50s. According to the Cox proportional hazards model, employment, marital status, and home ownership significantly increase the likelihood of purchasing a vehicle, while living in multi-unit dwellings decreases it. Interaction effects reveal that married individuals with employed spouses are substantially more likely to purchase vehicles. In conclusion, this study serves as a steppingstone toward integrating demographic lifecycle analysis into car ownership modeling that better reflects real-world scenarios and increases the accuracy of policy and strategic planning.

Car ownership↗
DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Memory Concerns, Memory Performance and Risk of Dementia in Patients with Mild Cognitive Impairment

Concerns about worsening memory (‘‘memory concerns’’; MC) and impairment in memory performance are both predictors of Alzheimer’s dementia (AD). The relationship of both in dementia prediction at the pre-dementia disease stage, however, is not well explored. Refined understanding of the contribution of both MC and memory performance in dementia prediction is crucial for defining at-risk populations. We examined the risk of incident AD by MC and memory performance in patients with mild cognitive impairment (MCI). We analyzed data of 417 MCI patients from a longitudinal multicenter observational study. Patients were classified based on presence (n = 305) vs. absence (n = 112) of MC. Risk of incident AD was estimated with Cox Proportional-Hazards regression models. Risk of incident AD was increased by MC (HR = 2.55, 95%CI: 1.33–4.89), lower memory performance (HR = 0.63, 95%CI: 0.56–0.71) and ApoE4-genotype (HR = 1.89, 95%CI: 1.18–3.02). An interaction effect between MC and memory performance was observed. The predictive power of MC was greatest for patients with very mild memory impairment and decreased with increasing memory impairment. Our data suggest that the power of MC as a predictor of future dementia at the MCI stage varies with the patients’ level of cognitive impairment. While MC are predictive at early stage MCI, their predictive value at more advanced stages of MCI is reduced. This suggests that loss of insight related to AD may occur at the late stage of MCI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Model output from simulations of manganese-carbon interactions in temperate forest soil profiles

This archive contains model output, code, and scripts for simulations of coupled manganese-carbon cycling in temperate forest soil profiles. These model results were generated as part of a study investigating how manganese availability influences soil organic carbon stocks and demonstrating a new model framework for coupling carbon and manganese cycling. The simulations were in support of a manuscript: "Modeling interactive effects of manganese bioavailability, nitrogen deposition, and warming on soil carbon storage." The study addresses the research questions: How does Mn bioavailability, as driven by subsurface mineral properties, pH, and redox status, affect temperate forest soil organic carbon and litter carbon stocks?How is the relationship between Mn bioavailability and carbon cycling affected by changes in temperature and nitrogen deposition?"Model simulations were conducted in a reactive transport modeling framework using PFLOTRAN coupled to python. Multiple model simulations testing different Mn-bearing mineral solubilities, hydrological patterns, nitrogen deposition rates, and temperatures are included. Soil properties, including total and exchangeable Mn concentrations, are based on values reported for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), a temperate forested watershed in central Pennsylvania, U.S.A where Mn cycling through vegetation has been documented.File formats include netCDF (.nc), python script (.py), shell script (.sh), plain text PFLOTRAN input file (.in), and plain text PFLOTRAN database file (.dat), and gzipped tar archive (tar.gz).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simulation Studies on the Interactions of Electron Beam with Wastewater

The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected into the water area, where the volume of water is around 75 cubic cm. The distribution parameters of the electron beam are from the GPT (General Particle Tracer) simulations for UITF (Upgraded Injector Test Facility) in Jefferson lab. By varying the distributions, several measurements including the dose (or energy deposition) distribution, electron fluence, photon fluence are scored and compared. Taking the comparisons into consideration, this paper is aiming to find better electron beams for the wastewater irradiation.

Li, X.↗
DOE OSTI2014

Behavioral Change and Building Performance: Strategies for Significant, Persistent, and Measurable Institutional Change

The people who use Federal buildings — Federal employees, operations and maintenance staff, and the general public — can significantly impact a building’s environmental performance and the consumption of energy, water, and materials. Many factors influence building occupants’ use of resources (use behaviors) including work process requirements, ability to fulfill agency missions, new and possibly unfamiliar high-efficiency/high-performance building technologies; a lack of understanding, education, and training; inaccessible information or ineffective feedback mechanisms; and cultural norms and institutional rules and requirements, among others. While many strategies have been used to introduce new occupant use behaviors that promote sustainability and reduced resource consumption, few have been verified in the scientific literature or have properly documented case study results. This paper documents validated strategies that have been shown to encourage new use behaviors that can result in significant, persistent, and measureable reductions in resource consumption. From the peer-reviewed literature, the paper identifies relevant strategies for Federal facilities and commercial buildings that focus on the individual, groups of individuals (e.g., work groups), and institutions — their policies, requirements, and culture. The paper documents methods with evidence of success in changing use behaviors and enabling occupants to effectively interact with new technologies/designs. It also provides a case study of the strategies used at a Federal facility — Fort Carson, Colorado. The paper documents gaps in the current literature and approaches, and provides topics for future research.

Wolfe, Amy K.↗