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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-Fidelity Modeling of Curbside Driving Behavior in SUMO: Preprint

Recent advances in mobility technologies have considerably increased the need for curbside use and congestion at curb-lanes. At airports and in dense urban centers, the growing adoption of Transportation Network Companies (TNCs), such as Uber and Lyft, has led to an increase in curbside traffic due to the reduction in the use public transit and other shared modes. In dense city areas, the curbside demand and congestion were further augmented by the growing use of e-commerce, which requires home-delivery of goods. To model vehicles' curbside interactions realistically, there is a need for high-fidelity simulation models that can represent the complex interplay of vehicles as they complete pick-up or drop-off trips. Vehicles' curbside behaviors are usually not modeled with high-fidelity in microscopic simulators such Simulation of Urban of Mobility (SUMO). This paper presents such a high-resolution model for vehicle curbside behavior in SUMO, using SUMO's Traci interface. Simulations results demonstrate that the improved curbside behavior captures vehicles' curbside maneuvering more accurately than the default SUMO curbside model, and increases the curbside utilization and capacity.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Evaluation of High Level Waste Sludge Processing Behavior

The U.S. Department of Energy’s (DOE) Hanford Site has 177 underground storage tanks that contain wastes from past nuclear fuel reprocessing and waste-management operations. Over 20% of this waste is in the form of an insoluble sludge that will require slurry modification before its transfer to the Waste Treatment and Immobilization Plant (WTP). Specific WTP acceptance criteria for waste feed delivery describe the physical and chemical characteristics of the waste that must be met before the waste is transferred to the WTP. One challenging requirement relates to the undissolved solids (UDS) composition in a waste feed because the waste contains solid particles that settle, and their concentration and relative proportion can change during the transfer of the waste in individual batches. A key uncertainty is the ability to transfer and mix wastes with large variations in UDS concentrations and resulting settling rates. To address this uncertainty, a number of small scale mixing and settling tests have been conducted to determine the mobilization performance of variable chemistry simulants. Comparison of the size and density of the particulate for each simulant to that of southeast area Hanford sludge was made using metrics for particle mobilization, suspension, settling, and pipeline transfer where dependance on particle size and density may be different, including: 1. Settling velocity, 2. Critical shear stress for erosion, 3. Just-suspended impeller speed, and 4. Pipeline critical transport velocity. Existing high-level waste sludge data has shown the effect that increasing Al concentration has on resulting settled solids. This differential settling of particles in the sludge has the possibility of resulting in solids segregation during feed preparation and uneven particle distribution during pipeline transportation or mixer jet pump operations. Understanding the predictive capabilities of HLW solids settling and transport as well as potential remedies for addressing disparate sludge behaviors can help provide technical guidance during HLW flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Stability and mobility of tungsten clusters on tungsten (110) surface: Ab initio and atomistic simulations

Quantifying the surface transport properties of tungsten (W) is of prime importance to understand the formation of nano-fuzz in fusion plasma-facing conditions. The stability and mobility of W adatom clusters (W n , n = 2-9) on the W(110) surface has been investigated by computer simulations, including ab initio calculations using density functional theory (DFT) and molecular statics (MS) simulations with multiple W interatomic potentials. The DFT results demonstrate that the sequential binding energy generally increases with number of W adatoms, except for the 5 th and 7 th W adatoms. The most common elemental migration steps of W n (n>2) clusters are observed to consist of monomer and dimer hops, while larger W n clusters can also diffuse by dissociation and recombination of smaller clusters. The threshold migration energy of W 9 is the highest, then followed by W 8 , W 4 , and W 6 , while W 3 , W 5 , and W 7 have similar migration energies. Compared to DFT, each interatomic potential evaluated overestimates the binding energies of W n clusters. Additionally, the embedded-atom potential developed by Juslin and Wirth adequately predicts the threshold migration energy of W n (n>2) clusters, although it predicts different underlying migration mechanisms. The results show that interaction mechanism between W adatoms controls the stability and mobility of W n clusters on the W(110) surface.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗
DOE OSTI2024

Modeling Electric Vehicle Charging Load Using Origin-Destination Data

The accelerating adoption of electric vehicles (EVs) poses challenges to the power grid, necessitating precise representation of mobility patterns for effective infrastructure upgrades. Traditional simulation-based charging demand estimation faces limitations in generating trip chains reflective of actual travel patterns without complex network modeling. Hence, an innovative agent-based trip chain generation model is introduced to overcome these challenges. Drawing from the National Household Travel Survey (NHTS) and the NextGen NHTS origin-destination add-on data for Clarke County, Georgia, this study proposes a simulation method capturing both temporal and spatial mobility patterns without relying on extensive network topology data. The resulting trip chains predict EV charging load at the Census Block Group level, validated with a 1.03 correlation to actual trip counts, affirming their reflective accuracy. Two charging scenarios, residential-only and charging-everywhere, reveal distinct demand profiles. The charging-everywhere scenario aligns closely with the trip profile, while the residential-only scenario exhibits an afternoon peak slightly surpassing the former. This study contributes a data-driven charging demand estimation methodology, offering critical insights for grid resiliency planning amid the evolving landscape of EV adoption.

Pan, Melrose↗
DOE OSTI2023

Energy Optimization of Light and Heavy-Duty Vehicle Cohorts of Mixed Connectivity, Automation and Propulsion System Capabilities via Meshed V2V-V2I and Expanded Data Sharing (Final Scientific and Technical Report)

Vehicle connectivity and automated driving technologies individually have the potential to decrease energy consumption and/or increase safety on light, medium or heavy duty vehicles to varying degrees depending on the traffic infrastructure and specific driving scenarios. Due to advances in sensing, perception and computing power, research and development emphasis in the mobility sector has shifted away from connectivity. Prior research has shown that driving automation with the absence of connectivity can in certain circumstances increase energy consumption. The effectiveness of synergizing connectivity and driving automation technologies is the focus of this work, specifically applied to vehicle cohorts of mixed composition, light and heavy duty, and powertrains ranging from all electric to conventional internal combustion engine. The project team is led by Michigan Technological University (MTU) and partnered with AVL Mobility Technologies Inc. (AVL), Borg Warner (BW), Traffic Technology Services (TTS), American Center for Mobility (ACM) and Navistar (NAV). The main thrusts for the team are to develop a micro-traffic simulation environment with specific VD&PT system attributes and CAV capabilities, 2) field a vehicle test fleet of mixed classification, propulsion and CAV capacity, 3) develop artificial intelligence (AI) and machine learning (ML) based multi-agent optimization methods for various traffic infrastructures, 4) integrate the virtual environment and the optimization methods then deploy the system as a CAV hardware in the loop (HiL) for the vehicle test fleet and 5) conduct closed track and public road testing to validate simulation and demonstrated energy and mobility improvements at multiple scales. For a cohort of mixed vehicles, the team will demonstrate a reduction of energy consumption of 10-50% at intersection, arterial roadway and limited access highway scenarios through connectivity and automation in simulation and at a closed test track. The energy reduction objectives of the project are summarized in Table 1, indicating the infrastructure and over what distances are relevant considered. Single scenario energy reductions are not relevant and thus, the research team took the approach to vary parameters associated with the infrastructure, vehicle cohort composition and dynamic behavior to generate energy consumption distributions for both unconnected and connected scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Alloying induces directionally-dependent mobility and alters migration mechanisms of faceted grain boundaries

Faceted grain boundaries exhibit unusual segregation and migration tendencies. To gain a deeper understanding of how solute atoms interact with faceted interfacial structures during migration, this study probes the migration behavior of a faceted Σ11 boundary in Cu doped with Ag atoms. Furthermore, the solutes are found to segregate to the facet with more free volume and strongly reduce boundary velocity in one migration direction, but not the other, due to the presence of a directionally-dependent motion mechanism that can escape solute pinning and therefore speed up migration. Hence, a new mechanism of chemically-induced anisotropy in grain boundary mobility is uncovered by these simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Temperature and composition dependent screw dislocation mobility in austenitic stainless steels from large-scale molecular dynamics

Abstract Extensive molecular dynamics simulations are performed to determine screw dislocation mobility in austenitic Fe 0.7 Ni x Cr 0.3-x stainless steels as a function of temperature ranging from 100 to 1300 K, resolved shear stress from 30 to 140 MPa, and Ni composition from 0.0 to 30.0 at%. These mobility data are fitted to a linear mobility law with a nonzero stress offset, referred to as the threshold stress. We find that both the linear drag coefficient and the threshold stress increase with Ni composition. The drag coefficient increases with temperature, whereas the threshold stress decreases with temperature. Based on these calculations, we determine fitting functions for the linear solute drag coefficient as a function of temperature and composition. The mobility laws determined in this study may serve to inform dislocation dynamics simulations pertinent to dislocation network evolution at elevated temperatures for a wide composition range of austenitic stainless steels.

Chu, Kevin (ORCID:000000031929710X)↗
DOE OSTI2022

Predicting Solar Cell Performance from Terahertz and Microwave Spectroscopy

Abstract Mobilities and lifetimes of photogenerated charge carriers are core properties of photovoltaic materials and can both be characterized by contactless terahertz or microwave measurements. Here, the expertise from fifteen laboratories is combined to quantitatively model the current‐voltage characteristics of a solar cell from such measurements. To this end, the impact of measurement conditions, alternate interpretations, and experimental inter‐laboratory variations are discussed using a (Cs,FA,MA)Pb(I,Br) 3 halide perovskite thin‐film as a case study. At 1 sun equivalent excitation, neither transport nor recombination is significantly affected by exciton formation or trapping. Terahertz, microwave, and photoluminescence transients for the neat material yield consistent effective lifetimes implying a resistance‐free JV‐curve with a potential power conversion efficiency of 24.6 %. For grainsizes above ≈20 nm, intra‐grain charge transport is characterized by terahertz sum mobilities of ≈32 cm 2 V −1 s −1 . Drift‐diffusion simulations indicate that these intra‐grain mobilities can slightly reduce the fill factor of perovskite solar cells to 0.82, in accordance with the best‐realized devices in the literature. Beyond perovskites, this work can guide a highly predictive characterization of any emerging semiconductor for photovoltaic or photoelectrochemical energy conversion. A best practice for the interpretation of terahertz and microwave measurements on photovoltaic materials is presented.

14 SOLAR ENERGY↗
DOE OSTI2021

Non-local corrections to the typical medium theory of Anderson localization

We use the recently developed finite cluster typical medium approach to study the Anderson localization transition in three dimensions. Applying our method to the box and binary alloy disorder distributions, we find a fast convergence with the cluster size. We demonstrate the importance of the typical medium environment and the non-local spatial correlations for the proper characterization of the localization transition. As the cluster size increases, our typical medium cluster method recovers the correct critical disorder strength for the transition. Our findings highlight the importance of the non-local cluster corrections for capturing the localization behavior of the mobility edge trajectories. Our results demonstrate that the typical medium cluster approach developed here provides a consistent and systematic description of the Anderson localization transition in the framework of the effective medium embedding schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Lifelike behavior of chemically oscillating mobile capsules

Inspired by the self-organization of unicellular species into multicellular organisms, we use theory and simulation to design a system of mobile, active microcapsules that produce chemicals according to a catalytic reaction network (CRN). In solution, the catalytic reactions generate a force that drives the flow of the surrounding fluid. The convective flow, in turn, transports the capsules to new chemical surroundings with each successive translation. Consequently, the chemical signal produced by a cluster of capsules is critically dependent on the proximity and spatial configuration of the neighboring capsules. If all of the capsules and chemical products involved in the CRN lie within sufficient proximity, then the system develops oscillatory behavior that drives the dynamic self-assembly of capsules into larger clusters that are capable of collective action. Finally, these simulations indicate potential chemo-mechanic mechanisms that enable single cellular units, such as ameba, to organize into multicellular life forms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Wetting of a Hydrophobic Surface: Far-IR Action Spectroscopy and Dynamics of Microhydrated Naphthalene

The interaction of water and polycyclic aromatic hydrocarbons is of fundamental importance in areas as diverse as materials science and atmospheric and interstellar chemistry. The interplay between hydrogen bonding and dipole–π interactions results in subtle dynamics that are challenging to describe from first principles. Here, we employ far-IR action vibrational spectroscopy with the infrared free-electron laser FELIX to investigate naphthalene with one to three water molecules. We observe diffuse bands associated with intermolecular vibrational modes that serve as direct probes of the loose binding of water to the naphthalene surface. These signatures are poorly reproduced by static DFT or Møller–Plesset computations. Instead, a rationalization is achieved through Born–Oppenheimer Molecular Dynamics simulations, revealing the active mobility of water over the surface, even at low temperatures. Therefore, our work provides direct insights into the wetting interactions associated with shallow potential energy surfaces while simultaneously demonstrating a solid experimental–computational framework for their investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Doe Nuclear Forensics Player Injection Tool

The code is intended for mobile devices and provides simulated localized fallout environment information to players participating in DOE Forensics training exercises.

Thompson, ScottJ. [Idaho National Laboratory (INL)↗
DOE OSTI2023

Energy-Efficient Maneuvering of Connected and Automated Vehicles (CAVs) with Situational Awareness at Intersections (Final Progress Report)

The increased development of Connected and Automated Vehicle (CAV) systems, currently used for safety and driver convenience, presents new opportunities to improve the energy efficiency of vehicles. Southwest Research Institute (SwRI) achieved a 20% energy consumption reduction in a 2017 Toyota Prius Prime plug-in hybrid by using connectivity (V2V, V2I, V2X) as part of the Next Generation Energy Technologies for Connected and Automated on-Road Vehicles (NEXTCAR) program. The energy consumption gains were achieved by a combination of vehicle dynamics and powertrain control algorithms with a focus on SAE L1 and L2 automated vehicles where a human is still responsible for safe operation. SwRI is now involved in NEXTCAR-II, focusing on energy-efficient control tech for SAE Level 4/5 automated vehicles, aiming for a 30% energy reduction compared to stock hybrids. The rise of Mobility as a Service (MaaS) is driving investments in L4 and L5 automated vehicles. A study by the University of Michigan shows these vehicles might increase energy use and emissions by 3-20%. Technology similar to NEXTCAR can enhance energy efficiency in highly automated vehicles, leveraging improved sensing and actuation capabilities. While the NEXTCAR programs targeted energy efficiency improvements for a single vehicle, this program adopts a more expansive approach. It places its focus on understanding and testing the cumulative effects within a region or corridor, aiming to assess how a subset of vehicles equipped with NEXTCAR-style technologies influence the overall energy consumption of all vehicles traveling within that area. Additionally, the program explores infrastructure-based mobility solutions to optimize efficiency, and seeks to understand and quantify public perception and likelihood of technology adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗
DOE OSTI2021

FY2020 Energy Efficient Mobility Systems Annual Progress Report

EEMS Program activities during FY 2020 focused on analytical research and large-scale modeling and simulation to understand the impacts that new mobility technologies and services will have at the vehicle-, traveler-, and overall transportation system-level. This research included the development of a multi-fidelity, end-to-end transportation system models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results from projects within each of the EEMS activity areas. The Computational Modeling and Simulation key activity area summarizes work within the sub-areas of (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) Artificial Intelligence, High-Performance Computing, and Data Analytics, and (3) Core Simulation and Evaluation Tools. Additionally, the program’s advanced R&D projects are summarized within (4) the Connectivity and Automation Technology key activity area. Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A system of shared autonomous vehicles for Chicago: Understanding the effects of geofencing the service

With autonomous vehicles (AVs) still in the testing phase, researchers and planners must resort to simulation techniques to explore possible futures regarding shared and automated mobility. An agent-based discrete-event transport simulator, POLARIS, is used in this study to simulate travel in the 20-county Chicago region with a shared AV (SAV) mobility option. Using this framework, the effect of an SAV fleet on system performance when constrained to serve within geofences is studied under four distinct scenarios: service restricted to the city, to the city plus suburban core, to the core plus exurban areas, and to the entire region — along with the choice of dynamic ridesharing (DRS) versus solo travel in an SAV. Results indicate that service areas need a balanced mix of trip generators and attractors, and an SAV fleet’s empty VMT (eVMT) can be noticeably reduced through suitable geofencing and DRS. Geofences can also help lower response times, reduce systemwide VMT across all modes, and ensure uniform access to SAVs. DRS is most useful in lowering VMT and %eVMT that arises from sprawled land development, but with insufficient demand to share rides, savings from the use of geofences is higher. Geofences targeting neighborhoods with high trip density bring about low response times and %eVMT, but fleet sizes in these regions need to be designed for uniformly low response times throughout a large region, as opposed to maximizing vehicle use in a 24-hour day.

33 ADVANCED PROPULSION SYSTEMS↗