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At least 37 records · Page 2

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DOE OSTI2019

High-frequency, high-power performance of AlGaN-channel high-electron-mobility transistors: an RF simulation study [High-frequency high power performance of AlGaN channel HEMTs: an RF simulation study]

The emerging Al-rich AlGaN-channel Al x Ga 1–x N/Al y Ga 1–y N high-electron-mobility transistors (HEMTs) with 0.7 ≤ y < x ≤ 1.0 have the potential to greatly exceed the power handling capabilities of today's GaN HEMTs, possibly by five times. This projection is based on the expected 4× enhancement of the critical electric field, the 2× enhancement of sheet carrier density, and the parity of the electron saturation velocity for Al-rich AlGaN-channel HEMTs relative to GaN-channel HEMTs. In this paper, the expected increased RF power density in Al-rich AlGaN-channel HEMTs is calculated by theoretical analysis and computer simulations, based on existing data on long-channel AlGaN devices. It is shown that a saturated power density of 18 W mm –1 , a power-added efficiency of 55% and an output third-order intercept point over 40 dB can be achieved for this technology. Furthermore, the method for large-signal RF performance estimation presented in this paper is generic and can be applied to other novel high-power device technologies at the early stages of development.

42 ENGINEERING↗

DOE OSTI2020

Integrating Overhead Camera Imagery with Reinforcement Learning to Improve Fuel Economy Through Adaptive Traffic Control

Overhead cameras have been deployed for some time as a sensor for traffic control, with many advantages over conventional inductive loop sensors in terms of robustness, ease of installation, and simplicity with respect to maintenance. We explore the utility of such imagery (in particular, fisheye lens cameras) for intelligent traffic control in real-time using reinforcement learning, with a goal of improving fuel economy for the overall intersection and grid of intersections. We summarize our initial work in data collection and approach to ascertain the ability to visually sense vehicular fuel consumption using real-world data. We then describe our deep reinforcement learning topology to test adaptive control informed by the camera capabilities. Next, we tested the proof-of-concept through a variety of simulation scenarios using the Simulation of Urban Mobility (SUMO) traffic simulator, which included different estimates on vehicle classifications, different traffic distributions, and different traffic densities. Six different control policies were tested ranging from simple timing, to heuristic visual-based methods, to actual policies learned via the reinforcement learning approach. Our results demonstrate the feasibility of the approach for controlling traffic lights for better fuel efficiency based on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗

DOE OSTI2023

Emerging Trends in Freight [Slides]

Freight transportation accounts for only 5% of the vehicles on U.S. roads, but 10% of vehicle miles of travel and 27% of on-road energy use. With rail and water, freight accounts for 28% of U.S. transportation energy and emissions. Trucking is the primary mode for transporting goods, but rail is a significant mode for longer shipments. Economic, technological, and operational trends pose both challenges and opportunities to meet U.S. demand for goods movement as well as national decarbonization goals. This presentation provides a systems perspective for energy efficiency freight mobility and an overview of available NREL analytical tools to address these challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗

DOE OSTI2022

HIVE™ [SWR-19-36]

The HIVE™ platform is a mobility services simulation platform developed to provide insight on the energy, infrastructure, service, and economic outcomes of various mobility as a service (MaaS) options. The HIVE platform takes a set of spatiotemporal travel origin-destination pairs and simulates the operation of a predefined mobility service fleet, incorporating request pooling, and various operational and charging behaviors. Hive specializes at modeling fleets of automated electric vehicles (AEVs) and can be used to site and size direct current fast charge (DCFC) stations and measure grid impacts of large-scale AEV fleets serving real-world MaaS trip demand (similar to taxis, Uber, Lyft, etc.). Potential outcomes from a Hive simulation include level of service, total vehicle miles traveled (VMT), deadheading (zero passenger) miles, simultaneous and total energy loads, average occupancy, and more. Hive is developed to generalize to new regions and can be customized to handle many scenarios and operating conditions.

Rames, Clement↗

DOE OSTI2025

A general kinetic framework for dislocation mobility derived from probabilistic cellular automaton simulations of the kink-pair mechanism

Dislocation mobility laws are essential components of dislocation-density-based crystal plasticity models. For dislocations governed by the kink-pair mechanism, however, existing formulations are typically limited to specific regimes due to the com plex interplay between stochastic kink-pair nucleation and lateral kink migration. In this work, we develop a general kinetic framework that expresses the average dislocation velocity as a function of mechanism-level variables: positive/negative kink pair nucleation rates, kink migration velocity, dislocation segment length, critical kink-pair width, and kink height. Probabilis tic cellular automaton simulations are used to capture the behavior of conceptual dislocation segments between the limiting conditions of migration outpacing nucleation on the one end and nucleation outpacing migration on the other. An elemen tary functional form that captures the system dynamics is suggested and fitted against the simulation results. This framework remains valid for arbitrary combinations of the six variables and is, therefore, compatible with any admissible constitutive re lations that describe their stress and temperature dependence. Comparisons with established approaches and experimental results confirm the robustness and physical consistency of the formulation, making it broadly applicable to material systems in which dislocation motion is governed by the kink-pair mechanism.

36 MATERIALS SCIENCE↗

DOE OSTI2017

A collision model for grain-resolving simulations of flows over dense, mobile, polydisperse granular sediment beds

We present a collision model for phase-resolved Direct Numerical Simulations of sediment transport that couple the fluid and particles by the Immersed Boundary Method. Typically, a contact model for these types of simulations comprises a lubrication force for particles in close proximity to another solid object, a normal contact force to prevent particles from overlapping, and a tangential contact force to account for friction. Our model extends the work of previous authors to improve upon the time integration scheme to obtain consistent results for particle-wall collisions. Furthermore, we account for polydisperse spherical particles and introduce new criteria to account for enduring contact, which occurs in many sediment transport situations. This is done without using arbitrary values for physically-defined parameters and by maintaining the full momentum balance of a particle in enduring contact. Lastly, we validate our model against several test cases for binary particle-wall collisions as well as the collective motion of a sediment bed sheared by a viscous flow, yielding satisfactory agreement with experimental data by various authors.

42 ENGINEERING↗

DOE OSTI2026

Open-Source Data for MAC-POSTS: Mobility Data Analytics Center - Prediction, Optimization, and Simulation Toolkit for Transportation Systems

MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems) is a toolkit for dynamic transportation network modeling. Developed by the Mobility Data Analytics Center (MAC) at Carnegie Mellon University, this package implements many classic dynamic transportation network models, as well as new models proposed by MAC members. It has served as one building block for many other models and research projects. As such, this package used to be treated as an internal research project of the MAC lab, and admittedly, the code base is messy, and the interface is hard to use. However, we are working hard to make it a generally usable and useful toolkit for dynamic transportation network modeling. We would really appreciate any feedback, comments, suggestions, or criticisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure↗

DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Pair mobility functions for rigid spheres in concentrated colloidal dispersions: Force, torque, translation, and rotation

The formulation of detailed models for the dynamics of condensed soft matter including colloidal suspensions and other complex fluids requires accurate description of the physical forces between microstructural constituents. In dilute suspensions, pair-level interactions are sufficient to capture hydrodynamic, interparticle, and thermodynamic forces. In dense suspensions, many-body interactions must be considered. Prior analytical approaches to capturing such interactions such as mean-field approaches replace detailed interactions with averaged approximations. However, long-range coupling and effects of concentration on local structure, which may play an important role in, e.g., phase transitions, are smeared out in such approaches. An alternative to such approximations is the detailed modeling of hydrodynamic interactions utilizing precise couplings between moments of the hydrodynamic traction on a suspended particle and the motion of that or other suspended particles. For two isolated spheres, a set of these functions was calculated by Jeffrey and Onishi [J. Fluid Mech. 139, 261–290 (1984)] and Jeffrey [J. Phys. Fluids 4, 16–29 (1992)]. Along with pioneering work by Batchelor, these are the touchstone for low-Reynolds-number hydrodynamic interactions and have been applied directly in the solution of many important problems related to the dynamics of dilute colloidal dispersions [G. K. Batchelor and J. T. Green, J. Fluid Mech. 56, 375–400 (1972) and G. K. Batchelor, J. Fluid Mech. 74, 1–29 (1976)]. Toward extension of these functions to concentrated systems, here we present a new stochastic sampling technique to rapidly calculate an analogous set of mobility functions describing the hydrodynamic interactions between two hard spheres immersed in a suspension of arbitrary concentration, utilizing accelerated Stokesian dynamics simulations. These mobility functions provide precise, radially dependent couplings of hydrodynamic force and torque to particle translation and rotation, for arbitrary colloid volume fraction ϕ. The pair mobilities (describing entrainment of one particle by the disturbance flow created by another) decay slowly with separation distance: as 1/r, for volume fractions 0.05 ≤ ϕ ≤ 0.5. For the relative mobility, we find an initially rapid growth as a pair separates, followed by a slow, 1/r growth. Up to ϕ ≤ 0.4, the relative mobility does not reached the far-field value even beyond separations of many particle sizes. In the case of ϕ = 0.5, the far-field asymptote is reached but only at a separation of eight radii and after a slow 1/r growth. At these higher concentrations, the coefficients also reveal liquid-like structural effects on pair mobility at close separations. These results confirm that long-range many-body hydrodynamic interactions are an essential part of the dynamics of concentrated systems and that care must be taken when applying renormalization schemes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Dynamic traffic routing in a network with adaptive signal control

In real traffic networks, travellers’ route choice is affected by traffic control strategies. In this work, we capture the interaction between travellers’ route choice and traffic signal control in a coherent framework. For travellers’ route choice, a VANET (Vehicular Ad hoc NETwork) is considered, where travellers have access to the real-time traffic information through V2V/V2I (Vehicle to Vehicle/Vehicle to Infrastructure) infrastructures and make route choice decisions at each intersection using hyper-path trees. We test our algorithm and control strategy by simulation in OmNet++ (A network communication simulator) and SUMO (Simulation of Urban MObility) under several scenarios. The simulation results show that with the proposed dynamic routing, the overall travel cost significantly decreases. Lastly, it is also shown that the proposed adaptive signal control reduces the average delay effectively, as well as reduces the fluctuation of the average speed within the whole network.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

A Systems Biology and Pond Culture-based Understanding and Improvement of Metabolic Processes Related to Productivity in Diverse Microalgal Classes for Viable Biofuel Production

The overarching goal of this project was to understand and manipulate fundamental molecular mechanisms involved in maximizing growth rate and lipid accumulation in diverse classes of microalgae under authentic diurnal conditions to enhance production capabilities for biofuels. The research was aimed at filling two critical knowledge gaps by addressing fundamental cellular issues that govern growth and fuel molecule accumulation in conjunction with realistic climate-simulated cultivation: 1) The insufficient understanding of the effect of metabolic topology on cellular carbon partitioning and its regulation with regards to productivity. 2) The understudied effect of the diurnal and cell cycles on cellular metabolism, resource allocation, and resource mobilization under simulated production conditions. To unravel broader as well as lineage-specific regulatory mechanisms that determine productivity, we compared green algae with diatoms. Complementing the systems approach with a pond-based cultivation method under authentic diurnal conditions, we anticipated an understanding of how the effect of diurnal and cell cycles affects growth and lipid productivity. Elucidation of the topology and regulation of relevant metabolic networks in proposed new model organisms was expected to enable improvements in functional capabilities and biosynthetic pathways. The major goals of the project were achieved by the following accomplishments. Genome assemblies and functional annotations for the green algae S. obliquus strain DOE0152Z and Coleastrella sp. strain DOE0202. Development of a metabolic map for the core carbon metabolism for S. obliquus. Analyzed the cellular topology for the core carbon network and proposed differences in core carbon metabolism for the Chlorophyceae versus the Trebouxiophyceae. Discovered the genes for enzymes involved in dicarboxylic acid metabolism and proposed the existence of C4-type metabolism for S. obliquus. Calculated the energy and reducing equivalencies for TAG and isoprenoid biosynthesis based on the core carbon network created in this project. Identified one newly created strain SOM-P004 (UV-Mutagenesis), which performed better at higher culture densities than wild type in LEAPS reactors under simulated environmental conditions. Results obtained within the course of this project were used in 2017 to apply for a Community Science Program (CSP) at the DOE Joint Genome Institute (JGI). The project (JGI Proposal Id: 503423) with the Title “Comparative genomics and germ plasm diversity in Acutodesmus, a green microalgal bioenergy feedstock candidate with potential for breeding and hybridization.” was selected for CSP 2018 for sequencing of up to 30 genomes of the alga A. obliquus (=S. obliquus). Our genome of the strain DOE0152Z serves as a reference for this new CSP project. Characterization of synchronized cultures of Cyclotella cryptica and the implications on productivity. Determination that some cellular pigments respond to light, but others to the cell cycle. Characterization of productivity of C. cryptica in PNNL ponds. Genome sequence and metabolic mapping of Marinichlorella kaistiae KAS603. Demonstration that some green algae store and utilize starch in the cytoplasm. Photorespiratory pathway clarified in T. pseudonana leading to a better understanding of carbon flux pathways in diatoms. Genome sequence determination, annotation, and comparison completed for C. cryptica, identifying potential metabolic differences that lead to high biomass and lipid accumulation ability for this species. Transcriptomic comparison of silicon (Si) and nitrogen (N) limited triacylglycerol accumulation in Cyclotella cryptica.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Investigating a Renewable-Resource-Targeting Mobile Aquaculture System Using Route Optimization Based on Optimal Foraging Theory

Aquaculture systems require careful consideration of location, which determines water conditions, pollution impacts, and hazardous conditions. Mobility may be able to address these factors while also supporting the targeting of renewable energy sources such as wind, wave, and solar power throughout the year. In this paper, a purpose-built mobile aquaculture ship is identified and modeled with a combination of renewable energy harvesting capabilities as a case study with the objective of assessing the potential benefits of targeting high renewable energy potentials to power aquaculture operations. A route optimization algorithm is created and tuned to simulate the mobility of the aquaculture platform and cost-basis comparisons are made to a stationary system. The small spatial variability in renewable energy potential when combining multiple resources significantly limits the benefits of a mobile, renewable-targeting aquaculture system. On the other hand, the consistent energy harvest from a blend of renewable energy types (13 kW installed wind capacity, 661 m 2 installed solar, and 1 m characteristic width wave-energy converter) suggests that the potential benefits of a mobile platform for offshore aquaculture (mitigation of environmental and social concerns, any potential positive impact on yields, hazard avoidance, etc.) can likely be pursued without significant increases in energy harvester costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Coherence in Polycrystalline Thin Films of Twisted Molecular Crystals

Helicoidal crystallites in rhythmically banded spherulites manifest spectacular optical patterns in small molecules and polymers. It is shown that concentric optical bands indicating crystallographic orientations typically lose coherence (in-phase twisting) with growth from the center of nucleation. Here, coherence is shown to increase as the twist period decreases for seven molecular crystals grown from the melt. This dependence was correlated to crystallite fiber thickness and length, as well as crystallite branching frequency, a parameter that was extracted from scanning electron micrographs, and supported by numerical simulations. Hole mobilities for 2,5-didodecyl-3,6-di(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione (DPP-C12) measured by using organic field-effect transistors demonstrated that more incoherent boundaries between optical bands in spherulites lead to higher charge transport for films with the same twist period. This was rationalized by combining our growth model with electrodynamic simulations. This work illustrates the emergence of complexity in crystallization processes (spherulite formation) that arises in the extra variable of helicoidal radial twisting. The details of the patterns analyzed here link the added complexity in crystal growth to the electronic and optical properties of the thin films.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Mechanism of monovalent and divalent ion mobility in Nafion membrane: An atomistic simulation study

Polymer cation exchange membranes (CEMs) are widely used in water treatment processes. The fundamental factors that control the separation and selectivity of cations with different valences in CEMs are not fully understood. In this study, we use atomistic molecular dynamics simulations to investigate the underlying molecular mechanisms that control the mobility of cations with different valences in Nafion membranes. Our results indicate structural differences in binding of monovalent and divalent cations, which gives rise to differences in ion diffusion in Nafion. Monovalent cations are shown to be “territorially” bound, i.e., bound while partially hydrated, to the fixed charge groups whereas divalent cations are shown to be “site” bound, i.e., bound while fully dehydrated, to the charge groups on the polymer. This difference in binding structure gives rise to differences in transport characteristics of cations in Nafion.

Chemistry↗

DOE OSTI2017

A water-based fast integrated mobility spectrometer (WFIMS) with enhanced dynamic size range

We developed a water-based fast integrated mobility spectrometer (WFIMS) with enhanced dynamic size range. The WFIMS builds on two established technologies: the fast integrated mobility spectrometer and laminar flow water-based condensation methodology. Inside WFIMS, particles of differing electrical mobility are separated in a drift tube and subsequently enlarged through water condensation. Particle size and concentration are measured via digital imaging at a frame rate of 10 Hz. When we measure particles of different mobilities simultaneously, the WFIMS resolves particle diameters ranging from 8 to 580 nm within 1 s or less. The performance of WFIMS was characterized with differential mobility analyzer (DMA) classified (NH 4 ) 2 SO 2 particles with diameters ranging from 8 to 265 nm. The mean particle diameters measured by WFIMS were found to be in excellent agreement with DMA centroid diameters. Furthermore, detection efficiency of WFIMS was characterized using a condensation particle counter as a reference and is nearly 100% for particles with diameter greater than 8 nm. In general, measured and simulated WFIMS mobility resolutions are in good agreement. But, some deviations are observed at low particle mobilities, likely due to the non-idealities of the WFIMS electric field.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections

Connected and Automated Vehicles (CAVs) can potentially improve the performance of the transportation system by reducing human errors. This paper investigates the safety impact of CAVs in a mixed traffic with conventional vehicles at intersections. Analyzing real-world AV crashes in California revealed that rear-end crashes at intersections are the dominant crash type. Therefore, to enhance our understanding of the future interactions between human-driven vehicles with CAVs at intersections, a simulation framework was developed to model the mixed traffic environment of Automated Vehicles (AV), cooperative AVs, and conventional human-driven vehicles. In order to model AVs driving behavior, Adaptive Cruise Control (ACC) and cooperative ACC (CACC) models are utilized. Particularly, this study explores system improvements due to automation and connectivity across varying CAV market penetration scenarios. ACC and CACC car following models are used to mimic the behavior of AVs and cooperative AVs. Real-world connected vehicle data are utilized to modify and tune the acceleration/deceleration regimes of the Wiedemann model. Next, the driving volatility concept capturing variability in vehicle speeds was utilized to calibrate the simulation to represent the safety performance of a real-world environment. Two surrogate safety measures are used to evaluate the safety performance of a representative intersection under different market penetration rate of CAVs: the number of longitudinal conflicts and driving volatility. At low levels of ACC market penetration, the safety improvements were found to be marginal, but safety improved substantially with more than 40% ACC penetration. Additional safety improvements can be achieved more quickly through the addition of cooperation and connectivity through CACC. Furthermore, ACC/CACC vehicles were found to improve mobility performance in terms of average speed and travel time at intersections.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗