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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

NREL Evaluates Performance of Hydraulic Hybrid Refuse Vehicles

This highlight describes NREL's evaluation of the in-service performance of 10 next-generation hydraulic hybrid refuse vehicles (HHVs), 8 previous-generation (model year 2013) HHVs, and 8 comparable conventional diesel vehicles operated by Miami-Dade County's Public Works and Waste Management Department in southern Florida. Launched in March 2015, the on-road portion of this 12-month evaluation focuses on collecting and analyzing vehicle performance data - fuel economy, maintenance costs, and drive cycles - from the HHVs and the conventional diesel vehicles. The fuel economy of heavy-duty vehicles, such as refuse trucks, is largely dependent on the load carried and the drive cycles on which they operate. In the right applications, HHVs offer a potential fuel-cost advantage over their conventional counterparts. This advantage is contingent, however, on driving behavior and drive cycles with high kinetic intensity that take advantage of regenerative braking. NREL's evaluation will assess the performance of this technology in commercial operation and help Miami-Dade County determine the ideal routes for maximizing the fuel-saving potential of its HHVs. Based on the field data, NREL will develop a validated vehicle model using the Future Automotive Systems Technology Simulator, also known as FASTSim, to study the impacts of route selection and other vehicle parameters. NREL is also analyzing fueling and maintenance data to support total-cost-of-ownership estimations and forecasts. The study aims to improve understanding of the overall usage and effectiveness of HHVs in refuse operation compared to similar conventional vehicles and to provide unbiased technical information to interested stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Fully nonlinear δf gyrokinetics for scrape-off layer parallel transport

Edge plasmas present a few challenges for gyrokinetic simulations that are absent in tokamak cores. Among them are large fluctuation amplitudes and plasma-wall interactions in the open field line region. In this work, the widely used core turbulence code GENE, which employs a δf -splitting technique, is extended to simulate open systems with large electrostatic fluctuations. With inclusion and proper discretization of the parallel nonlinear term, it becomes equivalent to a full- f code and the δf -splitting causes no fundamental difficulty in handling large fluctuations. The loss of particles to the wall is accounted for by using a logical sheath boundary, which is implemented in the context of a finite-volume method. The extended GENE code is benchmarked for the well-established one-dimensional parallel transport problem in the scrape-off layer during edge-localized modes. The parallel heat flux deposited onto the divertor target is compared with previous simulation results and shows good agreement.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Ab initio study of Ga-GaN system: Transition from adsorbed metal atoms to a metal–semiconductor junction

Ab initio studies of a GaN(0001)-Ga system with various thicknesses of a metallic Ga layer were undertaken. The studied systems extend from a GaN(0001) surface with a fractional coverage of gallium atoms to a Ga-GaN metal–semiconductor (m–s) contact. Electronic properties of the system are simulated using density functional theory calculations for different doping of the bulk semiconductor. It is shown that during transition from a bare GaN(0001) surface to a m–s heterostructure, the Fermi level stays pinned at a Ga-broken bond highly dispersive surface state to Ga–Ga states at the m–s interface. Adsorption of gallium leads to an energy gain of about 4 eV for a clean GaN(0001) surface and the energy decreases to 3.2 eV for a thickly Ga-covered surface. The transition to the m–s interface is observed. For a thick Ga overlayer such interface corresponds to a Schottky contact with a barrier equal to 0.9 and 0.6 eV for n- and p-type, respectively. Bond polarization-related dipole layer occurring due to an electron transfer to the metal leads to a potential energy jump of 1.5 eV, independent on the semiconductor doping. Additionally high electron density in the Ga–Ga bond region leads to an energy barrier about 1.2 eV high and 4 Å wide. This feature may adversely affect the conductivity of the n-type m–s system.

42 ENGINEERING↗
DOE OSTI2018

Adaptive enhanced sampling by force-biasing using neural networks

A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables smooth estimates of generalized forces in sparsely sampled regions, force estimates in previously unexplored regions, and continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. Furthermore, the method is also found to provide improvements over previous implementations of neural network assisted algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Maturation of biomass‐to‐biofuels conversion technology pathways for rapid expansion of biofuels production: a system dynamics perspective

Abstract The Biomass Scenario Model ( BSM ) is a system‐dynamics simulation model intended to explore the potential for rapid expansion of the biofuels industry. The model is not predictive — it uses scenario assumptions based on various types of data to simulate industry development, emphasizing how incentives and technological learning‐by‐doing might accelerate industry growth. The BSM simulates major sectors of the biofuels industry, including feedstock production and logistics, conversion, distribution, and end uses, as well as interactions among sectors. The model represents conversion of biomass to biofuels as a set of technology pathways, each of which has allowable feedstocks, capital and operating costs, allowable products, and other defined characteristics. This study and the BSM address bioenergy modeling analytic needs that were identified in recent literature reviews. Simulations indicate that investments are most effective at expanding biofuels production through learning‐by‐doing when they are coordinated with respect to timing, pathway, and target sector within the biofuels industry. Effectiveness metrics include timing and magnitude of increased production, incentive cost and cost effectiveness, and avoidance of windfall profits. Investment costs and optimal investment targets have inherent risks and uncertainties, such as the relative value of investment in more‐mature versus less mature pathways. These can be explored through scenarios, but cannot be precisely predicted. Dynamic competition, including competition for cellulosic feedstocks and ethanol market shares, intensifies during times of rapid growth. Ethanol production increases rapidly, even up to Renewable Fuel Standards‐targeted volumes of biofuel, in simulations that allow higher blending proportions of ethanol in gasoline‐fueled vehicles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts, Biorefining published by John Wiley & Sons, Ltd on behalf of Society of Chemical Industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Timescales of secondary organic aerosols to reach equilibrium at various temperatures and relative humidities

Abstract. Secondary organic aerosols (SOA) account for a substantial fraction of air particulate matter, and SOA formation is often modeled assuming rapid establishment of gas–particle equilibrium. Here, we estimate the characteristic timescale for SOA to achieve gas–particle equilibrium under a wide range of temperatures and relative humidities using a state-of-the-art kinetic flux model. Equilibration timescales were calculated by varying particle phase state, size, mass loadings, and volatility of organic compounds in open and closed systems. Model simulations suggest that the equilibration timescale for semi-volatile compounds is on the order of seconds or minutes for most conditions in the planetary boundary layer, but it can be longer than 1 h if particles adopt glassy or amorphous solid states with high glass transition temperatures at low relative humidity. In the free troposphere with lower temperatures, it can be longer than hours or days, even at moderate or relatively high relative humidities due to kinetic limitations of bulk diffusion in highly viscous particles. The timescale of partitioning of low-volatile compounds into highly viscous particles is shorter compared to semi-volatile compounds in the closed system, as it is largely determined by condensation sink due to very slow re-evaporation with relatively quick establishment of local equilibrium between the gas phase and the near-surface bulk. The dependence of equilibration timescales on both volatility and bulk diffusivity provides critical insights into thermodynamic or kinetic treatments of SOA partitioning for accurate predictions of gas- and particle-phase concentrations of semi-volatile compounds in regional and global chemical transport models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Design and Analysis of an Integral MPPT Control Law for Wave Energy Conversion Systems

In this paper, we propose an integral-based maximum power point tracking (MPPT) algorithm for point absorber wave energy conversion (WEC) systems. A permanent magnet synchronous generator (PMSG) is coupled to the point absorber and its drive implements the proposed MPPT control. While the rotating frame of reference of the PMSG implements power control, the slower mechanical frequency of the incident waves are processed with an additional transformation that yields another set of dc dynamics. The computed dc power in the new reference frame, which is focused on slow wave dynamics, is input to the MPPT control law that tunes the emulated resistance of the machine drive to extract peak power from the wave absorber device. We derive a stability condition for the proposed controller and validate our control design on a simulated 10kW system.

wave energy, maximum power point tracking (MPPT), ↗
DOE OSTI2025

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions↗
DOE OSTI2020

Hydrodynamic Interactions in Topologically Linked Ring Polymers.

Despite decades of interdisciplinary research on topologically linked ring polymers, their dynamics remain largely unstudied. These systems represent a major scientific challenge as they are often subject to both topological and hydrodynamic interactions (HI), which render dynamical solutions either mathematically intractable or computationally prohibitive. Here we circumvent these limitations by preaveraging the HI of linked rings. We show that the symmetry of ring polymers leads to a hydrodynamic decoupling of ring dynamics. This decoupling is valid even for nonideal polymers and nonequilibrium conditions. Physically, our findings suggest that the effects of topology and HI are nearly independent and do not act cooperatively to influence polymer dynamics. We use this result to develop highly efficient Brownian dynamics algorithms that offer enormous performance improvements over conventional methods and apply these algorithms to simulate catenated ring polymers at equilibrium, confirming the independence of topological effects and HI. The methods developed here can be used to study and simulate large systems of linked rings with HI, including kinetoplast DNA, Olympic gels, and poly[n]catenanes.

Rauscher, Phillip M.↗
DOE OSTI2015

Utilizing gas-filled cavities for the generation of an intense muon source

A key requirement for designing intense muon sources is operating rf cavities in multi-tesla magnetic fields. Recently, a proof-of-principle experiment demonstrated that an rf cavity filed with high pressure hydrogen gas could meet this goal. In this study, rigorous simulation is used to design and evaluate the performance of an intense muon source with gas filled cavities. We present a new lattice design and compare our results with conventional schemes. We detail the influence of gas pressure on the muon production rate.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Hidden Rotation Symmetry of the Jordan–Wigner Transformation and Its Application to Measurement in Quantum Computation

Using a global rotation by 𝜃 about the z-axis in the spin sector of the Jordan–Wigner transformation rotates Pauli matrices 𝑋̂ and 𝑌̂ in the 𝑥−𝑦 -plane, while it adds a global complex phase to fermionic quantum states that have a fixed number of particles. With the right choice of angles, this relates expectation values of Pauli strings containing products of 𝑋̂ and 𝑌̂ to different products, which can be employed to reduce the number of measurements needed when simulating fermionic systems on a quantum computer. Here, we derive this symmetry and show how it can be applied to systems in Physics and Chemistry that involve Hamiltonians with only single-particle (hopping) and two-particle (interaction) terms. We also discuss the consequences of this for finding efficient measurement circuits in variational ground state preparation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Comparison of Coarse-Grained Approaches in Predicting Polymer Nanocomposite Phase Behavior

Because of the considerable parameter space, efficient theoretical and simulation methods are required to predict the morphology and guide experiments in polymer nanocomposites (PNCs). Unfortunately, theoretical and simulation methods are restricted in their ability to accurately map to experiments based on necessary approximations and numerical limitations. In this study, we provide direct comparisons of two recently developed coarse-grained approaches for modeling polymer nanocomposites (PNCs): polymer nanocomposite field theory (PNC-FT) and dynamic mean-field theory (DMFT). These methods are uniquely suited to efficiently capture mesoscale phase behavior of PNCs in comparison to other theoretical and simulation frameworks. We demonstrate the ability of both methods to capture macrophase separation and describe the thermodynamics of PNCs. We systematically test how the nanoparticle morphology in PNCs is affected by a uniform probability distribution of grafting sites, common in field-based methods, versus random discrete grafting sites on the nanoparticle surface. We also analyze the accuracy of the mean-field approximation in capturing the phase behavior of PNCs. Moreover, the DMFT method introduces the ability to describe nonequilibrium phase behavior while the PNC-FT method is strictly an equilibrium method. With the DMFT method we are able to show the evolution of nonequilibrium states toward their equilibrium state and a qualitative assessment of the dynamics in these systems. These simulations are compared to experiments consisting of polystyrene grafted gold nanorods in a poly(methyl methacrylate) matrix to ensure the model gives results that qualitatively agree with the experiments. This study reveals that nanoparticles in a relatively high matrix molecular weight are trapped in a nonequilibrium state and demonstrates the utility of the DMFT framework in capturing nonequilibrium phase behavior of PNCs. In conclusion, both the PNC-FT and DMFT framework are promising methods to describe the thermodynamic and nonequilibrium phase behavior of PNCs.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-T-448: On the Perturbation Factor P-cav of the Markus Parallel Plate Ion Chambers in Clinical Electron Beams, Monte Carlo Based Reintegration of An Historical Experiment

Purpose: All present dosimetry protocols recommend well-guarded parallel-plate ion chambers for electron dosimetry. For the guard-less Markus chamber an energy dependent fluence perturbation correction pcav is given. This perturbation correction was experimentally determined by van der Plaetsen by comparison of the read-out of a Markus and a NACP chamber, which was assumed to be “perturbation-free”. Aim of the present study is a Monte Carlo based reiteration of this experiment. Methods: Detailed models of four parallel-plate chambers (Roos, Markus, NACP and Advanced Markus) were designed using the Monte Carlo code EGSnrc and placed in a water phantom. For all chambers the dose to the active volume filled with low density water was calculated for 13 clinical electron spectra (E{sub 0}=6-21 MeV) at the depth of maximum and at the reference depth under reference conditions. In all cases the chamber's reference point was positioned at the depth of measurement. Moreover, the dose to water DW was calculated in a small water voxel positioned at the same depth. Results: The calculated dose ratio D{sub NACP}/D{sub Markus}, which according to van der Plaetsen reflects the fluence perturbation correction of the Markus chamber, deviates less from unity than the values given by van der Plaetsen's but exhibits a similar energy dependence. The same holds for the dose ratios of the other well guarded chambers. But, in comparison to water, the Markus chamber reveals the smallest overall perturbation correction which is nearly energy independent at both investigated depths. Conclusion: The simulations principally confirm the energy dependence of the dose ratio D{sub NACP}/D{sub Markus} as published by van der Plaetsen. But, as shown by our simulations of the ratio D{sub W}/D{sub Markus}, the conclusion drawn in all dosimetry protocols is questionable: in contrast to all well-guarded chambers the guard-less Markus chamber reveals the smallest overall perturbation correction and also the smallest energy dependence.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Data-Driven Simulation-Based Planning for Electric Airport Shuttle Systems: A Real-World Case Study

Many airports are adopting battery electric buses in their shuttle fleets due to concerns over air quality and regulations. This study proposes a simulation-based optimization modeling framework to help airport shuttle operators effectively deploy electric buses. We evaluated a planned airport electric shuttle system with an event-driven simulator. Empirical data collected from existing systems were used to drive the simulations. We then proposed a simulation-based optimization model to determine the battery capacity, charging power, and number of chargers so that predefined objective(s) (e.g., minimizing total capital cost, minimizing emissions) are optimized. Compared to existing studies, the primary contribution of the proposed method is that it can model the real-world stochastic nature of operations in an electric bus system with much higher fidelity. To demonstrate the proposed modeling framework, we study a real-world shuttle system at the Dallas-Fort Worth International Airport, and present extensive numerical studies. When considering partial fleet electrification, the model can provide a set of Pareto optimal solutions. When considering full fleet electrification, the optimal solution requires a 50-kWh battery capacity and four 210-kW chargers, resulting in a total capital cost of $26,744,000. The results demonstrate that the proposed modeling framework can effectively optimize the planning of electric airport shuttle systems with partial or full fleet electrification.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Phase evolution in two-phase alloys during severe plastic deformation

Herein, phase evolution in FCC metals with strongly interacting alloy components during severe plastic deformation is investigated using molecular dynamics simulations. Specifically, we study the alloy microstructure in steady state, nucleation and growth of precipitates in supersaturated alloys, and the decomposition of precipitates in undersaturated alloys. The results are compared to a modified effective temperature model, providing a physical understanding for the atomic processes underlying the model and a perspective on its strengths and weaknesses. Key observations in this work are nucleation and growth of precipitates during SPD at a temperature of 100 K; Gibbs-Thomson-like behavior relating solubility to precipitate size under steady-state shearing; a direct relationship between the effective temperature and the shear modulus; and the importance of cluster agglomeration during precipitate growth. The study also reveals that the mechanisms of forced chemical mixing depends on precipitate size, adding complications for effective temperature models describing inhomogeneous systems. The simulations are shown to provide good semiquantitative agreement with experimental findings reported in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of disorder on antidot vortex Majorana states in three-dimensional topological insulators

Topological insulator/superconductor two-dimensional heterostructures are promising candidates for realizing topological superconductivity and Majorana modes. In these systems, a vortex pinned by a prefabricated antidot in the superconductor can host Majorana zero-energy modes (MZMs), which are exotic quasiparticles that may enable quantum information processing. However, a major challenge is to design devices that can manipulate the information encoded in these MZMs. One of the key factors is to create small and clean antidots, so the MZMs, localized in the vortex core, have a large gap to other excitations. If the antidot is too large or too disordered, the level spacing for the subgap vortex states may become smaller than temperature. In this paper, we numerically investigate the effects of disorder, chemical potential, and antidot size on the subgap vortex spectrum, using a two-dimensional effective model of the topological insulator surface. Our model allows us to simulate large system sizes with vortices up to 1.8 µ⁢m in diameter (with a 6 nm lattice constant). We also compare our disorder model with the transport data from existing experiments. As a result, we find that the spectral gap can exhibit a nonmonotonic behavior as a function of disorder strength, and that it can be tuned by applying a gate voltage.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Dual radio frequency plasma source: Understanding via electrical asymmetry effect

On the basis of the global model, the influences of driving voltage and frequency on electron heating in geometrically symmetrical dual capacitively coupled radio frequency plasma have been investigated. Consistent with the experimental and simulation results, non-monotonic behavior of dc self bias and plasma heating with increasing high frequency is observed. In addition to the local maxima of plasma parameters for the integer values of the ratio between the frequencies ({xi}), ourstudies also predict local maxima for odd integer values of 2{xi} as a consequence of the electrical asymmetry effect produced by dual frequency voltage sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗