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A theoretical framework combining transfer matrix method simulation and energy transfer (ET) calculation reveals critical device design guidelines for developing efficient ultrathin Si solar cells sensitized by semiconductor nanocrystals (NCs).
Abstract. An Earth system model (ESM) aerosol–cloud diagnostics package is developed to facilitate the routine evaluation of aerosols, clouds, and aerosol–cloud interactions simulated by the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). The first version focuses on comparing simulated aerosol properties with aircraft, ship, and surface measurements, which are mostly measured in situ. The diagnostics currently cover six field campaigns in four geographical regions: eastern North Atlantic (ENA), central US (CUS), northeastern Pacific (NEP), and Southern Ocean (SO). These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the Atmospheric Radiation Measurement (ARM) program and other agencies. Various types of diagnostics and metrics are performed for aerosol number, size distribution, chemical composition, cloud condensation nuclei (CCN) concentration, and various meteorological quantities to assess how well E3SM represents observed aerosol properties across spatial scales. Overall, E3SM qualitatively reproduces the observed aerosol number concentration, size distribution, and chemical composition reasonably well, but it overestimates Aitken-mode aerosols and underestimates accumulation-mode aerosols over the CUS and ENA regions, suggesting that processes related to particle growth or coagulation might be too weak in the model. The current version of E3SM struggles to reproduce the new particle formation events frequently observed over both the CUS and ENA regions, indicating missing processes in current parameterizations. The diagnostics package is coded and organized in a way that can be extended to other field campaign datasets and adapted to higher-resolution model simulations.
Weather normalization is a crucial task in several applications related to building energy conservation such as retrofit measurements and energy rating. This paper documents preliminary results found from an effort to determine a set of weather adjustment coefficients that can be used to smooth out impacts of weather on energy use of buildings in 1020 weather location sites available in the U.S. The U.S. Department of Energy (DOE) commercial reference building models are adopted as hypothetical models with standard operations to deliver consistency in modeling. The correlation between building envelop design, HVAC system design and properties for different building types and the change in heating and cooling energy consumption caused by variations in weather is examined.
Using the electromagnetic fields of an MHD simulation of magnetotail reconnection, flow bursts, and dipolarization, we further investigate the acceleration of electrons to suprathermal energies. Particular emphasis is on spatial properties and anisotropies as functions of energy and time. The simulation results are compared with Time History of Events and Macroscale Interactions during Substorms observations. The test particle approach successfully reproduces several observed injection features and puts them into a context of spatial maps of the injection region(s): a dominance of perpendicular anisotropies farther down the tail and closer to the equatorial plane, an increasing importance of parallel anisotropy closer to Earth and at higher latitudes, a drop in energy fluxes at energies below approximately 10 keV, coinciding with the plasma density drop, together with increases at higher energy, a triple peak structure of flux increases near 0 deg, 90 deg, and 180 deg, and a tendency of flux increases to extend to higher energy closer to Earth and at lower latitudes. We identified the plasma sheet boundary layers and adjacent lobes as a main source region for both increased and decreased energetic electron fluxes, related to the different effects of adiabatic acceleration at high and low energies. The simulated anisotropies tend to exceed the observed ones, particularly for perpendicular fluxes at high energies. The most plausible reason is that the MHD simulation lacks the effects of anisotropy-driven microinstabilities and waves, which would reduce anisotropies.
Purpose/Methods: Monte Carlo (MC) track structure simulations follow the primary as well as all produced secondary particles in an event-by-event manner, from starting or ejection energy down to total stopping. They provide useful information on physics and chemistry of the biological response to radiation. They depend on reliable interaction cross sections and transport models of the considered radiation quality with biologically relevant materials. Most transport models focus on sufficiently fast and bare (i.e., fully ionized) ions and cross sections calculated within the (relativistic) first Born or Bethe approximations. These theories consider the projectile as a point particle and rely on proton cross sections and simple charge-scaling methods; they neglect the atomic nature of the ion and break down at low and intermediate ion energies. Heavier ions are used in particle therapy and slow to intermediate and low energies in the biologically interesting Bragg peak. Lighter and slower fragment ions, including alpha particles, protons, and neutrons are also produced in nuclear and break up reactions of charged particles. Secondary neutrons also produce recoil protons and ions, mainly in the intermediate energy range. Results/Conclusion: This work reviews existing models for track structure simulations and cross section calculations for light and heavy ions focusing on the low and intermediate energy range. It also presents new and updated aspects on cross section calculations and simulation techniques for ions and discusses the need for new models, calculations, and experimental data.
The free energy of solvation and dissociation of hydrogen chloride in water is calculated through a combined molecular simulation quantum chemical approach at four temperatures between T = 300 and 450 K. The free energy is first decomposed into the sum of two components: the Gibbs free energy of transfer of molecular HCl from the vapor to the aqueous liquid phase and the standard-state free energy of acid dissociation of HCl in aqueous solution. The former quantity is calculated using Gibbs ensemble Monte Carlo simulations using either Kohn-Sham density functional theory or a molecular mechanics force field to determine the system’s potential energy. The latter free energy contribution is computed using a continuum solvation model utilizing either experimental reference data or micro-solvated clusters. The predicted combined solvation and dissociation free energies agree very well with available experimental data. CJM was supported by the US Department of Energy,Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.
A novel data interpretation process that utilizes comprehensive particle-in-cell (PIC) simulations is developed for the new retarding field energy analyzer (RFEA) currently being constructed at DIII-D for the lower divertor using the Divertor Material Evaluation System. Furthermore, this probe is expected to survive a heat load of up to 100 MW/m 2 for up to 5 s and reliably measure the main ion temperature (T i ) on the divertor target ranging from 10 to 200 eV. These extreme conditions posed significant engineering limitations on the probe geometry, thus extensive validation work has been performed. The conventional fitting method for the RFEA I–V characteristics is based on a simplified 1-D model without considering the ion space charge inside the probe cavity and may not be sufficient for probes designed for the DIII-D divertor environment. In this article, a more realistic description of the particle propagation process within the RFEA cavity is achieved by including both 3-D geometric effects and ion space charge in the PIC simulations, and the capability to reconstruct the ion energy distribution functions is demonstrated with reasonable consistency.
Here, we present dynamic simulations of energy-dependent losses in the radiation belt “slot region” and the formation of the two-belt structure for the quiet days after the 1 March storm. The simulations combine radial diffusion with a realistic scattering model, based data-driven spatially and temporally resolved whistler-mode hiss wave observations from the Van Allen Probes satellites. The simulations reproduce Van Allen Probes observations for all energies and L shells (2–6) including (a) the strong energy dependence to the radiation belt dynamics (b) an energy-dependent outer boundary to the inner zone that extends to higher L shells at lower energies and (c) an “S-shaped” energy-dependent inner boundary to the outer zone that results from the competition between diffusive radial transport and losses. We find that the characteristic energy-dependent structure of the radiation belts and slot region is dynamic and can be formed gradually in ~15 days, although the “S shape” can also be reproduced by assuming equilibrium conditions. The highest-energy electrons (E > 300 keV) of the inner region of the outer belt (L ~ 4–5) also constantly decay, demonstrating that hiss wave scattering affects the outer belt during times of extended plasmasphere. Through these simulations, we explain the full structure in energy and L shell of the belts and the slot formation by hiss scattering during storm recovery. We show the power and complexity of looking dynamically at the effects over all energies and L shells and the need for using data-driven and event-specific conditions.
Smarter Grid Solutions used the National Renewable Energy Laboratory’s (NREL’s) simulation capabilities at the Energy Systems Integration Facility to expand its Active Network Management technology for smart campus power control.
The GEANT4 toolkit is widely used for simulation of high energy physics (HEP) experiments, in particular, those at the Large Hadron Collider (LHC). The requirements of robustness, stability and quality of simulation for the LHC are demanding. This requires an accurate description of hadronic interactions for a wide range of targets over a large energy range, from stopped particle reactions to low energy nuclear interactions to interactions at the TeV energy scale. This is achieved within the Geant4 toolkit by combining a number of models, each of which are valid within a certain energy domain. Comparison of these models to thin target data over a large energy range indicates the strengths and weaknesses of the model descriptions and the energy range over which each model is valid. Software has been developed to handle the large number of validation tests required to provide the feedback needed to improve the models. An automated process for carrying out the validation and storing/displaying the results is being developed and will be discussed.
The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wind turbine. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen . While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the simulated wind energy profiles, NLR used OpenFAST to simulate a 3.4-MW International Energy Agency (IEA) reference wind turbine. The hour-long wind energy profiles varied over wind turbulence intensity (Class A or Class C) and average wind speed (5, 7, or 9 m/s). To match the power limits of the 1.25-MW electrolyzer and 3.4-MW IEA wind turbine most effectively and to maximize the efficiency of hydrogen production at a given average wind speed, the profiles were sometimes scaled by two times. This means that, in some cases, the experimental setup assumed two 1.25-MW electrolyzers were coupled with the wind turbine, representing a total maximum electrolysis load of 2.5 MW. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}-{average wind speed}-{turbulence class}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “windIEA3.4-5ms-C_2-400.zip” represents the hour-long experiment using the IEA 3.4-MW turbine, subjected to an average wind speed of 5 m/s and Class C wind turbulence, and connected to two 1.25-MW electrolyzers with the power supply set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wind turbine power. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis .
Using molecular dynamics simulations, we determined the threshold energy for creating defects as a function of the incident angle for all carbon and oxygen atoms in the cellulose monomer. Our analysis shows that the damage threshold energy is strongly dependent on the initial recoil direction and on average slightly higher for oxygen atoms than for carbon atoms in cellulose chain. We also performed cumulative bombardment simulations mimicking low-energy electron irradiation (such as TEM imaging) on cellulose. Analyzing the results, we found that formation of free molecules and broken glucose rings were the most common forms of damage, whereas cross-linking and chain scission were less common. Pre-existing damage was found to increase the probability of cross-linking.
A Monte Carlo program was developed to simulate a high energy gamma-ray telescope using a coded aperture mask (CAMTRAC). The ultimate purpose of the calculation will be to determine the optimum design parameters for such an instrument. The model can also used to ascertain under what conditions CAMTRAC performance is superior to that of conventional telescopes which employ electron-positron pair direction as the sole means of determining gamma ray direction.
The Nuclear Energy Advanced Modeling and Simulation program (NEAMS) from the Department of Energy s Office of Nuclear Energy has funded the development of a modeling and simulation workflow environment to support the various codes in its nuclear energy scientific computing toolkit. This NEAMS Integrated Computational Environment (NiCE) provides extensible tools and services that enable efficient code execution, input generation, pre-processing visualizations, and post-simulation data analysis and visualization for a large portion of the NEAMS Toolkit. A strong focus for the NiCE development team throughout FY 2015 has been support for the Multiphysics Object Oriented Simulation Environment (MOOSE) and the NEAMS nuclear fuel performance modeling application built on that environment, BISON. There is a strong desire in the program to enable and facilitate the use of BISON throughout nuclear energy research and industry. A primary result of this desire is the need for strong support for BISON in NiCE. This report will detail improvements to NiCE support for BISON. We will present a new and improved interface for interacting with BISON simulations in a variety of ways: (1) improved input model generation, (2) embedded mesh and solution data visualizations, and (3) local and remote BISON simulation launch. We will also show how NiCE has been extended to provide support for BISON code development.
Proton radiation therapy can deliver high radiation doses to tumors while sparing normal tissue. However, protons yield secondary neutron and gamma radiation that is difficult to detect, small in comparison to the prescribed dose, and not accounted for in most treatment planning systems. The risk for secondary malignancies after proton therapy may be dependent on the quality of this dose. Consequently, there is interest in characterizing the secondary radiation. Previously, we used the dual ionization chamber method to measure the separate absorbed dose from gamma-rays and neutrons secondary to the proton beam1, relying on characterization of ionization chamber response in the unknown neutron spectrum from Monte Carlo simulation. We developed a procedure to use Shieldwerx activation foils, with neutron activation energies ranging from 0.025 eV to 13.5 MeV, to measure the neutron energy spectrum from double scattering (DS) and pencil beam scanning (PBS) protons outside of the treatment volume in a water tank. The activated foils are transferred to a NaI well chamber for gamma-ray spectroscopy and activity measurement. Since PBS treats in layers, the switching time between layers is used to correct for the decay of the activated foils and the relative dose per layer is assumed to be proportional to the neutron fluence per layer. MATLAB code was developed to incorporate the layer delivery and switching time into a calculation of foil activity, which is then used to determine the neutron energy fluence from tabulated foil activation energy thresholds.1. Diffenderfer et. al., Med. Phys., 38(11) 2011.
According to the EIA, simple commercial buildings account for 97% of total commercial building stock. However, most simple commercial buildings for example small- to mid-sized offices, retail, schools and warehouses do not benefit from the data-driven decision-making capabilities of whole-building energy modeling. The high cost of custom modeling limits the use of energy modeling of simple buildings for new construction or retrofit measures. Lack of tools providing helpful information on interactive savings estimates creates difficulties in meeting aggressive decarbonization and energy efficiency goals for simple building designers and utility program managers. This paper reviews a beta phase Simple Building Calculator with the ability to generate relatively accurate and interactive modeling results based on a limited but robust set of inputs. It can evaluate whole-building or single measure savings in new or existing buildings, compare measure package choices, or provide simplified performance modeling for energy codes and utility incentives. The tool combines physical (annual whole building prototype simulation) and statistical modeling techniques to predict annual energy performance. It supports a variety of building characteristics for envelope, HVAC, and lighting with parameters ranging from vintage to max tech configurations, as well as support for single-zone and simple multi-zone HVAC systems. The Simple Building Calculator was designed to provide immediate feedback for otherwise computationally intensive tasks like measure comparison, development of multiple measure package combinations, or verification that measures meet efficiency targets—all with the goal of providing a tool for quick annual energy simulation of simple commercial buildings.
This project was only active for two months and was terminated due to a re-organization of the sponsoring initiative. The original purpose of the project was to develop and apply verification and validation (V&V) methodologies for the Energy System Co-Design with Multiple Objectives and Power Electronics (E-COMP) Initiative. This report summarizes the project and the work that was completed in the shortened time frame.
We investigate thermal properties of a 𝑈(1) lattice gauge theory in 1 + 1 dimensions through real-time simulations. We extract the spectral functions directly coupling to the pseudoscalar and scalar mesons, demonstrating the thermal modifications of these states with increasing temperatures. Introducing the notion of energy-flow operators, we quantify the temporal buildup of correlations in the energy flows across the lattice. We demonstrate that energy-energy correlators fail to factorize to products of energy flows, both in the vacuum and at nonzero temperature, indicating the presence of nontrivial correlations in the quantum states. Our results constitute a first real-time ab initio study of bound-state thermal broadening and finite temperature energy-flow correlations in a gauge theory, providing a benchmark for future studies of hadronic matter under extreme conditions.