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Contains the initial configurations and output results for the simulations reported in the paper Chemical and Morphological Structure of Transgenic Switchgrass Organosolv Lignin Extracted by Ethanol, Tetrahydrofuran, and γ-Valerolactone Pretreatments
Here we have developed a rigorous scattering matrix theory of light emission from periodically structured media using a Green’s function approach. We computationally simulate the spectral power inside the structure, incorporating Purcell factor enhancements, and find internal waveguiding modes and plasmonic losses. We simulate the light-outcoupling factor η out and describe how corrugations and structured media can enhance η out . We have extended our framework to describe non-periodic disordered arrays as well as aperiodic quasi-crystalline arrays. Flat organic light-emitting diodes (OLEDs) have low outcoupling with η out ~20% since most of the light is trapped in waveguided modes in higher index layers or lost to plasmonic excitations at the metal cathode. Periodically corrugated OLEDs can achieve highly enhanced η out ~65%-70% for pitch values between 1000 and 2000 nm, representing an enhancement factor >3 over planar structures. Periodic corrugations strongly diffract trapped waveguided and plasmonic modes to the emissive air cone. Disordered templates also can cause significant enhanced outcoupling with η out ~50%-55% for smaller nearest-neighbor separations of 300–400 nm. Quasi-crystalline tilings can also lead to enhancements of η out ~50%-55%. This framework can be utilized to design novel structured media that can generate high light extraction.
The presence of Laue oscillations in a film grown on a solid surface is broadly taken as indicating a high quality, crystallographically aligned film of the targeted compound. In this paper we briefly review the origins of both Laue oscillations and Kiessig fringes and show how they can be used together to determine if extra thickness exists above or below the coherently diffracting domains. The differences between experimental and “ideal” films are discussed and the effect of structural features (roughness, different thickness coherently diffracting domains and thickness in addition to the coherently diffracting domains) are illustrated with experimental and simulated data for metal and mixed-metal chalcogenide films of titanium, bismuth, vanadium/iron, and bismuth/molybdenum. Examples are given showing how quantitative information can be extracted from experimental diffraction patterns.
Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM).Two sets of sample data are provided for 2,555,152 buildings located within the boundary of Arizona in the United States:Data (846.3MB *.csv) - minimalist list of each building (rows) for the following fields (columns) • ID - unique building ID • Centroid - building center location in latitude/longitude (from Footprint2D) • Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) • State_abbr - state name • Area - estimate of total conditioned floor area (ft2) • Area2D - footprint area (ft2) • Height - building height (ft) • NumFloors - number of floors (above-grade) • WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) • CZ - ASHRAE Climate Zone designation • BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards • Standard - building vintage • Sample Models (114GB*.zip by county) - OpenStudio and EnergyPlus building energy models named according to IDThis data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).
With conventional sources of uranium forecasted to be depleted within a century, developing methods to cost-effectively harvest uranium from seawater, which is estimated to contain 1000 times more uranium than on land, are crucial to the continued viability of nuclear power generation. Studies have shown that coupling a uranium harvester system with an existing offshore structure, such as a floating wind turbine (FWT), could greatly reduce the cost of harvesting uranium from seawater as it eliminates the need for dedicated moorings and increases the overall energy-gathering ability of the offshore wind farm. This study explores the hydrodynamic effects of adding a uranium harvester to an offshore floating wind turbine. The experimentally determined hydrodynamic responses of two designs of a Symbiotic Machine for Ocean uRanium Extraction (SMORE) are compared with that of an unmodified FWT. Both SMORE designs utilize adsorbent filament that is enclosed in a hard permeable shell to decouple the mechanical and chemical requirements of the device. In this work, it was found that both SMORE designs do not significantly shift the resonant peaks of the FWT.
The proposed Jefferson Lab Electron Ion Collider (JLE-IC) envisions an ion complex composed of an ion linac, two booster synchrotrons and a collider ring. The evolv-ing design of the JLEIC booster required an increase in the extraction energy of the booster from 8 to 12.1 GeV kinetic energy, necessitating two machines instead of one. The decision was also made to switch to warm magnets, thus increasing the total radius of the 8 GeV booster. With the second booster being the same size as the collider rings. In this work we present the new designs for JLE-IC?s Low Energy Booster (LEB) and High Energy Boost-er (HEB).
Nonlinear integrable optics are a promising alternative approach to lattice design. The integrable optics test accelerator (IOTA) at Fermilab has been constructed for dedicated studies of magnetostatic elliptical elements as described by Danilov and Nagaitsev. The most compelling verification of correct implementation of the NIO lattice is direct observation of the analytically expected invariants. This report outlines the experimental and analytical methods for extracting the nonlinear invariants of motion from data gathered in the last IOTA run.
We present progress on the development of a machine learning (ML) regulation system for third-order resonant extraction of the beam delivered to the Mu2e experiment at Fermilab. We consider classical and ML-based controllers optimized on semi-analytic simulations and provide performance comparisons for several models. Additionally, we discuss the efficiency of each model in training, which has implications for future work on adaptive control. We also discuss progress on developing optimized implementations of ML models for edge-based inference.
We present a new global QCD analysis of unpolarized parton distribution functions (PDFs) and nuclear effects including for the first time data from the SeaQuest and Marathon experiments in addition to high-energy weak-boson-production data from the Tevatron and Large Hadron Collider. Simultaneously extracting the PDFs and nuclear effects, we examine the impact of the SeaQuest and Marathon data on the light-quark sea asymmetry and the EMC ratios of deuterium, helium, and tritium.
Southern Research Institute (Southern) teamed with partners Novus Energy Technologies (Novus), Carus Corporation (Carus), and Applied Membrane Technology, Inc. (AMT) to develop an innovative Geothermal ThermoElectric Generation (G-TEG) system specially designed to both generate electricity and extract high-value lithium (Li) from low-temperature geothermal brines. The process combined five modular technologies including – silica removal, nanofiltration (NF), membrane distillation (MD), Mn-oxide sorbent for Li recovery, and TEG. This project provides a proof of concept for each of these technologies. The first step in the process is silica precipitation through metal addition and pH adjustment to prevent downstream scaling in membrane processes. Next, the geothermal brine is concentrated with the first of a two stage MD system. The first stage MD system is made of a high-temperature material to withstand geothermal brine temperatures up to 150C.° The first stage MD is integrated with a G-TEG module for simultaneous energy generation. The release of energy from the MD permeate drives heat transfer across the TE module, producing electricity. The first stage MD concentrate is then treated utilizing an NF system to remove Ca 2+ and Mg 2+ . The NF concentrate will be disposed in the well by reinjection. The NF permeate undergoes concentration in a second stage of MD (polymeric material) to further concentrate Li in the NF permeate and enhance the efficiency of the downstream Li recovery process utilizing a Mn-oxide sorbent. Permeate from both the stages of the MD can be beneficially utilized as the permeates will contain less contaminants than the feed water. The concentrated geothermal brines are then contacted with the Mn-oxide sorbent. After Li from the geothermal brine is adsorbed on the sorbent, HCl is then utilized to regenerate the sorbent and recover the Li. The research and development project showed that the Si removal goal (>80%) could be achieved by increasing the pH of the brine and adding Fe 3+ under several scenarios. The NF was also successful in achieving significant Ca 2+ and Mg 2+ removal (~80%) while retaining most Li in the permeate for high strength brines. MD experiments showed that geothermal brines could be significantly concentrated with little fouling due to pre-treatment.
Geologic material properties are necessary parameters for ground motion modeling and are difficult and expensive to obtain via traditional methods. Alternative methods to estimate soil properties require a measurement of the ground's response to a force. A possible method of obtaining these measurements is active-source seismic surveys, but measurements of the ground response at the source must also be available. The potential of seismic sources to obtain soil properties is limited, however, by the repeatability of the source. Explosives, and hammer surveys are not repeatable because of variable ground coupling or swing strength. On the other hand, the Seismic Hammer TM (SH) is consistent in the amount of energy it inputs into the ground. In addition, it leaves large physical depressions as a result of ground compaction. The volume of ground compaction varies by location. Here, we hypothesize that physical depressions left in the earth by the SH correlate to energy recorded by nearby geophones, and therefore are a measurement of soil physical properties. Using measurements of the volume of shot holes, we compare the spatial distribution of the volume of ground compacted between the different shot locations. We then examine energy recorded by the nearest 50 geophones and compare the change in amplitude across hits at the same location. Finally, we use the percent difference between the energy recorded by the first and later hits at a location to test for a correlation to the volume of the shot depressions. We find that: * Ground compaction at the shot-depression does cluster geographically, but does not correlate to known surface features. * Energy recorded by nearby geophones reflects ground refusal after several hits. * There is no correlation to shot volume and changes in energy at particular shot locations. Deeper material properties (i.e. below the depth of surface compaction) may be contributing to the changes in energy propagation. * Without further processing of the data, shot-depression volumes are insufficient to understanding ground response to the SH. Without an accurate understanding of the ground response, we cannot extract material properties in conjunction with the SH survey. Additional processing including picking direct arrivals and static corrections may yield positive results.
In this project, RadiaBeam Technologies was tasked with developing a novel solution for a cost effective quench protection based on fast expansion of the normal zone. By inductively coupling a strong electromagnetic pulse via a resonant LC circuit, we attempted to demonstrate accelerated normal zone propagation. The AC field induces currents in the superconducting layer with the current density exceeding that of the critical current density, J c . This creates a large normal zone, uniformly distributing the dissipation through the magnet body. The method does not rely on thermal heating of the conductor, thus enabling nearly instantaneous protection. Through the course of the Phase II project, RadiaBeam Technologies continued extensive numerical modeling of the inductive quench system, re-designed and built several iterations of the POC system for testing and observed evidence of a transient partial quench being induced. However the final device was not fabricated. This was a consequence of the fundamentally complex nature of the energy extraction process and the challenges associated even with demonstrating the proof of concept in a bench top device.
These are slides about extracting the data from the LCM vk4 formatted output file. The following is covered: vk4 file produced by Keyence VK Software, custom analysis, no off the shelf way to read the file, reading the binary data in a vk4 file, various offsets in decimal lines, finding the height image data, directly in MATLAB, binary output beginning of height image data, color image information, color image binary data, color image decimal and binary data, MATLAB code to read vk4 file (choose a file, read the file, compute offsets, read optical image, laser optical image, read and compute laser intensity image, read height image, timing, display height image, display laser intensity image, display RGB laser optical images, display RGB optical images, display beginning data and save images to workspace, gamma correction subroutine), reading intensity form the vk4 file, linear in the low range, linear in the high range, gamma correction for vk4 files, computing the gamma intensity correction, observations.
The Muon g-2 experiment at Fermi National Accelerator Laboratory aims to measure the anomalous magnetic moment a of the muon to an unprecedented precision of 0.14 ppm, obtaining a near four-fold increase in precision over the previous experiment at Brookhaven National Laboratory (BNL). The value of a from BNL diers from the Standard Model prediction by 3.4 standard deviations, suggesting a tantalizing hint of new physics and so motivating a new measurement. The Fermilab experiment follows the measurement principle from the BNL experiment. A beam of positive muons is stored in the ring, where a combination of magnetic and electric elds helps to focus the beam. The combination of these elds and the stored beam properties directly impact the nal extraction of of a. The muon anomaly relies on the measurement of the spin precession frequency !a about the momentum of the muon. Due to a muon beam momentum spread of approximately 0:1%, !a must be corrected for the eect of a radial electric eld. The correction is estimated by means of a modied Fourier analysis of the so-called fast rotation signal. We explore the application of this analysis to the case of a beam with longitudinal spread and to the case of late-time beam detection. We also consider the numerical extension of the method, and apply it to data from the recent commissioning run.
This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This analysis has 30 distinct scenarios. The scenarios include 14 onshore production basins with their respective extraction technologies, for a total of 27 onshore scenarios. The scenarios also include two offshore production scenarios, Gulf of Mexico (GoM) and offshore Alaska, and an associated gas scenario. The results include a national average based on a production-weighted aggregation of the onshore, offshore, and associated gas scenarios. The life cycle GHG emissions from the United States (U.S.) natural gas supply chain are 19.9 g carbon dioxide equivalents (CO2e)/MJ (with a 95% mean confidence interval of 13.1 to 28.7 g CO2e/MJ). The top contributors to carbon dioxide (CO2) and methane (CH4) emissions are combustion exhaust and other venting from compressor systems. Compressor systems are prevalent in most supply chain stages, so compressor emissions are key emission drivers for life cycle emissions. Emission rates are highly variable across the entire supply chain. The national average CH4 emission rate is 1.24%, with a 95% confidence interval ranging from 0.84% to 1.76%.
The goal of the present project was to develop an advanced, low-cost manufacturing technique for fabrication of boride-based ultrahigh-temperature ceramics (UHTCs) that possess all the required properties to function as sustainable electrodes in magnetohydrodynamic (MHD) direct power extraction applications. Specifically, the project investigated use of mechanical activation-assisted self-propagating high-temperature synthesis (MASHS) followed by pressureless sintering for the fabrication of ceramic materials based on ZrB 2 and HfB 2 from inexpensive raw materials ZrO 2 , HfO 2 , and B 2 O 3 , with Mg as a reactant and NaCl or MgO as an inert diluent.
With the dawn of the exascale era, computer scientists and engineers are faced with tremendous challenges across all facets of the HPC system - scalability, performance, reliability, and power consumption. In particular, the power-performance benefit from one processor generation to the next is seeing ever-diminishing returns and will require fundamental changes in the way we approach computation. In fact, it is likely that different applications will require different types of accelerators in order to meet power, performance, and reliability requirements at scale. One potential type of accelerator, a dataflow architecture, diverges from the traditional sequentially executed instruction model into one that reflects the inherent instruction-level parallelism in a program. This work presents the initial steps toward a tool that can extract the control-dataflow graph from an application.
This report summarizes the results of an LDRD focused on developing and demonstrating statistically rigorous methods for analyzing and comparing complex activities from remote sensing data. Identifying activity from remote sensing data, particularly those that play out over time and span multiple locations, often requires extensive manual effort because of the variety of features that describe the activity and the required domain expertise. Our results suggest that there are some hidden challenges in extracting and representing activities in sensor data. In particular, we found that the variability in the underlying behaviors can be difficult to overcome statistically, and the report identifies several examples of the issue. We discuss key lessons learned in the context of the project, and finally conclude with recommendations on next steps and future work.