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The Higgs boson is a fundamental particle in the Standard Model of particle physics, theorized in the 1960s and later discovered in 2012 at the Large Hadron Collider (LHC). It plays a pivotal role in the mechanism of mass generation for other particles. This poster focuses on the application of Machine Learning algorithms to efficiently classify Higgs boson events.
Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.
The Large hadron Collider at CERN and four scientific collaborations: Alice, ATLAS, CMS, LHCb are in operation since September 2008. The accelerator delivered and the experiments processed trillions of events of proton-proton and heavy ions collisions and provided useful data for thousands of physics analyses and publications. The jewel of the published data is a discovery in 2012 of the long anticipated Higgs boson. During the operation time the regular acquisition of data was interleaved with two periods of maintenance, Long-shutdown-1 (2013-2015) and Long-shutdown-2 (2018-2022), which resulted in several improvements to the machine and the experiments. The CMS collaboration recorded to date two large physics datasets of pp collision data. The first dataset, called Run 2, was recorded between 2015 and 2018 with 140fb-1 of integrated luminosity taken at 13TeV of center of mass energy. The second dataset, called Run 3, has just started in 2022 and it has been recording pp collision data at 13.6 TeV of center of mass energy, with 80 fb-1 of data collected till the end of July 2023.For my presentation I selected the most recent results produced by CMS from Run2 and Run 3 which are covering the topics of Higgs boson properties, searches for new particles and additional scalars, top quark production and properties, and I am discussing other interesting models e.g. using SM particles as portals to the Dark matter.
Thallium radiochemistry was developed as a routine analytical capability at Los Alamos, dating from some of its earliest history after WWII. The first post-war compilation of radiochemical procedures published by the Radiochemistry Group J-11 is dated February 1953 as Los Alamos report LA-1566. The thallium radiochemistry procedure was authored by René J. Prestwood, and the details of the method as documented in 1953 are nearly identical to the thallium procedure contained in the most recent Collected Radiochemical and Geochemical Procedures (Fifth Edition) contained in Los Alamos report LA-1721 issued May 1990. René was a talented and well-respected member of the Radiochemistry Group. He first came to the lab in 1943 as an undergraduate student from UC Berkeley to join the Manhattan Project. After the war, René earned his PhD in Nuclear Chemistry with Art Wahl at Washington University in St. Louis. He then returned to Los Alamos as a technical staff member and retired in 1984. René passed away at the age of 92 on December 21, 2012.
In the United States, agricultural production is both a significant source of greenhouse gases (GHGs) (Environmental Protection Agency (EPA), 2022) and uniquely susceptible to climate change impacts (Vermeulen et al., 2012). Decarbonization solutions have been proposed for addressing agricultural GHGs; however, research has been limited in synthesizing qualitative and quantitative analysis of potential GHG mitigation solutions in the United States. In this report, we review U.S. agricultural GHG sources by activity and quantify potential mitigation solutions based on a comprehensive data and literature analysis. We also discuss agricultural carbon sequestration options to offset GHG emissions. In our analysis, we identified two significant and hard-to-abate GHG sources (N 2 O from soil management, and CH 4 from enteric fermentation from livestock) as well as high-impact GHG mitigation solutions (e.g. agroforestry, reforestation, and biochar application) and cross-cutting GHG mitigation solutions (renewable energy production, precision agriculture, no-till, integrated nutrient management, and biochar). This report is meant to provide initial analysis and establish a foundation for future agricultural decarbonization research - it is not an exhaustive analysis of all available studies. However, to our knowledge this report is the most comprehensive assessment of agricultural GHG emissions and associated mitigation opportunities in the United States to date. Future empirical research is recommended to close research gaps in different climates, soils, and agricultural systems. Meta-analyses for all mitigation solutions would increase confidence in the estimated GHG mitigation potentials. To conclude this report, we discuss short-term and long-term pathways for agricultural decarbonization in the United States, the importance of accounting for total GHG fluxes, potential co-benefits of agricultural decarbonization, analysis of study data confidence, and research gaps.
With the increase on population the world will depend on renewable sources to meet the increasingly energy needs. Use of lignocellulosic biomass as a renewable source has been proven efficient for conversion to cellulosic ethanol and capable of contributing to achieve the threshold on energy demand while reducing greenhouse gases in 90% when compared with fossil fuels (Wang et al., 2007, 2012). However, the processing of biomass encounters limitations in feeding and flow within biorefineries due to the system plugging by compaction and slurry high yield stress, preventing transport of biomass materials and in some cases unexpected plant shutdowns that results in high operational costs (dos Santos et al., 2021; Ximenes et al., 2021). Different solutions for biomass handling and slurry formation from densified materials like pellets have been studied. Cellulosic biomass residues are typically processed in pretreatment reactors to which acid or base is added (Humbird et al., 2002). Other pretreatments such as liquid hot water (LHW) and steam explosion that act without the addition of chemicals use pressures above the saturation vapor of water, to disrupt biomass structure (Ruiz et al., 2021). Although these methods are widely known, the use of pretreatments like acid digestion and LHW present challenges like waste disposal and could be energy inefficient (Mosier et al., 2005). Alternatively other approaches like enzymatic liquefaction have been applied for biomass transformation into slurries with promising results and without the use of pretreatments (dos Santos et al., 2021). Nevertheless, enzymatic liquefaction implementation faces difficulties due to the recalcitrant properties of biomass, its variability, and the release of enzyme inhibitors. While it has been proven that chemical composition properties in biomass have effects on enzyme inhibition (Huang et al., 2022; Kim et al., 2011; Zhai et al., 2018), hindering the efficiency of the liquefaction, not ample research has been conducted in understanding the physical properties as particle size, porosity, water adsorption retention and their effect in the ability to form a slurry at high solids concentration (Yan et al., 2020). In order to improve lignocellulosic biomass handling and formation of biomass slurries, enzyme assisted liquefaction for slurry creation from corn stover at solids loadings up to 30% is reported in this work. Two different kinds of biomass (pelleted corn stover and cobs) were liquefied in a fed-batch process using commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU or 3 FPU per gram of dry solids in 10 mM sodium citrate buffer solution (pH 4.8). Pellets were fed into a 1 L stirred bioreactor according to a predefined fed-batch protocol over the first 5 hours until reaching 30% of solids loading. After 6, 24 and 96 hours, samples were taken and characterized with respect to their sugar composition, rheology and water absorption. Successful slurry creation with dramatically reduced yield stress was achieved for corn stover for both assessed enzymes. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3 FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme. Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours. Yield stress decreased when residence time increased with an enhanced fluidity noted for higher enzyme concentrations. A profile for 6, 24 and 96h of yield stress measurements is presented.
Terephthalic acid (TA) is a high volume and high market commodity chemical which is a monomer used in making polyethylene terephthalate (known as PET) for beverage bottles and packaging films. The global demand for TA in 2012 was 47 million ton and it is expected to grow at a 6 percent rate to reach around 65 million ton in 2018. TA is currently made from petroleum derived p-xylene produced as a co-product during ethylene production in the naphtha cracking process. At present, ethylene is mostly made by ethane cracking of cheap natural gas-shale gas, making naphtha cracking to produce p-xylene uneconomical. Combined with potential unavailability of the petroleum based p-xylene to meet market demand and the end user’s interest in sustainable PET products has created significant attention towards biomass based feed sources for the TA production. The goal of the proposed work is to develop a catalytic process from a biomass-sourced feedstock to a chemical intermediate that can serve as the basis for the economical and renewable TA production that meets market needs.
Stackless traversal is a technique to speed up range queries by avoiding usage of a stack during the tree traversal. One way to achieve that is to transform a given binary tree to store a left child and a skip-connection (also called an escape index). In general, this operation requires an additional tree traversal during the tree construction. For some tree structures, however, it is possible to achieve the same result at a reduced cost. We propose one such algorithm for a GPU hierarchy construction algorithm proposed by Karras in Karras 2012. Furthermore, we show that our algorithm also works with the improved algorithm proposed by Apetrei in Apetrei 2014, despite a different ordering of the internal nodes. We achieve that by modifying Apetrei’s algorithm to restore the original Karras’ ordering of the internal nodes. Using the modified algorithm, we show how to construct a hierarchy suitable for a stackless traversal in a single bottom-up pass.
Generic Technical Factors Affecting Fuel Fabrication. Many in-reactor physical, chemical, metallurgical, mechanical, thermodynamic, and nucleonic factors influence the design and functionality of nuclear fuel. Detailed discussion of these technical factors is beyond the scope of this cost-oriented preface document; however, the following three references are suggested for a more comprehensive discussion of fuel design requirements for both commercial and special use (military and remote location) reactors: IAEA-TECDOC-1686 (IAEA 2012), the World Nuclear Association webpage “Nuclear Fuel and its Fabrication (WNA 2020a), and INL/EXT-20-54641 (Mariani 2020). To aid the reader’s understanding of how design affects life cycle costs, a few technical factors are also briefly discussed in the sections below.
RHIC Run 23 used Gold beam from Tandem with an AGS extraction energy of 9.8 GeV. The same basic setup, 8 single bunch transfers from the Booster and a 12-6 merge in the AGS to provide 4 bunches at extraction, had been used before to deliver Tandem Au to RHIC. But in those cases, it was used for low energy runs (3.85 GeV in 2021 and 5.75 GeV in 2020) where extraction was below transition energy (7.9 GeV). Tandem beam was used for this run because the intensity and stability of EBIS Au did not meet the requirements for RHIC. Physics was first declared in RHIC on May 22 nd and on August 1 st the run was cut short by about 2 months due to a major failure in RHIC. Prior to the advent of EBIS as the preinjector in 2012, 9.8 GeV Tandem Au was regularly delivered to RHIC but the setup in the Booster and AGS was quite different: Four Booster transfers of 6 bunches each were merged into 4 bunches using a 24-12-4 merge scheme. The supercycle length was 6.0 sec before June 29 th when it was extended to 6.6 sec to accommodate EBIS commissioning. The Tandem, Booster, and AGS were on user 1 for the 9.8 GeV setup. Some work with EBIS Au 32+ took place on EBIS, Booster, and AGS user 5 using the standard 9.8 GeV injector setup with a 4 to 1 merge in Booster and a 6-3-1 type merge in AGS. The Siemens motor generator was used for the entire run. An intensity limit of 8.0e9 Au 77+ ions in the AGS was in effect during the run to protect the J7 plunging stripping foil and the Copper absorber of the AGS beam dump. This corresponds to a merged bunch intensity limit of 2.0e9 Au 77+ ions for 4 equal intensity bunches. The per bunch intensity limit can be increased to 2.67e9 by reducing the number of BtA transfers from 8 to 6. There was also a Booster Late intensity limit of 16e9 Au ions in effect to protect the BtA stripping foil from damage due to overheating. Lowering the number of transfers also makes this limit less of a constraint. BtA foil 5, which was installed in 2020 and had not been used regularly prior to this run was used all run and showed no obvious signs of deterioration. In May, a Tandem Au 3.85 GeV setup from 2021 was also re-established on AGS user 2. It was used for APEX on May 24 and July 26. Initial work with 3.85 GeV beam was on May 19. Proton beam was also set up during the run and extracted to W dump on July 10. It was used for APEX on July 12. Although the OPPIS source was used the AGS setup was without snakes.
The Lighting Market Characterization report details how many lighting products (lamps and luminaires) were installed in the U.S. as of 2020, where they were installed, and how much energy they consumed. It also highlights key changes in U.S. lighting market characteristics between 2015 and 2020. This is the fourth edition of the LMC report; previous versions were released in 2002, 2012 and 2017. By publishing summary estimates of installed stock and energy use of various general illumination lighting products, these reports help DOE and others plan effective lighting research and development programs based on changing needs.
The Lighting Market Characterization report details how many lighting products (lamps and luminaires) were installed in the U.S. as of 2020, where they were installed, and how much energy they consumed. It also highlights key changes in U.S. lighting market characteristics between 2015 and 2020. This is the fourth edition of the LMC report; previous versions were released in 2002, 2012 and 2017. By publishing summary estimates of installed stock and energy use of various general illumination lighting products, these reports help DOE and others plan effective lighting research and development programs based on changing needs.
The Lighting Market Characterization report details how many lighting products (lamps and luminaires) were installed in the U.S. as of 2020, where they were installed, and how much energy they consumed. It also highlights key changes in U.S. lighting market characteristics between 2015 and 2020. This is the fourth edition of the LMC report; previous versions were released in 2002, 2012 and 2017. By publishing summary estimates of installed stock and energy use of various general illumination lighting products, these reports help DOE and others plan effective lighting research and development programs based on changing needs.
HTTP Strict Transport Security (HSTS) is a standard that ensures website visitor’s traffic is always sent using HTTPS ensuring that all traffic is protected during transit. This initiative was adopted in 2012 by the IETF and has grown in popularity all around the world. Because the traffic is encrypted with TLS/SSL, it can be used by attackers to bypass various cybersecurity capabilities such as a site firewall. To address this lack of visibility into encrypted traffic in motion, the CST at Fermilab acquired the Cloudflare Web Application Firewall (WAF). To help in the implementation and integration of the Cloudflare WAF, I was directed to learn about and aid in this process. This has been a profound learning experience into the on-goings of project management, web application firewalls, collaboration, and networking.
This presentation characterizes spatial trends in radium (Ra) concentrations, sources, and potential impacts generated from Marcellus Shale produced waters. Here, we combine previously published produced water data with additional Ra activity measurements extracted from residual waste reports submitted to the Pennsylvania Department of Environmental Protection from 2012-2023. This is the largest, spatially referenced compilation of Ra activity measurements from produced water sourced from the Marcellus Shale to date. The median Marcellus Shale produced water Ra activity presented here is 6,906 pCi/L (interquartile range = 12,515 pCi/L). Radium activities in the positively skewed dataset can exceed 30,000 pCi/L in some parts of the state. The regional trends in Ra concentrations and isotopic ratios will be characterized and potential environmental and health implications discussed.
Historical unplanned releases at the UPR-100-N-17 166-N Diesel Oil Supply Line Leak waste site located within the 100-NR-1 OU resulted in diesel fuel contamination of the unsaturated vadose zone and site groundwater. Enhanced in situ bioremediation of the deep vadose zone was the final remedy decision for the 100-NR-1 Operable Unit (OU) and the full-scale bioventing demo began in 2012. For this remedy, oxygen is actively supplied to the deep vadose zone to stimulate aerobic hydrocarbon degrading microorganisms to metabolize petroleum contamination. Degradation rate calculations based on vadose zone respirometry measurements, however, have indicated declining activity over recent years, though the precise reason for this apparent decline has not been determined. In this investigation 100-NR-1 OU sediment cores were analyzed for total microbial biomass, as well as enumeration of diesel and BTEX degrading bacteria to determine if these microbial populations have declined relative to previous measurements taken in 2009.
The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.
We present a preliminary version of the East Asia Tomography (EAT) model, an adjoint waveform tomography model of East and Southeast Asia. We used SPiRaL (Simmons et al., 2021) as our starting model and source parameters for 238 earthquakes from the Global Centroid Moment Tensor catalogue (Ekström et al., 2012). After 50 iterations on Lawrence Livermore National Laboratory’s Lassen supercomputer, we converge on a model with a minimum period of 50 seconds. The preliminary model shows improved slab structure compared to SPiRaL and shows significantly reduced misfit. In later versions of the model, we aim to harness techniques proposed in other studies to improve waveform predictions that travel through the ocean (e.g., Wehner et al., 2022) and use relative amplitude-based misfit functions (e.g., Tao et al., 2018) to better constrain Earth structure. We hope to iterate the current extent of the model to 25 seconds minimum period before iterating to shorter periods for a smaller subregion of the full model.