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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

File format for normalizing radiological concentration exposure rate and dose rate data for the effects of radioactive decay and weathering processes

This report specifies the electronic file format that was agreed upon to be used as the file format for normalized radiological data produced by the software tool developed under this TI project. The NA-84 Technology Integration (TI) Program project (SNL17-CM-635, Normalizing Radiological Data for Analysis and Integration into Models) investigators held a teleconference on December 7, 2017 to discuss the tasks to be completed under the TI program project. During this teleconference, the TI project investigators determined that the comma-separated values (CSV) file format is the most suitable file format for the normalized radiological data that will be outputted from the normalizing tool developed under this TI project. The CSV file format was selected because it provides the requisite flexibility to manage different types of radiological data (i.e., activity concentration, exposure rate, dose rate) from other sources [e.g., Radiological Assessment and Monitoring System (RAMS), Aerial Measuring System (AMS), Monitoring and Sampling). The CSV file format also is suitable for the file format of the normalized radiological data because this normalized data can then be ingested by other software [e.g., RAMS, Visual Sampling Plan (VSP)] used by the NA-84’s Consequence Management Program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Open Source Platform for Live Processing of High Data Rate Electron Microscopy (SBIR Phase I Award Topic 15, Subtopic B, Final Scientific / Technical Report)

4D scanning transmission electron microscopy (STEM) is experiencing a revolution both in terms of data size, and data veracity, as are many other areas of experimental data acquisition. This presents enormous opportunities to make new scientific discoveries, but is also hamstrung by aging software that is no longer fit for purpose. Experimental data acquisition platforms must make the same investments in software infrastructure that the simulation community made decades ago to take advantage of high-performance computing (HPC) if they hope to realize the full potential of the latest advances made in detector technology. This requires rethinking the design and deployment of hardware, moving away from small, fixed commodity computing capabilities with closed interfaces to open, modular, scalable systems designed for parallelism and throughput. The technical approach will leverage best-in-class open source technologies, and develop new approaches strategically to build an open source platform for experimental data acquisition targeting high data rate electron microscopy. The project will develop a software platform that uses the power and performance of modern HPC resources to ingest the large volume of data produced by electron microscopes using direct electron detectors. A set of configurable pipelines will be used to enable the processing to be tailored to the problem being investigated with builtin visualization of data at interactive rates. This project will leverage investments made by the DOE and other agencies to provide a powerful software platform for the experimental data community working with most powerful electron microscopes, such as 4D STEM detectors. It will create a platform that serves as a reference for the community. Permissive open source licensing will make the platform available to all, with a simple deployment strategy offering the ability to keep data close to where it is generated. This advanced software platform will require customization for each deployment, creating opportunities for software services that are typically offered to extend open source software platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

HunStat2 – a simple and low-cost potentiostat with electrochemical impedance spectroscopy capability

We have developed a low-cost (30 USD), simple do-it-yourself (DIY) potentiostat with cyclic voltammetry (CV), open circuit potential (OCP) and electrochemical impedance spectroscopy (EIS) capability. The HunStat2 potentiostat is based on Analog Devices' AD5941 Analog Front End chip, which significantly simplifies the construction of potentiostats for both direct and alternating current (DC and AC, respectively) techniques. Interested readers are provided with circuit diagrams and a bill of materials to build the potentiostat on their own. In addition, control software is also provided free of charge. The software enables acquisition and visualization of data. In summary, HunStat2 introduces a simple and low-cost DIY potentiostat recommended for both analytical and educational purposes.

Vamos, Istvan [Lajos Petrik Vocational Chemistry S↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2013

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Improvements to the operational efficiency of the Portsmouth 'Blue Box' Assay system - 15162

The 'Blue Box' in Building 326 at Portsmouth comprises a dual cargo container lined with high density polyethylene with 5% (elemental) boron that acts as a neutron shield. This construction provides a low environmental neutron background to support the capability to attain low values of minimal detectable activity (MDA). A Non-destructive Assay (NDA) measurement platform known as the Fluor B and W Portsmouth Slab Counter (FBPSC) is housed inside the Blue Box. This comprises four neutron slab detectors supported with an electronic system supplying power and associated signal processing. The system is operated by a laptop computer which has data acquisition and analysis capabilities. Each slab contains five {sup 3}He proportional counters embedded in polyethylene. The system is designed to measure the mass of U-235 in coolers from the Portsmouth site using passive neutron counting. The system was calibrated by taking measurements with {sup 252}Cf sources attached to various positions on the outside surfaces of a surrogate cooler. In addition, Monte-Carlo N-Particle (MCNP) simulations were performed to extend the baseline calibration for coolers of various sizes used in the gaseous-diffusion process. The basic principle of operation is to measure the total neutron emission from the item and determine the mass of {sup 235}U using the system efficiency (determined from MCNP calculations combined with the calibration measurements) combined with known isotopic information ({sup 235}U enrichment and U-235/U-234 ratio), assumed chemical composition, and gross cooler mass. The FBPSC analysis program calculates the mass of U-235 within the cooler being assayed, together with the associated Total Measurement Uncertainty (TMU). A background correction is performed that accounts for the measured environmental background with a cosmic-ray spallation correction (based on the cooler's gross weight). The software suite developed for the system also includes the capability to track and trend measurement control data in order to quickly identify conditions where the system has drifted outside of its quality control envelope. The MDA of the system has been determined to be less the 15 g of U-235 for count times that are typically less than 5 minutes (depending on the uranium isotopics). This is primarily the result of the low neutron background rate inside the Blue Box (approximately 3 times lower than at nearby locations outside the box). Additionally, various software features have been designed to yield optimum counting performance for the system including count time adjustment and interval filtering to reject statistical outliers that are usually associated with cosmic spallation events. The operation of the system has proven to be very efficient, with the short measurement time providing a high throughput rate of coolers through the Blue Box NDA system. Significant operational benefits and improved data traceability have been yielded compared to the previous measurement process, which involved operators taking measurement with counter/scalers and manually entering data into spreadsheets. As of August 2014, this system successfully measured all coolers required to support completion of a contractually-required Performance Milestone. There are approximately 1900 coolers available for measurement. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

INTEGRATED WORKFLOW MANAGEMENT FOR PARTICLE ACCELERATOR SIMULATION

Supercomputing systems are used for a wide range of computationally demanding tasks in many fields of science and engineering. They play a key role in numerical simulation, in which mathematical models are computed in order to simulate the behavior of physical systems. Scientists and engineers that use supercomputers for numerical simulation often have their productivity limited by the need to manually organize and manage extremely large amounts of data that are often produced and consumed by the software programs run on these systems. Recognizing these limitations, Kitware Inc. (Clifton Park, NY) and SLAC National Accelerator Laboratory (Menlo Park, CA) are developing an advanced software platform that can reduce the cognitive overhead required by knowledge workers when using supercomputers for numerical simulation. Phase I of the project is complete and includes the development of new capabilities for organizing simulation project files, improvements to the user interface and overall usability, and deployment of a “middle tier” server to sit between user desktop machines and supercomputers to offload much of the data management workload. The project also developed prototype software for executing sequences of numerical simulations, and a prototype for migrating supercomputing software to cloud-based computing systems to provide a potential alternative to supercomputers with different logistical and price-to-performance tradeoffs.

Tourtellott, John↗
DOE OSTI2019

NEAMS Workbench and Bison Fuel Performance Remote Application Configuration

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership class facilities. The NEAMS Workbench [1,2,3] initiative will facilitate the transition from conventional computer codes to high-fidelity ones by providing a common analysis environment and interface for model creation, review, execution, output review, and visualization for integrated codes. The BISON fuel performance code [4] is a finite element method (FEM)-based software being developed by multiple organizations led by the Idaho National Laboratory for the US Department of Energy Office of Nuclear Energy. BISON can simulate a variety of fuel and cladding compositions and geometries in varying dimensionalities, depending upon the problem type and complexity, including one-dimensional (1D), 1.5D, 2D axially symmetric (2D-rz), 2D radial-azimuthal (2D-rθ), or 3D models. The NEAMS Workbench allows execution of the BISON fuel performance code on local and remote compute resources. In this report, the detailed instructions of configuring the NEAMS Workbench for remote execution of the BISON fuel performance code on a portable batch system (PBS)-scheduled compute resource, as well the transfer of associated Bison files, is illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗
DOE OSTI2020

Software Sustainability $\&$ High Energy Physics

New facilities of the 2020s, such as the High Luminosity Large Hadron Collider (HL-LHC), will be relevant through at least the 2030s. This means that their software efforts and those that are used to analyze their data need to consider sustainability to enable their adaptability to new challenges, longevity, and efficiency, over at least this period. This will help ensure that this software will be easier to develop and maintain, that it remains available in the future on new platforms, that it meets new needs, and that it is as reusable as possible. This report discusses a virtual half-day workshop on "Software Sustainability and High Energy Physics" that aimed 1) to bring together experts from HEP as well as those from outside to share their experiences and practices, and 2) to articulate a vision that helps the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) to create a work plan to implement elements of software sustainability. Software sustainability practices could lead to new collaborations, including elements of HEP software being directly used outside the field, and, as has happened more frequently in recent years, to HEP developers contributing to software developed outside the field rather than reinventing it. A focus on and skills related to sustainable software will give HEP software developers an important skill that is essential to careers in the realm of software, inside or outside HEP. The report closes with recommendations to improve software sustainability in HEP, aimed at the HEP community via IRIS-HEP and the HEP Software Foundation (HSF).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

CMS Analysis and Data Reduction with Apache Spark

Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems for distributed data processing, collectively called "Big Data" technologies have emerged from industry and open source projects to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and tools, promising a fresh look at analysis of very large datasets that could potentially reduce the time-to-physics with increased interactivity. Moreover these new tools are typically actively developed by large communities, often profiting of industry resources, and under open source licensing. These factors result in a boost for adoption and maturity of the tools and for the communities supporting them, at the same time helping in reducing the cost of ownership for the end-users. In this talk, we are presenting studies of using Apache Spark for end user data analysis. We are studying the HEP analysis workflow separated into two thrusts: the reduction of centrally produced experiment datasets and the end-analysis up to the publication plot. Studying the first thrust, CMS is working together with CERN openlab and Intel on the CMS Big Data Reduction Facility. The goal is to reduce 1 PB of official CMS data to 1 TB of ntuple output for analysis. We are presenting the progress of this 2-year project with first results of scaling up Spark-based HEP analysis. Studying the second thrust, we are presenting studies on using Apache Spark for a CMS Dark Matter physics search, comparing Spark's feasibility, usability and performance to the ROOT-based analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Determing the Radiative Heat Transfer out of the Fireball of an Atmospheric Nuclear Detonation using Experimental Data

When Edgerton, Germeshausen and Grier, Inc. (EG&G) conducted the atmospheric nuclear tests in the 1950s, they made several continuous records of the light output over time with special "streak cameras." Once processed, these "streak films" contained long bands of varying optical density on black-and-white 35mm film. The purpose for creating them was to determine the time-dependent rate of radiative heat transfer out of the fireball. Back then, EG&G's manual examination methods were not precise enough to make complete analysis worthwhile, so the data was never fully analyzed. With the advent of new computer software, recently developed analysis techniques have reduced uncertainty in the data to where re-analysis is providing results far more reliable than anything EG&G published. Previously inaccessible information can now be accurately gathered from the original films. The method described here allows the streak films to be analyzed so a radiative power curve for an atmospheric nuclear detonation can be constructed using only experimental data. It was applied to five streak films here, though it may be applicable to other types of films as well. The data was plotted and compared to solutions generated with the Hybrid Chemistry (HYCHEM) software. The results are explained, and uncertainty values are provided. If the results from more films show consistency and the sources of uncertainty are mitigated, enough data may be discovered to create a correction factor for HYCHEM or to make more accurate yield determinations using G.I. Taylor's equations. Several other conclusions and recommendations are also posed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

Status Report on the Development of Micro-Scheduling Software for the Advanced Outage Control Center Project

The long-term viability of existing nuclear power plants (NPPs) in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet, refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are difficult to coordinate. Finding ways to improve refueling outage performance while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center project is a research and development (R&D) demonstration activity under the Light Water Reactor Sustainability (LWRS) Program. LWRS is a R&D program which works with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current NPPs. The Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, this INL R&D project is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This report describes specific recent efforts to develop a capability called outage Micro-Scheduling. Micro-Scheduling is the ability to allocate and schedule outage support task resources on a sub-hour basis. Micro-Scheduling is the real-time fine-tuning of the outage schedule to react to the actual progress of the primary outage activities to ensure that support task resources are optimally deployed with the least amount of delay and unproductive use of resources. The remaining sections of this report describe in more detail the scheduling challenges that occur during outages, how a Micro-Scheduling capability helps address those challenges, and provides a status update on work accomplished to date and the path forward.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Combining In-situ Diagnostics and Data Analytics for Discovery of Process-Structure-Property Relationships in AM parts – A Step Toward Digital Twins

In-situ additive manufacturing (AM) diagnostic tools (e.g., optical/infrared imaging, acoustic, etc.) already exist to correlate process anomalies to printed part defects. This current work aimed to augment existing capabilities by: 1) Incorporating in-situ imaging w/ machine learning (ML) image processing software (ORNL- developed "Peregrine") for AM process anomaly detection 2) Synchronizing multiple in-situ sensors for simultaneous analysis of AM build events 3) Correlating in-situ AM process data, generated part defects and part mechanical properties The key R&D question investigated was to determine if these new combined hardware/software tools could be used to successfully quantify defect distributions for parts build via SNL laser powder bed fusion (LPBF) machines, aiming to better understand data-driven process-structure-property- performance relationships. High resolution optical cameras and acoustic microphones were successfully integrated in two LPBF machines and linked to the Peregrine ML software. The software was successfully calibrated on both machines and used to image hundreds of layers of multiple builds to train the ML software in identifying printed part vs powder. The software's validation accuracy to identify this aspect increased from 56% to 98.8% over three builds. Lighting conditions inside the chamber were found to significantly impact ML algorithm predictions from in-situ sensors, so these were tailored to each machine's internal framework. Finally, 3D part reconstructions were successfully generated for a build from the compressed stack of layer-wise images. Resolution differences nearest and furthest from the optical camera were discussed. Future work aims to improve optical resolution, increase process anomalies identified, and integrate more sensor modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2015

2015 ESGF Progress Report

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration whose purpose is to develop the software infrastructure needed to facilitate and empower the study of climate change on a global scale. ESGF’s architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces. The cornerstones of its interoperability are the peer-to-peer messaging, which is continuously exchanged among all nodes in the federation; a shared architecture for search and discovery; and a security infrastructure based on industry standards. ESGF integrates popular application engines available from the open-source community with custom components (for data publishing, searching, user interface, security, and messaging) that were developed collaboratively by the team. The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs of the global climate science community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of an advanced ultrasonic phased array for the characterization of thick, reinforced concrete components (Final Scientific/Technical Report)

There are no nondestructive evaluation (NDE) tools capable of characterizing microscale damage throughout the thickness of concrete components, due to the multiphase, heterogeneous and multiscale nature of concrete. Ultrasound is only scattered by features at the same length scale, or smaller, than the wavelength of a wave’s dominant frequency. Successful imaging of microscale damage using ultrasound requires that the ultrasonic wavelength be on the order of a few millimeters (or smaller), yet the heterogeneous microstructure of concrete, with its fine and coarse aggregates, is on this same (and higher) micrometer/millimeter length scale, causing excessive ultrasonic wave scattering even in “good” concrete. The proposed solution applies non-collinear wave mixing to spatially image microscale damage, while still maintaining penetration through thick concrete components. This microscale imaging is possible by combining nonlinear wave mixing, with advanced phased array hardware and software to develop a breakthrough tool that will bring revolutionary changes in NDE of concrete infrastructure in terms of image resolution and depth of penetration. This work uses non-collinear wave mixing which exploits the physics that material nonlinearities such as microscale damage, cause interactions between two intersecting ultrasonic waves due to cross-mixing, which can lead to the generation of a third wave with a frequency and wave number of the sum or difference of the incident waves. The concrete material volume at this mixing point is characterized/imaged. This project delivered a single-sided nonlinear ultrasonic phased array imaging device, that can image microscale damage (microcracks of 100 micrometers) through a 0.5 m thick concrete component and assessed the commercial feasibility of such arrays for improved crack detection.

42 ENGINEERING↗
DOE OSTI2021

NUBOW-3D Demonstration on LFR: Final CRADA Report

The NUBOW-3D software was developed to assist in designing a core restraint system for sodium-cooled fast spectrum reactors. Originally conceived during the FFTF design activities, the United States has been a proponent of limited free bow reactor design ever since to improve safety performance. In fast spectrum reactors, successful safety performance during reactor transients requires favorable reactivity feedback that leads to safe power stabilization or even natural system shutdown. In fast spectrum reactors, one key mechanism that designers use to improve the performance is to make thermal expansion inject negative feedback into the reactor system. While most fast reactor systems generally have a negative reactivity response to geometric expansion, the NUBOW-3D software allows the designers to better explore the impact on reactivity and optimize the system to maximize its impact.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Final Report: High Energy Physics at the Energy Frontier at Louisiana Tech

The Louisiana Tech University High Energy Physics group has developed a research program aimed at experimentally testing the Standard Model of particle physics and searching for new phenomena through a focused set of analyses in collaboration with the ATLAS experiment at the Large Hadron Collider (LHC) at the CERN laboratory in Geneva. This research program includes involvement in the current operation and maintenance of the ATLAS experiment and full involvement in Phase 1 and Phase 2 upgrades in preparation for future high luminosity (HL-LHC) operation of the LHC. Our focus is solely on the ATLAS experiment at the LHC, with some related detector development and software efforts. We have established important service roles on ATLAS in five major areas: Triggers, especially jet triggers; Data Quality monitoring; grid computing; GPU applications for upgrades; and radiation testing for upgrades. Our physics research is focused on multijet measurements and top quark physics in final states containing tau leptons, which we propose to extend into related searches for new phenomena. Focusing on closely related topics in the jet and top analyses and coordinating these analyses in our group has led to high efficiency and increased visibility inside the ATLAS collaboration and beyond. Based on our work in the DØ experiment in Run II of the Fermilab Tevatron Collider, Louisiana Tech has developed a reputation as one of the leading institutions pursuing jet physics studies. Currently we are applying this expertise to the ATLAS experiment, with several multijet analyses in progress.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗