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At least 685 records · Page 38

Implementing a Laser Stabilization System for Trapping Ca+ Ions: an Internship Reflection

At Lawrence Livermore National Laboratory, I contributed to a project developing 3D printed micro ion traps for quantum computing. I designed, implemented, and assessed a laser stabilization system that locked lasers to the frequencies required for calibrating our High Finesse WS8-10 wavelength meter and for laser cooling and trapping of Ca+ ions. I also programmed a Python interface for hardware communication, data collection, and statistical analysis. Additionally, I optimized and aligned laser beam paths, and I implemented a closed digital feedback loop using Proportional, Integral, and Derivative (PID) control parameters. I analyzed both the long-term and short-term behavior of our locked lasers and adjusted PID parameters to enhance performance. Furthermore, I used COMSOL to simulate the capacitance of a linear Paul trap design and predict our trap’s performance. The procedures I developed for the interface, analysis, and simulations will continue to support the ion trapping experiment after my appointment. I strengthened my skills in data analysis, Python coding, and optical alignment for laser systems. My confidence as a researcher grew, particularly in communicating my research. This experience taught me the importance of careful planning and consideration in research and solidified my desire to continue exploring novel quantum technology as an undergraduate

42 ENGINEERING↗

MatLib-1.0: Nuclear Material Properties Library

The U.S. Nuclear Regulatory Commission (NRC) uses the computer code Fuel Analysis under Steady-state and Transients (FAST) to model steady-state and transient fuel behavior to support regulatory decisions. FAST relies on a material properties library (MatLib) that contains the thermal and mechanical properties of the nuclear materials and coolants of interest to support the US commercial nuclear industry. MatLib contains properties for a variety of nuclear fuels, cladding and other structural materials, gases, and coolants. In this document, material property correlations for the materials contained within MatLib are presented and discussed. When available, comparisons are made between the material property correlations and available data. Additionally, uncertainties are quantified on the material properties, which is then used by the NRC to support uncertainty quantification for best-estimate plus uncertainty safety evaluation reviews. This document describes MatLib-1.0, which is the first official version of the MatLib library. This document is one of a series of documents on FAST; the other documents detail the models used by FAST as well as its integral assessment to experiments and commercial data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

MatLib-1.2.2: Nuclear Material Properties Library

The U.S. Nuclear Regulatory Commission (NRC) uses the computer code Fuel Analysis under Steady-state and Transients (FAST) to model steady-state and transient fuel behavior to support regulatory decisions. FAST relies on a material properties library (MatLib) that contains the thermal and mechanical properties of the nuclear materials and coolants of interest to support the U.S. commercial nuclear industry. MatLib contains properties for a variety of nuclear fuels, cladding and other structural materials, gases, and coolants. In this document, material property correlations for the materials contained within MatLib are presented and discussed. When available, comparisons are made between the material property correlations and available data. Additionally, uncertainties are quantified on the material properties, which is then used by the NRC to support uncertainty quantification for best-estimate plus uncertainty safety evaluation reviews. This document describes MatLib-1.2.2, updated from MatLib-1.2.1 to include additional properties for metallic fuel. It is one of a series of documents on FAST; the other documents detail the models used by FAST as well as its integral assessment to experiments and commercial data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).

59 BASIC BIOLOGICAL SCIENCES↗

The Gremlin Framework

The Gremlin sofrware package is a performance analysis approach targeted to support the Co-Design process for future systems. It consists of a series of modules that can be used to alter a machine's behavior with the goal of emulating future machine properties. The modules can be divided into several classes; the most significant ones are detailed below. PowGre is a series of modules that help explore the power consumption properties of applications and to determine the impact of power constraints on applications. Most of them use low-level processor interfaces to directly control voltage and frequency settings as well as per nodes, socket, or memory power bounds. MemGre are memory Gremlins and implement a new performance analysis technique that captures the application's effective use of the storage capacity of different levels of the memory hierarchy as well as the bandwidth between adjacent levels. The approach models various memory components as resources and measures how much of each resource the application uses from the application's own perspective. To the application a given amount of a resource is "used" if not having this amount will degrade the application's performance. This is in contrast to the hardware-centric perspective that considers "use" as any hardware action that utilizes the resource, even if it has no effect on performance. ResGre are Gremlins that use fault injection techniques to emulate higher fault rates than currently present in today's systems. Faults can be injected through various means, including network interposition, static analysis, and code modification, or direct application notification. ResGre also includes patches to previously released LLNL codes that can counteract and react to injected failures.

Source record↗

Review of Transient Testing of Fast Reactor Fuels in the Transient REActor Test Facility (TREAT)

The restart of the Transient REActor Test (TREAT) facility provides a unique opportunity to engage the fast reactor fuels community to reinitiate in-pile experimental safety studies. Historically, the TREAT facility played a critical role in characterizing the behavior of both metal and oxide fast reactor fuels under off-normal conditions, irradiating hundreds of fuel pins to support fast reactor fuel development programs. The resulting test data has provided validation for a multitude of fuel performance and severe accident analysis computer codes. This paper will provide a review of the historical database of TREAT experiments including experiment design, instrumentation, test objectives, and salient findings. Additionally, the paper will provide an introduction to the current and future experiment plans of the U.S. transient testing program at TREAT.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Containment Sodium Chemistry Models in MELCOR.

To meet regulatory needs for sodium fast reactors’ future development, including licensing requirements, Sandia National Laboratories is modernizing MELCOR, a severe accident analysis computer code developed for the U.S. Nuclear Regulatory Commission (NRC). Specifically, Sandia is modernizing MELCOR to include the capability to model sodium reactors. However, Sandia’s modernization effort primarily focuses on the containment response aspects of the sodium reactor accidents. Sandia began modernizing MELCOR in 2013 to allow a sodium coolant, rather than water, for conventional light water reactors. In the past three years, Sandia has been implementing the sodium chemistry containment models in CONTAIN-LMR, a legacy NRC code, into MELCOR. These chemistry models include spray fire, pool fire and atmosphere chemistry models. Only the first two chemistry models have been implemented though it is intended to implement all these models into MELCOR. A new package called “NAC” has been created to manage the sodium chemistry model more efficiently. In 2017 Sandia began validating the implemented models in MELCOR by simulating available experiments. The CONTAIN-LMR sodium models include sodium atmosphere chemistry and sodium-concrete interaction models. This paper presents sodium property models, the implemented models, implementation issues, and a path towards validation against existing experimental data.

Louie, David↗

Comparison of Attila Transport Code with MCNP in the Analysis of Small Modular Reactor Shielding

Of great importance in the design of a nuclear power plant is the evaluation of shielding from the ionizing radiation produced in the core of the nuclear reactor. This requires simulation software to predict the dose rates in the areas of interest. These problems are referred to as deep penetration problems, as they involve the reduction of a radiation field by two or three orders of magnitude or more. This makes accurate analyses difficult for Monte Carlo based solutions that rely on enough particles being sampled in an area of interest. Comparing the simulation of the same modeled system with more than one computer application, especially one that uses a different algorithmic approach, is a way to gain confidence in the results. In this research, two models were created, one in Monte Carlo N Particle (MCNP) which uses a stochastic algorithmic approach, and the other in Attila, which uses a deterministic algorithmic approach to test the validity of the model and to estimate the dose rates in the area of interest. Successful comparison of the two models is a way we can validate the model used for that estimation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗