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At least 163 records · Page 9

Assessment of Electrode Contamination Mitigation at 0.5 MA Scale

The Z Machine at Sandia National Laboratories uses current pulses with peaks up to 27 MA to drive target implosions and generate high energy density conditions of interest for stockpile stewardship programs pertinent to the NNSA program portfolio . Physical processes in the region near the Z Machine target create electrode plasmas which seed parasitic current loss that reduce the performance and output of a Z experiment. Electrode surface contaminants (hydrogen, water, hydrocarbons) are thought to be the primary constituent of electrode plasmas which contribute to loss mechanisms. The Sandia team explore d in situ heating and plasma discharge techniques by integrating requisite infrastructure into Sandia's Mykonos LTD accelerator, addressing potential impacts to accelerator operation, and reporting on the impact of these techniques on electrode plasma formation and shot performance. The in situ discharge cleaning utilizes the electrodes of the accelerator to excite an argon-oxygen plasma to sputter and chemically react contaminants from electrode surfaces. Insulating breaks are required to isolate the plasma in electrode regions where loss processes are most likely to occur. The shots on Mykonos validate that these breaks do not perturb experiment performance, reducing the uncertainty on the largest unknown about the in situ cleaning system. Preliminary observations with electrical and optical diagnostics suggest that electrode plasma formation is delayed, and overall inventory has been substantively reduced. In situ heating embeds cartridge heaters into accelerator electrodes and employs a thermal bakeout to rapidly desorb contaminants from electrode surfaces. For the first time, additively manufactured (AM) electrode assemblies were used on a low impedance accelerator to integrate cooling channels and manage thermal gradients. Challenges with poor supplier fabrication to specifications, load alignment, thermal expansion and hardware movement and warpage appears to have introduced large variability in observed loss, though, preventing strong assertions of loss reduction via in situ heating. At this time, an in situ discharge cleaning process offers the lowest risk path to reduce electrode contaminant inventories on Z, though we recommend continuing to develop both approaches. Additional engineering and testing are required to improve the implementation of both systems. .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Requirements Documents for the Large Mechanical Parts Precision Cleaner (LMPPC) in the Optics Assembly Building (OAB)

The National Ignition Facility (NIF) is the world's largest energetic laser whose missions include sresearch in inertial confinement fusion, experiments for the Stockpile Stewardship, and other high fluence laser research. Due to the high fluence of lasers, extreme environmental conditions, and radiation presence, all mechanical parts (metal, plastic, etc.) installed on NIF must be precision cleaned. Precision cleaned parts are also required in supporting facilities like the Optics Processing Facility (OPF). Small debris inside the laser beams or on optics can cause optic damage, interfere with diagnostics, and interfere with experiments.

42 ENGINEERING↗

Multidisciplinary Research and Development at the Dual-Axis Radiograph Hydrodynamic Test Facility (DARHT) [Slides]

DARHT is the nation’s premiere flash radiography facility. Flash radiography allows interior views of complex structures that are rapidly moving. DARHT is used to image the implosion of mock weapon assemblies containing surrogate materials. DARHT is the only dual-axis facility in the nation enabling 3D reconstructions, with multi-pulse capability for multiple time points. DARHT is an essential facility for Science-based Stockpile Stewardship at LANL and within the NNSA complex.

43 PARTICLE ACCELERATORS↗

2022 Agnew and Metropolis Postdoc Fellow Showcase Event Book

Agnew National Security Postdoc Fellows pursue cutting-edge experimental, theoretical, computational science, and engineering research aligned with the national security mission. Metropolis Postdoc Fellows pursue cutting-edge research in the areas of computational and computer science, physics, and engineering. Computer simulation capabilities are developed in support of the stockpile stewardship program together with broader national nuclear security needs. Fellows have access to some of the most powerful supercomputers in the world to perform pioneering research.

42 ENGINEERING↗

Detectors and Instrumentation [Slides]

D&I targets diagnostic maturation and development for subcritical and hydrodynamic experiments 2 to 5 years into the future. Key technology areas include imaging, detectors, instruments and control systems. Most of the work scope is funded from Stockpile Stewardship’s Hydrodynamic and Subcritical Experiment Execution Support (HSEES) portfolio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

National Ignition Facility. Facility and Infrastructure Systems Maintenance Plan

Ensuring the reliability of the NIF, including its support systems, laser systems, target diagnostic systems, and utilities, is essential to the availability of the NIF in its support of NNSA missions. NIF is a key capability in the DOE Stockpile Stewardship Program and supports high energy physics experiments for nuclear weapons, energy, and astrophysics applications. High system reliability provides opportunities for shots and scientific discoveries with opportunities to enhance and upgrade capabilities. This Maintenance Plan (MP) identifies the policies and procedures used to perform and support asset management of the NIF Facility and Infrastructure Systems (FInS), NIF Lasers & Alignment (LASE), NIF Target Experimental Operations (TOPS), NIF Target Area Science and Engineering (TASE), and NIF&PS Control Systems (NCS). The FInS systems include the facility, HVAC, contamination control, beampath, and Line Replaceable Units (LRUs) as well as utilities which create the beampath environments, such as vacuum, argon, or clean dry air. The LASE systems are Programmatic systems which include laser diagnostics, alignment, power conditioning, pulsed power, and input laser systems. The TOPS and TASE systems are also Programmatic systems which include target and diagnostic delivery systems and positioners, many different insertable and fixed target diagnostics, and cryogenic and target gas fill systems. Finally, the NCS systems include both software and hardware for industrial and shot operation control systems. Policies governing administrative and operational practices related to maintenance of FInS, LASE, TOPS, TASE, and NCS systems are described in this plan. In addition, the plan provides processes and procedures for managing, tracking, and documenting the work. This document, the NIF Operations Management Plan, NIF-5020544 (Ref. 1), and NIF Shot Operations Plan, NIF-5018506 (Ref. 2), together satisfy the requirements of the Conduct of Operations. Duties, responsibilities, and reporting requirements of the various positions associated with FInS, LASE, and TOPS maintenance are detailed in this plan. The FInS systems include both Real Property systems with asset management requirements specified in DOE Order 430.1C (Ref. 3) and Programmatic systems. In addition, for FInS, there is a list of the System Level Maintenance Plans (SLMPs) in NIF-1007419198 (Ref. 4) which provide the system descriptions and maintenance plan and schedule. In addition, the list includes the Reliability Centered Maintenance (RCM) and Experience Centered Maintenance (ECM) evaluations that have been performed for applicable FInS systems as well as reliability criticality per Section 3.5. The -AM version of the NIF Maintenance Plan focuses on the reliability program for FInS, LASE, TOPS, TASE, and NCS within the context of the overall NIF Reliability, Availability, and Maintainability (RAM) program and incorporates changes since the -AL version from August 2011 and has been updated to be fully consistent with the updates to Ref. 1. It also includes asset management considerations, updates to the Work Order (WO) process within the NIF Computerized Maintenance Management System (CMMS) which is EAM infor® System Maintenance and Reliability Tracking (SMaRT) (Ref. 5), and updates to metrics and key performance indicators (KPIs).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Looking back at 50 years of cutting-edge capabilities: LANSCE ‘underpins Los Alamos as a world-class scientific institution’

What started with an idea and a memo has since grown into a one-of-a-kind, world-renowned facility that contributes to the nation’s advancement of science and technology. First known as LAMPF (Los Alamos Meson Physics Facility) until the 1990s when it became LANSCE (Los Alamos Neutron Science Center), the facility is celebrating the 50th anniversary of its first full-capacity proton beam on June 9, 1972. Since then, LANSCE has contributed to a range of national security goals, such as supporting the Lab’s stockpile stewardship program, helping to advance the science of medical radioisotopes, improving the understanding of hydrodynamics, and more. “LANSCE has served the nation through its near-unique capabilities,” said Alan Carr, Senior Historian at the National Security Research Center, which houses the facility’s evolution through decades of documents, photos and other materials. “Since 1972, LANSCE has been the Lab’s major experimental science facility and underpins Los Alamos as a world-class scientific institution. This was true 50 years ago and is still true today.” In commemoration of this anniversary, we’re taking a look back at LANSCE’s historic five decades, including its first director, earliest milestones and important contributions to national security.

43 PARTICLE ACCELERATORS↗

LANL Regular Employee Population and Demographics, FY15-21

This document summarizes an effort to compile and analyze the LANL regular employee population’s demographic attributes and trends between FY15-FY21 using MicroStrategy, a web-based data analytics and visualization tool. LANL’s HR Division collected and prepared data for the Weapons Program’s annual reporting activities for the 2017 through 2023 NNSA Stockpile Stewardship and Management Plan (SSMP). Los Alamos workforce data represent the fiscal year-end snapshot of the permanent employee population who are categorized by the Common Occupational Classification System (COCS). This work enables further analyses, including trends for all workforce attributes presented in the SSMPs as well as a definition of a crosswalk between COCS categorization and the internal laboratory job classification hierarchy. Data for other sites and the federal workforce, as shown in the SSMPs, are included and corresponding figures can be visualized within the MicroStrategy tool. A portable, Excel-based version of the tool was developed and shared with the multi-site workforce working group. This summary highlights selected aspects of the LANL regular workforce. The data analyses and visualizations communicate insights within three major themes regarding permanent LANL employees: 1) demographic transformation, 2) attrition, and 3) skills. Regarding demographic transformation, and consistent with the general trend across the enterprise, early career regular employees are the fastest growing group, with growth ranging between 12-34% year-to-year over the seven-year period analyzed. The data also reflect effects of internal and external factors on attrition; the large spike in separations in FY18 aligns with the contract transition from LANS to Triad and the dip in attrition between FY20-FY21 is likely a result of the global pandemic. The population of regular employees in general management, engineer, and operator COCS categories have the fastest growth rates amongst all the occupational categories. The MicroStrategy and Excel tools provide additional details and trends.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enabling High-Energy-Density Physics Using X-Ray Free Electron Lasers

New High-Energy-Density (HED) Physics research facilities, such as x-ray free electron lasers (XFEL) are becoming available to the research community. These new tools can be used to address stockpile stewardship science questions in the HED regime with greater accuracy and in parameter ranges not previously accessible. Two important challenges that must be overcome before using the XFEL are developing simulation tools needed to design the experiment and developing large quantities of inexpensive targets from which the HED state is created. We developed two-dimensional simulations in a new geometry (planar) to determine basic plasma parameters that could be expected in a notional experiment. We developed a postprocessor that used the results of the simulations to predict the x-ray Thomson scattering (XRTS) signal that yield the plasma density and pressure at a specified location and time. Finally, we developed several possible target geometries that are inexpensive and easy to use. With these tools in hand, the risk in designing an experiment for an XFEL is significantly reduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Health Assessment and Performance Monitoring of Large Machine Diagnostics

Presentation to be given at the CCS-6 Statistical Seminar Series. Regularly maintained and operated diagnostic machines are a backbone of data collection and are a vital component of the Stockpile Stewardship Program’s efforts to better understand nuclear physics. The Cygnus X-ray machine, stationed at the Nevada National Security Site’s U1a underground facility, is one such diagnostic that provides a radiographic capability for the subcritical experiment program. Component failures within Cygnus can result in catastrophic downtime for the diagnostic, affecting performance, schedules, and cost. However, over the years various measurements have been collected on the two Cygnus axes, including voltage and current measurements at different locations, which we believe have predictive power to indicate machine health. We will share preliminary insight into this data and the machine learning approaches we are taking to assess Cygnus’ health, observe declining performance, and predict failures.

97 MATHEMATICS AND COMPUTING↗

DARHT Overview [Slides]

DARHT is a key facility for Stockpile Stewardship. Dual Axis Radiographic Hydrodynamic Test Facility - World-class X-ray radiography for dynamic non-nuclear tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fission Product Yields of 233 U and 239 Pu by Neutron-Induced Fission at Neutron Energies from 0.18-140 MeV [Slides]

Nuclear fission is an important process with applications in astrophysics, nuclear reactors, and stockpile stewardship. Despite having been discovered over 80 years ago, fission is not fully described by a predictive model. This study will show fission product mass yields and total kinetic energies (TKE) across a large range of incident neutron energies for future refinement of fission models. 233U(n,f) data is used to verify features and structures on a previous experiment and compared against fission models. 239Pu(n,f) data will be analyzed to show new data at higher neutron energies using techniques to handle fission in the presence of alphas. 252Cf(sf) data will be used for calibration and benchmarking with a thin-backed target.

07 ISOTOPE AND RADIATION SOURCES↗

Benchmark and Assessment of the Surrogate Reaction Method for Determining Unknown (n,n') and (n,2n) Reaction Cross Sections

A new approach for determining (n,n' ) and (n,2n) cross sections from a combination of indirect measurements and theory is presented. The method builds on and significantly extends the surrogate reactions framework developed at LLNL. Multiple theory advances are described and the overall approach is demonstrated through an application to benchmark cross sections. The work addresses nuclear data needs of the Stockpile Stewardship Program (SSP) and this report comprises multiple completion criteria for an ASC/PEM Level-2 milestone.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures

The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures promise to provide savings in energy efficiency, area, and latency when compared to traditional CPUs for these types of applications — neuromorphic analog and digital technologies provide both low-power and configurable acceleration of challenging artificial intelligence (AI) algorithms. If designed into a heterogeneous system with other accelerators and conventional compute nodes, these technologies have the potential to augment the capabilities of traditional High Performance Computing (HPC) platforms [5]. This expanded computation space requires not only a new approach to physics simulation, but the ability to evaluate and analyze next-generation architectures specialized for AI/ML workloads in both traditional HPC and embedded ND applications. Developing this capability will enable ASC to understand how this hardware performs in both HPC and ND environments, improve our ability to port our applications, guide the development of computing hardware, and inform vendor interactions, leading them toward solutions that address ASC’s unique requirements.

97 MATHEMATICS AND COMPUTING↗

Predicting and Controlling Corrosion (Abbreviated Final Report)

Corrosion accumulates significant replacement costs in the transportation, utility, manufacturing, and infrastructure sectors. It also underpins several of LLNL’s core missions in stockpile stewardship, defense, and energy security. Whereas most corrosion and aging models are empirically parameterized to describe well-defined conditions late in the reaction, the factors that determine the early stages of corrosion—during which mitigation could be most impactful— are poorly understood. This project addressed the critical need for new approaches to predict the kinetics of corrosion initiation based on firm physical and chemical understanding. The activities encompassed degradation of relevant metals in both hydrogen-rich and environmental corrosion scenarios. The team integrated state-of-the-art multiscale simulation, in situ characterization, and data science within three technical thrusts: hydriding of Ti alloys; aqueous corrosion of Al and Ni-Cr alloys; and degradation of additively manufactured 316L stainless steel. In each case, novel capabilities were developed to identify and track the impacts of key atomistic, compositional, and microstructural features on the metal systems. For hydriding, protocols were developed to tightly integrate multiscale models, advanced multimodal characterization, and machine learning to determine how hydrogen interacts with native passivating surface oxides and nucleates new undesired phases, shedding new light on the critical role of grain boundaries, interfaces, and atomically disordered regions. For aqueous corrosion, the project demonstrated methods to predict dissolution rates of metal surfaces in corrosive solutions, to measure and understand microstructural and grain orientation effects on corrosion susceptibility, and to investigate competing growth and dissolution kinetics of surface oxides. For additively manufactured metals, analysis using state-of-the-art microscopy techniques revealed the role of specific heterogeneities invoked during laser processing, including cellular structure, dislocations, and precipitates, on corrosion susceptibility. In addition to new capabilities and understanding, the project provided an avenue for workforce development, as well as key partnerships with stakeholders in corrosion science.

08 HYDROGEN↗

Mitigation of cross-beam energy transfer with laser bandwidth [Slides]

Control of laser-plasma instabilities (LPI) is critical for inertial fusion. Future stockpile stewardship experiments on the NIF will require increased fusion yield (up to 10 MJ), which will require higher laser energy and intensity and will have a higher LPI risk. To be successful, we need to understand the nonlinear behavior of LPI and develop an improved capability for modeling and mitigating LPI in ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Analytics Supporting Stockpile and Enterprise Planning [Slides]

A robust and growing modeling effort supports Los Alamos weapons leadership as well as NNSA (NA18, NA12, NA19) and DoD (DASD-NM, USSTRATCOM). Current work are valuable to several key NNSA working groups supporting strategic planning: Stockpile Stewardship Management Plan (SSMP); Requirements & Planning Document (RPD) analysis; Requirements and Capacity Working Group (RCWG); Production Integration Collaboration Working Group (PICWG); Enterprise Modeling and Analysis Consortium (EMAC); Cost Estimating Analysis Group (CEAG).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Fission with Exotic Nuclei (Full Technical Report)

Despite its importance for stockpile stewardship or nuclear forensics, data on fission is fragmentary: most experiments have only been performed on stable actinide nuclei and are often incomplete, and theoretical simulations often contain many parameters hard to constrain, which results in large uncertainties. Consequently, nuclear libraries have large gaps for important isotopes. The goal of this project was to prepare to take advantage of the unprecedented yields of radioactive isotopes at the upcoming DOE Facility for Rare Ion Beams and to leverage recent progress in the field of machine learning to develop a comprehensive program of fission studies that could address some of the most pressing problems in nuclear fission over the next several decades. Our project leveraged synergies between experimental nuclear physics, nuclear theory, and data science expertise at LLNL. On the experimental front, our main objective was to develop in-house expertise for inverse kinematics reactions with relativistic beams as well as to field and test new detectors to perform correlated measurements of fission properties. On the theoretical side, the objective was to develop a novel, high-fidelity and scalable approach of fissionfragment calculations based on emulating computationally expensive, quantum-mechanical calculations of nuclear properties with deep neural networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗