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At least 163 records · Page 9

Radiation Case Strategic Analysis Tool [Fact Sheet]

The LANL Radiation Case Production Planning Tool is an executive-level decision support tool for planning related to the demand and production of radiation cases. The spreadsheet-based tool includes decision factors for stockpile program demand combined with production and infrastructure planning at Y-12. The tool displays graphical comparisons of supply and demand under different scenarios. The tool is based on NNSA planning documents and process analyses from Y12.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Operation Plumbbob

On June 24, 1957, a thirty-seven kiloton nuclear device, codenamed Priscilla, exploded 700 feet over the Nevada Test Site’s Frenchman dry lake. Below, on the lakebed, was a bank vault designed by the Mosler Safe Company for one of several Federal Civil Defense Administration experiments. The vault was constructed “to evaluate the effectiveness of a reinforced-concrete vault and steel vault door in providing protection against the effects of a nuclear detonation.” Blast damage to the exterior was largely confined to the side walls, whose concrete was stripped off; its steel reinforcing rods bent and twisted. The vault door was essentially undamaged and was opened with minimal difficulty. The vault contents - sandbags, movie camera, and thermometers - were only slightly disturbed. The camera operated as planned, running 40 ft of film. The film, however, was completely fogged. Two clinical type thermometers registered 88°F, and a 24-hr stylus American temperature recorder registered a constant 88°F. Priscilla was the fifth of twenty-nine tests conducted in 1957 as part of Operation Plumbbob, whose stated purpose was to conduct tests “aimed to attain new knowledge important to the defense of the United States and the Free World.” Individual events included “proof tests of air defense and antisubmarine warheads to be stockpiled, development tests of bomb components and mockups, and design tests of smaller and lighter warheads.” One test, John, was that of an air-to-air missile detonated 18,500 feet over the test site.

99 GENERAL AND MISCELLANEOUS↗

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↗

Print or order a LANSCE 50th anniversary poster [Poster]

To mark the anniversary of LANSCE and its five decades of cutting-edge science, the National Security Research Center’s graphic designer Gabriella Smith (from CEA-CAS) illustrated a commemorative poster now available for display. The LANSCE (the Los Alamos Neutron Science Center) facility houses one of the nation’s most powerful linear accelerators, which are used to improve safety and security as well as advance technology in stockpile sustainment, modern materials and manufacturing, and threat mitigation, among other areas. Now-deceased Lab scientist Louis Rosen, who is featured prominently on the poster, first proposed creating this major experimental science facility, said NSRC Archivist-Historian Madeline Whitacre (WRS-NSRCMS)

99 GENERAL AND MISCELLANEOUS↗

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↗

New Energy Infrastructure Outlook 2022 [Slides]

This report provides a perspective on energy infrastructure under development in the continental U.S. as of the end of 2021, focusing on those making significant progress toward achieving commercial operation. Infrastructures covered in this report include power plants, electric transmission, natural gas pipelines and liquefied natural gas terminals. Additionally, this report includes a section on stockpiled volumes of coal, natural gas, and petroleum.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗

The Dual-Axis Radiographic Hydrodynamic Test Facility Capability Expansion (DCX) Strategy

The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility is a vital and important part of the Nation’s nuclear security enterprise. With more than two decades of operations, DARHT has a storied history. Conceived in the 1970s, constructed in the 1990s, and operational since 2000, DARHT has advanced from open-air hydrodynamic experiments (hydros) to foam-confined hydros, to vessel-confined hydros, and in 2022, the 75th hydro was successfully completed. Radiography has advanced from a single-axis, single-pulse system to a dual-axis, multi-pulse capability to variable fields of view (VFV) on both accelerators. The culmination of these experiences, accomplishments, and advancements has brought us to a very important question: What do the next two decades at DARHT look like? The world is not the same place it was in the 1990s when construction at DARHT was in progress. Evolving threats, an expanding mission, and technology changes necessitate adaptation. To adapt, the aging facility, accelerators, vessels, and detector systems require improvements to ensure DARHT remains the Nation’s hydrodynamic data foundation for stockpile certification, safety, surety, and global security threats.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY2022

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), test information management system (TIMS), and [WAVES] Analysis for Verified Engineering Simulation (WAVES).

42 ENGINEERING↗

Decision Science for Machine Learning (DeSciML)

The increasing use of machine learning (ML) models to support high-consequence decision making drives a need to increase the rigor of ML-based decision making. Critical problems ranging from climate change to nonproliferation monitoring rely on machine learning for aspects of their analyses. Likewise, future technologies, such as incorporation of data-driven methods into the stockpile surveillance and predictive failure analysis for weapons components, will all rely on decision-making that incorporates the output of machine learning models. In this project, our main focus was the development of decision scientific methods that combine uncertainty estimates for machine learning predictions, with a domain-specific model of error costs. Other focus areas include uncertainty measurement in ML predictions, designing decision rules using multiobjecive optimization, the value of uncertainty reduction, and decision-tailored uncertainty quantification for probability estimates. By laying foundations for rigorous decision making based on the predictions of machine learning models, these approaches are directly relevant to every national security mission that applies, or will apply, machine learning to data, most of which entail some decision context.

97 MATHEMATICS AND COMPUTING↗

Florida Alternative Transportation Fuel Resilience Plan

Hurricanes are increasing in frequency, intensity, duration, and are projected to continue increasing. Many counties and cities in Florida are developing resilience plans to help them minimize damage from hurricanes and accelerate recovery. The transportation portion of these plans tend to focus on bolstering road infrastructure, stockpiling diesel for strategic fleets, purchasing high-water vehicles, and placing evacuation shelters in safe areas. An Achilles heel of these plans is their dependence on diesel fuel, which is particularly vulnerable to hurricane-related disruptions since 90% of petroleum in Florida needs to be imported via maritime tanker. These tankers are restricted from accessing Florida ports before and during hurricanes because the risks of damage to the port facilities and tanker are too high. Therefore, transportation resilience can be fortified by diversifying the transportation fuels utilized in a hurricane.

33 ADVANCED PROPULSION SYSTEMS↗