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W-8 is part of the Weapon Systems (W) Engineering Division. W Division provides the system engineering and program management necessary to sustain the safety, reliability, and security of Los Alamos National Laboratory’s assets in the active United States nuclear stockpile: the B61, W76, W78, and W88.
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A viewgraph presentation describing plastic activities from committee D-20 is shown.
A navigation and communications network is proposed to support an anticipated need for infrastructure in the Earth-Moon system. Periodic orbits will host the constellations while a novel, autonomous navigation strategy will guide the spacecraft along their path strictly based on satellite-to-satellite telemetry. In particular, this paper investigates the second stage of a larger constellation optimization scheme for multi-spacecraft systems. That is, following an initial orbit down-selection process, this analysis provides insights into the ancillary problem of spacecraft placement. Two case studies are presented that consider configurations of up to four spacecraft for a halo orbit and a cycler trajectory.
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A navigation technology known as LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation) has been known to produce very impressive navigation results for scenarios involving two or more cooperative satellites near the Moon, such that at least one satellite must be in an orbit significantly perturbed by the Earth, such as a lunar halo orbit. The two (or more) satellites track each other using satellite-to-satellite range and/or range-rate measurements. These relative measurements yield absolute orbit navigation when one of the satellites is in a lunar halo orbit, or the like. The geometry between a lunar halo orbiter and a GEO satellite continuously changes, which dramatically improves the information content of a satellite-to-satellite tracking signal. The geometrical variations include significant out-of-plane shifts, as well as inplane shifts. Further, the GEO satellite is almost continuously in view of a lunar halo orbiter. High-fidelity simulations demonstrate that LiAISON technology improves the navigation of GEO orbiters by an order of magnitude, relative to standard ground tracking. If a GEO satellite is navigated using LiAISON- only tracking measurements, its position is typically known to better than 10 meters. If LiAISON measurements are combined with simple radiometric ground observations, then the satellite s position is typically known to better than 3 meters, which is substantially better than the current state of GEO navigation. There are two features of LiAISON that are novel and advantageous compared with conventional satellite navigation. First, ordinary satellite-to-satellite tracking data only provides relative navigation of each satellite. The novelty is the placement of one navigation satellite in an orbit that is significantly perturbed by both the Earth and the Moon. A navigation satellite can track other satellites elsewhere in the Earth-Moon system and acquire knowledge about both satellites absolute positions and velocities, as well as relative positions and velocities in space. The second novelty is that ordinarily one requires many satellites in order to achieve full navigation of any given customer s position and velocity over time. With LiAISON navigation, only a single navigation satellite is needed, provided that the satellite is significantly affected by the gravity of the Earth and the Moon. That single satellite can track another satellite elsewhere in the Earth- Moon system and obtain absolute knowledge of both satellites states.
NREL's Lifecycle Analysis Integration into Opensource Numerical models (LiAISON) framework computes temporally explicit life cycle impacts and resource uses for specific technologies (foreground) in a dynamic system context (background). LiAISON computes results for a series of environmental mid-points enabling an analysis of prospective tradeoffs of emerging technologies toward 2100. This prospective feature is of critical importance when analyzing present-day emerging technologies whose large-scale impacts during deployment phases will occur in different, future system contexts. LiAISON systematically accounts for dynamic system changes by applying an integrated background of the future energy-economy-land-climate system, generated by exogenous integrated assessment models (IAMs). Using IAM scenarios, LiAISON generates a time-series of life cycle inventory (LCI) databases, which are then used to calculate the impacts per functional unit per time step. This expands current practice of using static, future system assumptions, e.g., a specific grid-mix each year. Further, IAM scenarios are provided in a standardized format of shared-socioeconomic pathways (SSP) and representative concentration pathways (RCP) combinations. These are coherent, regularly, published, and peer-reviewed scenario combinations that establish a reproducible and standardized societal and climate mitigation futures context. They are comparable across IAMs and expand the system boundary of the traditional LCA by including dimensions such as societal and behavioral changes. We apply the framework to assess two emerging Power-to-Hydrogen processes, high temperature electrolysis using solid oxide fuel cell (HT-SOE) and polymer electrolyte membrane electrolysis (PEME). We compare the technologies to a baseline Hydrogen production process via steam methane reforming. Despite the decarbonized electricity systems' beneficial effects on the PtH2 processes' carbon intensities, we find environmental tradeoffs, which require technology improvements via learning-by-doing to be alleviated. Future work via ongoing collaborations will focus on linking the framework to other energy-economy-land-climate models and open-source life cycle inventory databases.
Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that takes advantage of the asymmetrical gravity field present in a three-body system in order to perform absolute tracking of satellites using only relative satellite-to-satellite observations. Previous studies have demonstrated LiAISON's practical applications for lunar missions, including a satellite in a halo orbit about either the Earth-Moon L1 or L2 point. This paper studies the viability of applying LiAISON measurements between a lunar halo orbiter and a satellite in a geosynchronous orbit. Simulations demonstrate that the absolute positions and velocities of both satellites are observable using only relative measurements with an achieved uncertainty on the order of observation noise.
This paper examines the benefits of navigating a crewed vehicle at the Moon using both ground tracking and satellite-to-satellite tracking, where the tracking satellite is stationed in a lunar halo orbit. Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that has been shown to dramatically improve the navigation of lunar satellites, libration orbiters, and Earth orbiting satellites using simple scalar satellite-to-satellite observations, such as range or Doppler. In this paper, LiAISON is applied to the problem of navigations a crewed vehicle in low lunar orbit. It has been found that adding LiAISON observations to a ground navigation solution improves the navigation enough to reduce the number of active ground tracking stations from six to three.
Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that takes advantage of the asymmetrical gravity field present in a three-body system in order to perform absolute tracking of satellites using only relative satellite-to-satellite observations. Previous studies have demonstrated LiAISON’s practical applications for lunar missions, including a satellite in a halo orbit about either the Earth-Moon L₁or L₂ point. This paper studies the viability of applying LiAISON measurements between a lunar halo orbiter and a satellite in a geosynchronous orbit. Simulations demonstrate that the absolute positions and velocities of both satellites are observable using only relative measurements with an achieved uncertainty on the order of observation noise.
A method is presented for the automatic determination of assembly partial orders from a liaison graph representation of an assembly through the extraction of preferred subassemblies. In particular, the authors show how to select a set of tentative subassemblies by decomposing a liaison graph into a set of subgraphs based on feasibility and difficulty of disassembly, how to evaluate each of the tentative subassemblies in terms of assembly cost using the subassembly selection indices, and how to construct a hierarchical partial order graph (HPOG) as an assembly plan. The method provides an approach to assembly planning by identifying spatial parallelism in assembly as a means of constructing temporal relationships among assembly operations and solves the problem of finding a cost-effective assembly plan in a flexible environment. A case study of the assembly planning of a mechanical assembly is presented.
This project focuses on delivering solutions under deactivation and decommissioning (D&D) in support of DOE EM-4.11 as well as IT development for environmental applications (KM-IT for EM-4.11) and waste & material management (WIMS for EM-4.22). All technology development related activities will also engage the Office of Technology Development (EM-3.2). This work is also relevant to infrastructure management activities being carried out at DOE sites such as Oak Ridge, Savannah River, Hanford, Idaho and Portsmouth. As appropriate and within the parameters of the DOE-FIU Cooperative Agreement (CA), coordination at the proper level will occur with the sites and national laboratories involved in the project research efforts as well as with the points-of-contact at DOE HQ (e.g., HQ Project Leads, HQ Field Liaisons, Office of Technology Development, CA Technical Monitor, COR, etc.).
The Weapon Systems Engineering Division (W) provides the system engineering and program management necessary to sustain the safety, reliability, and security of the Los Alamos National Laboratory’s assets in the active United States nuclear stockpile - the B61, W76, W78 and W88. The Division generates key certification data for Annual Assessment supporting the Laboratory Director's letter to the President on the health of those warheads. This role demands ongoing surveillance of the active stockpile and evaluation of the potential impact of any issues through design, engineering, fabrication, testing using state-of-the-art computational simulation tools and engineering test facilities. The Division works in close liaison with the several production facilities across the nuclear security complex as well as with the customers in the US Navy and Air Force.
Translators serve a unique role in the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility, offering scientific input through various leadership and service roles. The Translators direct the creation of value-added products (VAPs) and analysis tools that make ARM measurements more accessible to the scientific community. Translators also serve as liaisons between users and the ARM infrastructure, collecting information about priorities and communicating ARM data and services. A key group focus is supporting the DOE Atmospheric System Research (ASR) program scientists and ASR’s efforts towards a process-level understanding of cloud-aerosol interactions, and in reducing uncertainty in global climate model projections. The ARM Translator Group (Table 1) consists of the five Translators, a representative of software development, and one from the Data Quality Office (DQO). Additionally, the ARM Engineering and Process Manager participates in this group and provides input and direction from ARM and its programmatic priorities.
The Student Programs further the Laboratory’s goal of developing and mentoring the next generation of scientific, technical, and professional staff by supporting 2,000+ interns at all levels (high school, undergraduate, graduate, and postgraduate) along with 2,000+ mentors and 70 division student liaisons. The activities include internship promotion and external engagement, intern identification and sourcing, training and orientation, professional and career development, social and community engagement, and compliance.
The Midwest Tribal Energy Resources Association (MTERA) embarked on a 5-year (extended to 7-year) initiative aimed at advancing Tribal energy resilience and sustainability through intertribal collaboration. By bringing together Tribes in Minnesota, Wisconsin, and Michigan (EPA Region 5 Tribes), the project's scope encompassed organizational growth, governance and management formalization and enhancement, and the planning and deployment of energy-related services to Member Tribes. MTERA strategically pursued four key objectives to fulfill its mission: 1. Clearinghouse Development: Creation of a centralized hub offering valuable information, education, and outreach for Tribal communities and their neighbors. 2. Policy Liaison: Serving as a vital link between federal and state agencies to contribute to the formulation of inclusive energy policies that ensure both Tribal and regional energy success. 3. Energy Planning and Research: Providing essential support for energy planning, researching financing opportunities, and exploring effective procurement strategies. 4. Training Support: Facilitating training and apprenticeship initiatives to empower the Tribal workforce and enhance community capabilities.