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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2020

Fissionable Materials Handlers Operators-Initial Training

These courses were designed for all Initial Fissionable Material Handlers Operators and Supervisors whose job activities will require the performance of Fissile Material Operations located within the Plutonium Facility (PF-4). The course requirements are based on DOE order 426.2, Personnel Section, Qualification, and Training Requirements for Fissionable Material Handlers. These courses are required training for all initial Fissionable Material Handlers and is specific to TA-55 FMH Certification. It covers the core areas and topics in Criticality Safety, Material-at-Risk, Nuclear Material Control and Accountability, Radiological Protection, TA-55 Material Handling and Movement.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS2024

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗

DOE OSTI2017

Remote Monitoring System Design Requirements for Accountable Nuclear Materials at the Nevada National Security Site

The Nevada National Security Site (NNSS) worked with other sites within the Department of Energy National Nuclear Security Administration weapons complex to develop design requirements for a Remote Monitoring System. System objectives included: Continuous monitoring of packaging (containers) within a Facility's buildings to meet Material Control and Accountability (MC&A) inventory requirements. Remotely access and receive monitoring data for tamper detection/alarm, tracking information, environmental conditions, equipment metadata (serial number, date of manufacture, etc.), and assessment video feeds. All data processing, storage/retrieval, and communications will be protected in a manner commensurate with its trust level and classification. Remotely collected and processed data will be securely stored, backed up, and archived. Current and historical data will accessible within and outside of a Building (location). Automated creation of reports and data visualization. Design features to facilitate the potential future integration with the Facility's physical security alarm and display system. The requirements may be used to develop an integrated conceptual design or may be used in a modular fashion to inform separate designs. The guiding principles in developing the system objectives include: For MC&A needs, remotely perform the physical inventory and evidence collection of tamper for Security Category I and II packaged material within a facility and be capable of satisfying guidelines establish by DOE M 470.4-6, “Nuclear Material Control and Accountability.” For personnel safety needs: Meet/satisfy Nuclear Explosive Safety requirements. Minimize the exposure of personnel to radiation to be as low as reasonably achievable (ALARA) in accordance with NSTec Radiological Controls Manual. For DOE nuclear materials, Building environment shall be controlled to meet requirements for packaged nuclear materials specified in weapons laboratory literature.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1986

Spacecraft 2000

The Spacecraft 2000 program has been conceived by NASA with the objective to maintain the U.S. in a strong technical position in the space arena. The program is to involve a cooperative NASA/industry effort with long-range technology development aims. The technology areas addressed are related to spacecraft power, spacecraft energy storage, power management and distribution, autonomous operation-control, onboard systems integration, secondary propulsion, communications technologies, and systems/subsystems technology verification. Aspects of Spacecraft 2000 interactions with industry are discussed, taking into account visitations of NASA personnel to selected industrial concerns, most critical concerns (general), major technical concern, technology drivers for future spacecraft power systems, technology considerations for secondary propulsion, and questions of commercialization. Plans related to a Spacecraft 2000 program formulation are also considered.

Faymon, K. A.↗

NASA NTRS1987

Automated Subsystem Control for Life Support System (ASCLSS)

The Automated Subsystem Control for Life Support Systems (ASCLSS) program has successfully developed and demonstrated a generic approach to the automation and control of space station subsystems. The automation system features a hierarchical and distributed real-time control architecture which places maximum controls authority at the lowest or process control level which enhances system autonomy. The ASCLSS demonstration system pioneered many automation and control concepts currently being considered in the space station data management system (DMS). Heavy emphasis is placed on controls hardware and software commonality implemented in accepted standards. The approach demonstrates successfully the application of real-time process and accountability with the subsystem or process developer. The ASCLSS system completely automates a space station subsystem (air revitalization group of the ASCLSS) which moves the crew/operator into a role of supervisory control authority. The ASCLSS program developed over 50 lessons learned which will aide future space station developers in the area of automation and controls..

Block, Roger F.↗

DOE OSTI2015

Electronic Production Control System News Note

The CMD subprogram develops and deploys multi-application weapon component manufacturing capabilities needed to replace sunset technologies, upgrade existing technologies, and introduce new technologies that support the nuclear weapons stockpile. Sandia National Laboratories (SNL) is currently developing an Electronic Production Control System (EPCS) for ASIC production in the back end of line (BEOL) flow. A pre-production version of EPCS has been released and is operating as intended. We are currently processing all ASIC products, including CVV validation ASICs. The BEOL flow includes wafer probe, packaging, quality inspection, initial electrical test, dynamic burn-in, final electrical test, quality inspection, final visual inspection, radiation testing, SNL acceptance, DOE SSO acceptance, and qualification testing steps. EPCS will execute this production workflow (initiate, control, and electronically track each product); it will implement defect prevention strategies; it will create an electronic inventory control system that is accountable for all ASIC material from inception to delivery; it will electronically collect and store any and all required quality evidence and most of the electronic BEOL data; and it will create a management reporting module with production statistics and timelines. The defect prevention strategies include the use of 2D marks on our ASICs with 2D scanners so that there will be no manual entry of part numbers (scanners), will not allow testing the wrong parts in Test and Burn-in. Other defect prevention strategies will negate the possibility of neither using the wrong test or burn-in program for any part nor the use of BEOL machines or boards that are out of calibration. In summary, EPCS is being implemented and it will greatly improve the product acceptance through full electronic data collection and quality control and defect prevention through bar codes, scanners, tracking training of personnel, and tracking tool availability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2014

International Training Course on Implementing State Systems of Accounting for and Control (SSAC) of Nuclear Material for States with Small Quantity Protocols (SQP): Course Overview and Objectives [Slides]

This course is hosted by Los Alamos National Laboratory on behalf of the U.S. National Nuclear Security Administration (NNSA) in collaboration with the IAEA to support Member States in managing small quantities of nuclear and radioactive materials in a manner that is compliant with their international obligations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS1974

United States manned spacecraft reliability experience

Attention is given to the reliability controls in manned spacecraft programs, taking into account the project Mercury, the Gemini program, the Apollo program, the Skylab program, and the Apollo-Soyuz test project. Reliability controls used in these programs are related to reliability management, parts and materials control, failure mode and effects analysis, reliability quantitative analysis, problem reporting and corrective action control, test control, limited-life control, and milestone reviews. A summary is presented of the major reliability tasks and innovations being used on the Space Shuttle program. Examples of these innovations include improved management techniques and an early identification of specific certification tests.

Kleinknecht, K. S.↗

NASA NTRS2017

[Random Variable Read Me File]

Readme for the Random Variable Toolbox usable manner. is a Web-based Git version control repository hosting service. It is mostly used for computer code. It offers all of the distributed version control and source code management (SCM) functionality of Git as well as adding its own features. It provides access control and several collaboration features such as bug tracking, feature requests, task management, and wikis for every project.[3] GitHub offers both plans for private and free repositories on the same account[4] which are commonly used to host open-source software projects.[5] As of April 2017, GitHub reports having almost 20 million users and 57 million repositories,[6] making it the largest host of source code in the world.[7] GitHub has a mascot called Octocat, a cat with five tentacles and a human-like face

Teubert, Christopher↗

NASA NTRS2019

Management by Trajectory: Improving Predictability for Airspace Operations

In the present-day National Airspace System, the air traffic management system attempts to predict the trajectory for each flight based on the flight plan and scheduled or controlled departure time. However, gaps in trajectory data and models, coupled with tactical control actions that are not communicated to automation systems or other stakeholders, lead to trajectory predictions that are less accurate than they could be. This affects traffic flow management performance. Management by Trajectory (MBT) is a NASA concept for air traffic management in which every flight operates in accordance with a 4D trajectory that is negotiated between the airspace user and the FAA to account for the airspace user’s goals while complying with NAS constraints. The primary benefit of MBT is an improvement in system performance due to increased trajectory predictability and stability, which result from managing traffic in all four dimensions (2D route, vertical, and time), ensuring that changes to the flight’s trajectory are incorporated into the assigned trajectory, and utilizing improved time or arrival control standards. Importantly, the performance improvements support increasing efficiency without increasing collision risk. This paper provides an overview of MBT and describes fast-time simulation results evaluating the safety, performance, and efficiency effects of MBT.

Fernandes, Alicia B.↗

NASA NTRS2000

Trajectory Design and Control for the Compton Gamma Ray Observatory Re-Entry

The Compton Gamma Ray Observatory (CGRO) controlled re-entry operation was successfully conducted in June of 2000. The surviving parts of the spacecraft landed in the Pacific Ocean within the predicted footprint. The design of the maneuvers to control the trajectory to accomplish this re-entry presented several challenges. These challenges included timing and duration of the maneuvers, fuel management, post maneuver position knowledge, collision avoidance with other spacecraft, accounting for the break-up of the spacecraft into several pieces with a wide range of ballistic coefficients, and ensuring that the impact footprint would remain within the desired landing area in the event of contingencies. This paper presents the initial re-entry trajectory design and the evolution of the design into the maneuver sequence used for the re-entry. The paper discusses the constraints on the trajectory design, the modifications made to the initial design and the reasons behind these modifications. Data from the re-entry operation are presented.

Hoge, Susan↗

DOE OSTI2023

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗

NASA NTRS2001

Trajectory Design and Control for the Compton Gamma Ray Observatory Re-Entry

The Compton Gamma Ray Observatory (CGRO) controlled re-entry operation was successfully conducted in June of 2000. The surviving parts of the spacecraft landed in the Pacific Ocean within the nominal impact target zone. The design of the maneuvers to control the trajectory to accomplish this re-entry presented several challenges. These challenges included the timing and duration of the maneuvers, propellant management, post-maneuver state determination, collision avoidance with other spacecraft, accounting for the break-up of the spacecraft into several pieces with a wide range of ballistic coefficients, and ensuring that the impact footprint would remain within the desired impact target zone in the event of contingencies. This paper presents the initial re-entry trajectory design and traces the evolution of that design into the maneuver sequence used for the re-entry. The paper also discusses the spacecraft systems and operational constraints imposed on the trajectory design and the required modifications to the initial design based on those constraints. Data from the reentry operation are also presented.

Hoge, Susan↗

DOE OSTI2016

A modeling framework for optimal energy management of a residential building

Residential buildings are currently equipped with energy production facilities, e.g., solar rooftops and batteries, which in conjunction with smart meters, can function as smart energy hubs coordinating the loads and the resources in an optimal manner. This paper presents a mathematical model for the optimal energy management of a residential building and proposes a centralized energy management system (CEMS) framework for off-grid operation. The model of each component of the hub is integrated within the CEMS. The optimal decisions are determined in real-time by considering these models with realistic parameter settings and customer preferences. Model predictive control (MPC) is used to adapt the optimal decisions on a receding horizon to account for the deviations in the system inputs. Simulation results are presented to demonstrate the feasibility and effectiveness of the proposed CEMS framework. Results show that the proposed CEMS can reduce the energy cost and energy consumption of the customers by approximately 17% and 8%, respectively, over a day. In conclusion, using the proposed CEMS, the total charging cycles of the ESS were reduced by more than 50% in a day.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Data from Assessing Precipitation, Evapotranspiration, and NDVI as Controls of U.S. Great Plains Plant Production

Productivity throughout the North American Great Plains grasslands is generally considered to be water limited, with the strength of this limitation increasing as precipitation decreases. We hypothesize that cumulative actual evapotranspiration water loss (AET) from April to July is the precipitation‐related variable most correlated to aboveground net primary production (ANPP) in the U.S. Great Plains (GP). We tested this by evaluating the relationship of ANPP to AET, precipitation, and plant transpiration (Tr). We used multi‐year ANPP data from five sites ranging from semiarid grasslands in Colorado and Wyoming to mesic grasslands in Nebraska and Kansas, mean annual NRCS ANPP, and satellite‐derived normalized difference vegetation index (NDVI) data. Results from the five sites showed that cumulative April‐to‐July AET, precipitation, and Tr were well correlated (R2: 0.54–0.70) to annual changes in ANPP for all but the wettest site. AET and Tr were better correlated to annual changes in ANPP compared to precipitation for the drier sites, and precipitation in August and September had little impact on productivity in drier sites. April‐to‐July cumulative precipitation was best correlated (R2 = 0.63) with interannual variability in ANPP in the most mesic site, while AET and Tr were poorly correlated with ANPP at this site. Cumulative growing season (May‐to‐September) NDVI (iNDVI) was strongly correlated with annual ANPP at the five sites (R2 = 0.90). Using iNDVI as a surrogate for ANPP, we found that county‐level cumulative April–July AET was more strongly correlated to ANPP than precipitation for more than 80% of the GP counties, with precipitation tending to perform better in the eastern more mesic portion of the GP. Including the ratio of AET to potential evapotranspiration (PET) improved the correlation of AET to both iNDVI and mean county‐level NRCS ANPP. Accounting for how different precipitation‐related variables control ANPP (AET in drier portion, precipitation in wetter portion) provides opportunity to develop spatially explicit forecasting of ANPP across the GP for enhancing decision‐making by land managers and use of grassland ANPP for biofuels.

Field Data↗

DOE OSTI2022

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

Abstract Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO $$_2$$ 2 sequestration and wastewater injection. Managing the pressures by controlling injection/extraction are challenging because of complex heterogeneity in the subsurface. The heterogeneity typically requires high-fidelity physics-based models to make predictions on CO $$_2$$ 2 fate. Furthermore, characterizing the heterogeneity accurately is fraught with parametric uncertainty. Accounting for both, heterogeneity and uncertainty, makes this a computationally-intensive problem challenging for current reservoir simulators. To tackle this, we use differentiable programming with a full-physics model and machine learning to determine the fluid extraction rates that prevent over-pressurization at critical reservoir locations. We use DPFEHM framework, which has trustworthy physics based on the standard two-point flux finite volume discretization and is also automatically differentiable like machine learning models. Our physics-informed machine learning framework uses convolutional neural networks to learn an appropriate extraction rate based on the permeability field. We also perform a hyperparameter search to improve the model’s accuracy. Training and testing scenarios are executed to evaluate the feasibility of using physics-informed machine learning to manage reservoir pressures. We constructed and tested a sufficiently accurate simulator that is 400 000 times faster than the underlying physics-based simulator, allowing for near real-time analysis and robust uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Ten-Year ALARA Review of Dosimetry Results 1 January 2008 through 31 December 2017

Dosimetry results from 1 January 2008 through 31 December 2017 were reviewed to demonstrate that radiation protection methods used at Sandia National Laboratories are compliant with regulatory limits and consistent with the philosophy to keep exposures to radiation As Low As is Reasonably Achievable (ALARA). Personnel dosimetry (external and internal) and environmental thermoluminescent dosimeter results were reviewed for the Sandia National Laboratories in New Mexico, California, and Nevada. ALARA is a philosophical approach to radiation protection by managing and controlling radiation exposures (individual and collective) to the work force and to the public to levels that are As Low As is Reasonably Achievable taking social, technical, economic, practical, and public policy considerations into account. ALARA is not a dose limit but a planning tool with the objective to keep doses below applicable dose limits As Low As is Reasonably Achievable. In the case of Sandia National Laboratories, formal ALARA goals are not needed since Collective and individual doses are well below applicable limits through operational ALARA practices implemented during Work Planning and Control activities.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2019

Robust Decentralized State Estimation

The health of a distribution grid is maintained by a distribution management system (DMS). Before the rise of distributed energy resource (DER), the DMS primarily managed the unidirectional power flow through the distribution grid from external sources (e.g. power brought from a large generating plant to the distribution grid by a transmission grid). Now, a typical DMS will utilize distributed energy resource manage systems (DERMS) to account for DER such as rooftop solar, community solar, and wind turbines. Each DERMS is responsible for an area of the distribution grid, issuing commands to the associated real-time automation controller (RTAC) to regulate power flow and maintain health of that section of the grid.

42 ENGINEERING↗