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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Spinoff 2009

Topics covered include: Image-Capture Devices Extend Medicine's Reach; Medical Devices Assess, Treat Balance Disorders; NASA Bioreactors Advance Disease Treatments; Robotics Algorithms Provide Nutritional Guidelines; "Anti-Gravity" Treadmills Speed Rehabilitation; Crew Management Processes Revitalize Patient Care; Hubble Systems Optimize Hospital Schedules; Web-based Programs Assess Cognitive Fitness; Electrolyte Concentrates Treat Dehydration; Tools Lighten Designs, Maintain Structural Integrity; Insulating Foams Save Money, Increase Safety; Polyimide Resins Resist Extreme Temperatures; Sensors Locate Radio Interference; Surface Operations Systems Improve Airport Efficiency; Nontoxic Resins Advance Aerospace Manufacturing; Sensors Provide Early Warning of Biological Threats; Robot Saves Soldier's Lives Overseas (MarcBot); Apollo-Era Life Raft Saves Hundreds of Sailors; Circuits Enhance Scientific Instruments and Safety Devices; Tough Textiles Protect Payloads and Public Safety Officers; Forecasting Tools Point to Fishing Hotspots; Air Purifiers Eliminate Pathogens, Preserve Food; Fabrics Protect Sensitive Skin from UV Rays; Phase Change Fabrics Control Temperature; Tiny Devices Project Sharp, Colorful Images; Star-Mapping Tools Enable Tracking of Endangered Animals; Nanofiber Filters Eliminate Contaminants; Modeling Innovations Advance Wind Energy Industry; Thermal Insulation Strips Conserve Energy; Satellite Respondent Buoys Identify Ocean Debris; Mobile Instruments Measure Atmospheric Pollutants; Cloud Imagers Offer New Details on Earth's Health; Antennas Lower Cost of Satellite Access; Feature Detection Systems Enhance Satellite Imagery; Chlorophyll Meters Aid Plant Nutrient Management; Telemetry Boards Interpret Rocket, Airplane Engine Data; Programs Automate Complex Operations Monitoring; Software Tools Streamline Project Management; Modeling Languages Refine Vehicle Design; Radio Relays Improve Wireless Products; Advanced Sensors Boost Optical Communication, Imaging; Tensile Fabrics Enhance Architecture Around the World; Robust Light Filters Support Powerful Imaging Devices; Thermoelectric Devices Cool, Power Electronics; Innovative Tools Advance Revolutionary Weld Technique; Methods Reduce Cost, Enhance Quality of Nanotubes; Gauging Systems Monitor Cryogenic Liquids; Voltage Sensors Monitor Harmful Static; and Compact Instruments Measure Heat Potential.

Source record↗
NASA NTRS2022

Actuator and Motor Control End-to-End V&V on the Mars 2020 Rover

The Mars 2020 Perseverance rover is the most advanced robotic exploration system ever sent to another planet. To support the complex scientific and mobility needs of the mission, the rover utilizes 33 actuators, three multi-degree-of-freedom force-torque sensors, fifteen single or dual-speed resolvers, two solenoid valves, and twelve contact switches. The control for these actuators and sensors is achieved by several levels of flight software, coordinated between two computers with varying bandwidth control loops. Furthermore, the actuators and sensors were integrated into multiple larger robotic mechanisms that were delivered by different organizations at various points in the Integration and Test (I&T) timeline. All of this created a very complex Verification and Validation (V&V) scenario involving multiple subsystems and teams, several hardware and software testbeds with varying levels of fidelity, and significant systems engineering to ensure the overall I&T schedule could be maintained while ensuring system hardware safety.This paper details the integrated V&V effort across multiple teams and venues to provide full coverage of all necessary functionality, performance, and fault protection. First, it provides an overview of how the V&V campaign was subdivided among teams and venues and provides descriptions of the various hardware configurations used to support the testing. The Mars 2020 implementation of the plan incorporates many of the lessons learned from Mars Science Laboratory’s test campaign, and these value-added modifications are discussed here. Also included in this section is the system-level environmental testing approach used for mechanisms. Second, the paper describes the phased approach used by the teams to support new hardware and software deliveries to testbed and Systems I&T. In this approach the test campaign was built upon higher-level mechanism needs for performance, functionality, and safety at specific times in the campaign. Finally, the paper discusses lessons learned from the V&V campaign that should be applied to future large-scale motion control testing efforts.

Borne, Davis↗
NASA NTRS2010

NASA Tech Briefs, March 2010

Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.

Source record↗
NASA NTRS2017

Ames Engineering Directorate

The Ames Engineering Directorate is the principal engineering organization supporting aerospace systems and spaceflight projects at NASA's Ames Research Center in California's Silicon Valley. The Directorate supports all phases of engineering and project management for flight and mission projects-from R&D to Close-out-by leveraging the capabilities of multiple divisions and facilities.The Mission Design Center (MDC) has full end-to-end mission design capability with sophisticated analysis and simulation tools in a collaborative concurrent design environment. Services include concept maturity level (CML) maturation, spacecraft design and trades, scientific instruments selection, feasibility assessments, and proposal support and partnerships. The Engineering Systems Division provides robust project management support as well as systems engineering, mechanical and electrical analysis and design, technical authority and project integration support to a variety of programs and projects across NASA centers. The Applied Manufacturing Division turns abstract ideas into tangible hardware for aeronautics, spaceflight and science applications, specializing in fabrication methods and management of complex fabrication projects. The Engineering Evaluation Lab (EEL) provides full satellite or payload environmental testing services including vibration, temperature, humidity, immersion, pressure/altitude, vacuum, high G centrifuge, shock impact testing and the Flight Processing Center (FPC), which includes cleanrooms, bonded stores and flight preparation resources. The Multi-Mission Operations Center (MMOC) is composed of the facilities, networks, IT equipment, software and support services needed by flight projects to effectively and efficiently perform all mission functions, including planning, scheduling, command, telemetry processing and science analysis.

Small Satellites↗
DOE OSTI2023

Supporting Nuclear Energy Research with MLOps

Artificial intelligence (AI) and machine learning (ML) have been shown to be increasingly helpful tools in a growing number of use-cases relevant to scientific research, despite significant software-related obstacles. There exist large technical costs to setting up, using, and maintaining AI/ML models in production. This often prevents researchers from utilizing these models in their work. The growing field of machine learning operations (MLOps) aims to automate much of the AI/ML life cycle while increasing access to these models. This paper presents our initial work in creating a nuclear energy MLOps platform for use by researchers at Idaho National Laboratory (INL) and aims to reduce the barriers of using AI/ML in scientific research. We hope to promote the integration of the latest AI/ML technologies into researchers' workflows and create more opportunity for scientific innovation. In this paper we discuss how our MLOps efforts aim to increase usage and the impact of AI/ML models created by engineers. We also present several use-cases that are currently integrated. Finally, we evaluate the maturity of our project as well as our plans for future functionality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

NEEMO 15: Evaluation of Human Exploration Systems for Near-Earth Asteroids

The NASA Extreme Environment Mission Operations (NEEMO) 15 mission was focused on near-Earth Asteroid (NEA) exploration techniques evaluation. It began with a University of Delaware autonomous underwater vehicle (AUV) systematically mapping the coral reef for hundreds of meters surrounding the Aquarius habitat. This activity is akin to the type of "far field survey" approach that may be used by a robotic precursor in advance of a human mission to a NEA. Data from the far-field survey were then examined by the NEEMO science team and follow-up exploration traverses were planned, which used Deepworker single-person submersibles. Science traverses at NEEMO 15 were planned according to a prioritized list of scientific objectives developed by the science team based on review and discussion of previous related marine science research including previous marine science saturation missions conducted at the Aquarius habitat. AUV data was used to select several areas of scientific interest. The Deepworker science traverses were then executed at these areas of interest during 4 days of the NEEMO 15 mission and provided higher resolution data such as coral species distribution and mortality. These traverses are analogous to the "near field survey" approach that is expected to be performed by a multi mission space exploration vehicle (MMSEV) during a human mission to a NEA before conducting extravehicular activities (EVA)s. In addition to the science objectives that were pursued, the NEEMO 15 science traverses provided an opportunity to test newly developed software and techniques. Sample collection and instrument deployment on the NEA surface by EVA crew would follow the "near field survey" in a human NEA mission. Sample collection was not necessary for the purposes of the NEEMO science objectives; however, the engineering and operations objectives during NEEMO 15 were to evaluate different combinations of vehicles, crewmembers, tools, and equipment that could be used to perform these tasks on a NEA. Specifically, the productivity and acceptability of simulated NEA exploration activities were systematically quantified and compared when operating with different combinations of crew sizes and exploration systems including MMSEVs, EVA jet packs, and EVA translation devices.

Chappell, Steven P.↗
NASA NTRS1996

NASAwide electronic publishing system-prototype STI electronic document distribution: Stage-4 evaluation report: Appendices - Part 2

This evaluation report contains an introduction, seven chapters, and five appendices. The Introduction describes the purpose, conceptual framework, functional description, and technical report server of the Scientific and Technical Information (STI) Electronic Document Distribution (EDD) project. Chapter 1 documents the results of the prototype STI EDD in actual operation. Chapter 2 documents each NASA center's post processing publication processes. Chapter 3 documents each center's STI software, hardware. and communications configurations. Chapter 7 documents STI EDD policy, practices, and procedures. The appendices consist of (A) the STI EDD Project Plan, (B) Team members, (C) Phasing Schedules, (D) Accessing On-line Reports, and (E) Creating an HTML File and Setting Up an xTRS. In summary, Stage 4 of the NASAwide Electronic Publishing System is the final phase of its implementation through the prototyping and gradual integration of each NASA center's electronic printing systems, desk top publishing systems, and technical report servers, to be able to provide to NASA's engineers, researchers, scientists, and external users, the widest practicable and appropriate dissemination of information concerning its activities and the result thereof to their work stations.

Tuey, Richard C.↗
DOE OSTI2023

Towards a Standard Process Management Infrastructure for Workflows Using Python

Orchestrating the execution of ensembles of processes lies at the core of scientific workflow engines on large scale parallel platforms. This is usually handled using platform-specific command line tools, with limited process management control and potential strain on system resources. The PMIx standard provides a uniform interface to system resources. The low level C implementation of PMIx has hampered its use in workflow engines, leading to the development of Python binding that has yet to gain traction. In this paper, we present our work to harden the PMIx Python client, demonstrating its usability using a prototype Python driver to orchestrate the execution of an ensemble of processes. We present experimental results using the prototype on the Summit supercomputer at Oak Ridge National Laboratory. This work lays the foundation for wider adoption of PMIx for workflow engines, and encourages wider support of more PMIx functionality in vendor provided system software stacks.

Elwasif, Wael↗
DOE OSTI2022

Reimagining Codesign for Advanced Scientific Computing: Report for the ASCR Workshop on Reimagining Codesign

In March 2021, the U.S. Department of Energy’s Advanced Scientific Computing Research program convened the Workshop on Reimagining Codesign. The workshop, also known as ReCoDe, was organized around discussions on eight topic areas: (1) codesign for traditional high-performance computing workloads; (2) codesign of memory/storage systems; (3) codesign of machine learning, neuromorphic, quantum, and other non-von Neumann accelerators; (4) codesign for edge computing and processing at experimental instruments; (5) codesign for security and privacy; (6) hardware design tools and open-source hardware for high-productivity codesign; (7) tools, software stack, and programming languages for high-productivity codesign; and (8) quantitative tools and data collection for modeling and simulation for codesign. The panels identified four Priority Research Directions from these deliberations: (1) breakthrough computing capabilities with targeted heterogeneity and rapid design; (2) software and applications that embrace radical architecture diversity; (3) engineered security and integrity, from transistors to applications; and (4) design with data-rich processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine Learning-enabled Scalable Performance Prediction of Scientific Codes

Hardware architectures become increasingly complex as the compute capabilities grow to exascale. Here, we present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and predicts runtime of that code on the target hardware platform, which is defined in the input parameters. PPT-AMMP transforms the code to an (architecture-independent) intermediate representation, then (i) analyzes the basic block structure of the code, (ii) processes architecture-independent virtual memory access patterns that it uses to build memory reuse distance distribution models for each basic block, and (iii) runs detailed basic-block level simulations to determine hardware pipeline usage. PPT-AMMP uses machine learning and regression techniques to build the prediction models based on small instances of the input code, then integrates into a higher-order discrete-event simulation model of PPT running on Simian PDES engine. We validate PPT-AMMP on four standard computational physics benchmarks and present a use case of hardware parameter sensitivity analysis to identify bottleneck hardware resources on different code inputs. We further extend PPT-AMMP to predict the performance of a scientific application code, namely, the radiation transport mini-app SNAP. To this end, we analyze multi-variate regression models that accurately predict the reuse profiles and the basic block counts. We validate predicted SNAP runtimes against actual measured times.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

MOBI and FEANICS Programming in Labview

The flight software engineering branch provides design and development of embedded real-time software applications for flight and supporting ground systems to support the NASA Aeronautics and Space Programs. In addition, this branch evaluates, develops and implements new technologies for embedded real-time systems, and maintains a laboratory for applications of embedded technology. This branch supports other divisions and is involved with many other projects. My mentor Rochelle and I are involved in the Fluids and Combustion Facility (FCF) project, the MOBI project, and the FEANICS project. The Fluids and Combustion Facility (FCF) will occupy two powered racks on the International Space Station (ISS). It will be a permanent modular, multiuser facility to accommodate microgravity science experiments onboard the ISS's U.S. Laboratory Module. FCF will support NASA Human Exploration and Development of Space program objectives requiring sustained, systematic research in the disciplines of fluid physics and combustion science. The fluids experiment is called FIR and the combustion experiment is called CIR. The MOBI Experiment is an experiment that is performed to understand the physics of bubble segregation and resuspension in an inertia, monodisperse gas-liquid suspension, and to understand how bubble pressure resists segregation in suspensions with continuous phase inertia. The main focus of FEANICS and the solid combustion experiments will be to conduct basic and applied scientific investigations in fire-safety to support NASA's Bioastronautics Initiative. Based on data obtained in microgravity and experience gained from the beginning of the U.S. manned space program, these normal gravity flammability assessments have been assumed to be conservative with respect to flammability in all environments. However, some of the complex interactions that govern ignition and flame growth can only be evaluated in the long durations of microgravity available on the ISS. Before any of these projects actually go to the ISS, they are going to be tested on NASA's KC-135 Low-G airplane, the KC-135 Low-G Flight Research aircraft (a predecessor of the Boeing 707) is used to fly parabolas to create 20-25 seconds of weightlessness so that the astronauts can experience and researchers can investigate the effects of zero gravity. My mentor and I have been working with Labview to write the programs that are going to acquire, analyze and present the data acquired from these Test flights on the KC-135. We have been working closely with electrical, and mechanical engineers to make sure the program and the hardware can communicate and perform the operations necessary for the flight test. LabVIEW delivers a powerful graphical development environment for signal acquisition, measurement analysis, and data presentation, giving you the flexibility of a programming language without the complexity of traditional development tools. The programming of the control panel and the code are both done in GUIs which allow for flexibility in the code and the program.

Rios, Jeffrey N.↗
DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

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↗
NASA NTRS2004

Students Soaring High with Software Spinoff

An educational software product designed by the Educational Technology Team at Ames Research Center is bringing actual aeronautical work performed by NASA engineers to the public in an interactive format for the very first time, in order to introduce future generations of engineers to the fundamentals of flight. The "Exploring Aeronautics" multimedia CD-ROM was created for use by teachers of students in grades 5 through 8. The software offers an introduction to aeronautics and covers the fundamentals of flight, including how airplanes take off, fly, and land. It contains a historical timeline and a glossary of aeronautical terms, examines different types of aircraft, and familiarizes its audience with the tools used by researchers to test aircraft designs, like wind tunnels and computational fluid dynamics. "Exploring Aeronautics" was done in cartoon animation to make it appealing to kids," notes Andrew Doser, an Ames graphic artist who helped to produce the CD-ROM, along with a team of multimedia programmers, artists, and educators, in conjunction with numerous Ames scientists. In addition to lively animation, the software features QuickTime movies and highly intuitive tools to promote usage of NASA s scientific methods in the world of aeronautics.

Source record↗
NASA NTRS2015

T-38 Primary Flight Display Prototyping and HIVE Support Abstract & Summary

This fall I worked in EV3 within NASA's Johnson Space Center in The HIVE (Human Integrated Vehicles & Environments). The HIVE is responsible for human in the loop testing, getting new technologies in front of astronauts, operators, and users early in the development cycle to make the interfaces more human friendly. Some projects the HIVE is working on includes user interfaces for future spacecraft, wearables to alert astronauts about important information, and test beds to simulate mock missions. During my internship I created a prototype for T-38 aircraft displays using LabVIEW, learned how to use microcontrollers, and helped out with other small tasks in the HIVE. The purpose of developing a prototype for T-38 Displays in LabVIEW is to analyze functions of the display such as navigation in a cost and time effective manner. The LabVIEW prototypes allow Ellington Field AOD to easily make adjustments to the display before hardcoding the final product. LabVIEW was used to create a user interface for simulation almost identical to the real aircraft display. Goals to begin the T-38 PFD (Primary Flight Display) prototype included creating a T-38 PFD hardware display in a software environment, designing navigation for the menu's, incorporating vertical and horizontal navigation bars, and to add a heading bug for compass controls connected to the HSI (Horizontal Situation Indicator). To get started with the project, measurements of the entire display were taken. This enabled an accurate model of the hardware display to be created. Navigation of menu's required some exploration of different buttons on the display. The T-38 simulator and aircraft were used for examining the display. After one piece of the prototype was finished, another trip of to the simulator took place. This was done until all goals for the prototype were complete. Some possible integration ideas for displays in the near future are autopilot selection, touch screen displays, and crew member preferences. Complete navigation, control, and function customization will be achievable once a display is fully developed. Other than the T-38 prototyping, I spent time learning how to design small circuits and write code for them to function. This was done by adding electronic circuit components to breadboard and microcontroller then writing code to speak to those components through the microcontroller. I went through an Arduino starter kit to build circuits and code software that allowed the hardware to act. This work was planned to assist in a lighting project this fall but another solution was discovered for the lighting project. Other tasks that I assisted with, included hands on work such as mock-up construction/removal, logic analyzer repairs, and soldering with circuits. The unique opportunity to be involved work with NASA has significantly changed my educational and career goals. This opportunity has only opened the door to my career with engineering. I have learned over the span of this internship that I am fascinated by the type of work that NASA does. My desire to work in the aerospace industry has increased immensely. I hope to return to NASA to be more involved in the advancement of science, engineering, and spaceflight. My interests for my future education and career lie in NASA’s work - pioneering the future in space exploration, scientific discovery and aeronautics research.

Boniface, Andrew↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
NASA NTRS2022

New Rover Conops with High-Performance Onboard Computing: Give Up Raw Data to Reduce Ops Cost and Do More Science

A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.

Didier, A.↗