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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Self-Driving Laboratory for Polymer Electronics

Owing to the chemical pluripotency and viscoelastic nature of electronic polymers, polymer electronics have shown unique advances in many emerging applications such as skin-like electronics, large-area printed energy devices, and neuromorphic computing devices, but their development period is years-long. Recent advancements in automation, robotics, and learning algorithms have led to a growing number of self-driving (autonomous) laboratories that have begun to revolutionize the development and accelerated discovery of materials. In this perspective, we first introduce the current state of autonomous laboratories. Then we analyze why it is challenging to conduct polymer electronics research by an autonomous laboratory and highlight the needs. Here, we further discuss our efforts in building an autonomous laboratory, namely Polybot, for the automated synthesis and characterization of electronic polymers and their processing and fabrication into electronic devices. Finally, we share our vision in using a self-driving laboratory for different types of polymer electronics research.

36 MATERIALS SCIENCE↗
NASA NTRS2005

A Proposed Role of Aeroelasticity in NASA's New Exploration Vision

On 14 January 2004, NASA received a mandate to return astronauts to the Moon, evolve a sustained presence there, then head out into the solar system to Mars and perhaps beyond. This new space exploration initiative directs NASA to develop human and robotic technologies that can deliver payloads larger than Apollo to the Moon, to Mars, and bring astronauts and samples safely back to Earth at costs much lower than Apollo. These challenges require creative aerospace systems. On proposed technology for safely delivering payloads to the surface of Mars and returning samples to Earth involves deployed flexible and inflatable decelerators for atmospheric entry. Because inflatable decelerators provide the entry vehicle more drag surface area at smaller mass than traditional ablative devices, this class of decelerators can potentially accomodate larger mass payloads. The flexibility of these lightweight aeroshells can pose both vehicle and aeroelastic stability problems if not properly designed for the expected flight regimes. Computational tools need to be developed for modelling the large and nonlinear deformations of these highly flexible structures. Unlike wind tunnel testing, an integrated and efficient aeroelastic analysis tool can explore the entire flight environment. This paper will provide some background on flexible deployable decelerators, survey the current state of technology and outline the proposed development of an aeroelastic analysis and capability.

Bartels, Robert E.↗
NASA NTRSDate not supplied

Predicting Quadcopter Noise With The Lattice-Boltzmann Method

From small delivery Unmanned Aircraft Systems (UAS) to short-haul building-to-building aircraft, urban air mobility is gaining traction as a new approach to tackle the problem of transportation in densely populated areas. NASA’s vision for vertical lift vehicles is to capitalize on and improve unique capabilities to greatly benefit the United States’ growing civil flight requirements. This vision is embodied in the Revolutionary Vertical Lift Technology (RVLT)project [1]. Beyond safety, one of the chief concerns of communities where drones are becoming more popular is the noise they generate. Noise will undoubtedly be one of the major obstacles to public acceptance of any new urban air mobility technology. The ability to predict the acoustics of new conceptual aircraft with multiple rotors and complex fuselages is critical to enable the creation of quieter designs. The objective of this research is to build up a better physical understanding of the noise generated by a typical quadcopter drone and what it takes to predict it from first principles using computational fluid dynamics (CFD) with the Lattice-Boltzmann method (LBM). The specific goals are to establish best practices to predict multi-rotor and vehicle interaction noise with LBM, validate these predictions by comparing to wind tunnel measurements, and assess the computational cost necessary to obtain accurate predictions.

Francois Cadieux↗
NASA NTRS2003

The Logical Extension

The same software controlling autonomous and crew-assisted operations for the International Space Station (ISS) is enabling commercial enterprises to integrate and automate manual operations, also known as decision logic, in real time across complex and disparate networked applications, databases, servers, and other devices, all with quantifiable business benefits. Auspice Corporation, of Framingham, Massachusetts, developed the Auspice TLX (The Logical Extension) software platform to effectively mimic the human decision-making process. Auspice TLX automates operations across extended enterprise systems, where any given infrastructure can include thousands of computers, servers, switches, and modems that are connected, and therefore, dependent upon each other. The concept behind the Auspice software spawned from a computer program originally developed in 1981 by Cambridge, Massachusetts-based Draper Laboratory for simulating tasks performed by astronauts aboard the Space Shuttle. At the time, the Space Shuttle Program was dependent upon paper-based procedures for its manned space missions, which typically averaged 2 weeks in duration. As the Shuttle Program progressed, NASA began increasing the length of manned missions in preparation for a more permanent space habitat. Acknowledging the need to relinquish paper-based procedures in favor of an electronic processing format to properly monitor and manage the complexities of these longer missions, NASA realized that Draper's task simulation software could be applied to its vision of year-round space occupancy. In 1992, Draper was awarded a NASA contract to build User Interface Language software to enable autonomous operations of a multitude of functions on Space Station Freedom (the station was redesigned in 1993 and converted into the international venture known today as the ISS)

Source record↗
DOE OSTI2015

2015 Summary Report on Industrial and Regulatory Engagement Activities

The Advanced Instrumentation, Information, and Control (II&C) Systems Technologies pathway of the Light Water Reactor Sustainability(LWRS) Program conducts a vigorous engagement strategy with the U.S. nuclear power industry, including the nuclear operating companies, major support organizations, the Nuclear Regulatory Commission (NRC), and suppliers. The goal of this engagement strategy is to develop a shared vision and common understanding across the nuclear industry of the need for II&C modernization, the performance improvement that can be obtained, and the opportunities for collaboration to enact this vision. The primary means of engaging the nuclear operating companies is through a Utility Working Group (UWG), composed of utility representatives that participate in formal meetings and bi-monthly phone calls to provide input on nuclear plant needs and priorities for II&C technologies. Two working groups were initiated during FY 2015 to provide a means for UWG members to focus on particular technologies of interest. The Outage Improvement Working Group consists of eight utilities that participate in periodic conference calls and have access to a share-point web page for acccess to project materials developed in the Advanced Outage Control Center pilot project. In the area of computer-based procedures and automated work packages, the II&C Pathway has worked with the Nuclear Information Technology Strategic Leadership (NITSL) to set up a monthly conference call with interested utility members to discuss various aspects of mobile worker technologies. Twenty one technical and project reports were delivered to the UWG during FY 2015, reflecting the work of the II&C Pathway pilot projects during the year. Distribution of these reports is one of the primary means of transferring to the nuclear industry the knowledge and experience gained during the development of advanced II&C technologies in support of LWR sustainability. Site visits to discuss pilot project activities and future plans were made to Arizona Public Service, Exelon, Duke Energy, Pacific Gas & Electric, SCANA, Southern Nuclear, South Texas Project, STARS Alliance, Tennessee Valley Authority, and Xcel. Discussions were also held on the pathway goals and activities with major industry support organizations during FY 2102, including the Institute of Nuclear Power Operations (INPO), the Nuclear Information Technology Strategic Leadership (NITSL), the Nuclear Energy Institute (NEI), and the Electric Power Research Institute. The Advanced II&C Pathway work was presented at five major industry conferences and Informal discussions were held with key NRC managers at industry conferences. In addition, discussions were held with NRC senior managers on digital regulatory issues through participation on the NEI Digital I&C Working Group. Meetings were held with major industry suppliers and consultants, to explore opportunities for collaboration and to provide a means of pilot project technology transfer. In the international area, discussions were held with Electricite’ de France (EdF) concerning possible collaboration in the area NPP configuration control using intelligent wireless devices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Introducing PRIMRE's MRE Software Knowledge Hub (February 2021)

This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE's roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered. An early draft of new guidance developed from this knowledge is presented.

gap analysis↗
DOE OSTI2025

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗
NASA NTRS1990

Robot tracking system improvements and visual calibration of orbiter position for radiator inspection

The following separate topics are addressed: (1) improving a robotic tracking system; and (2) providing insights into orbiter position calibration for radiator inspection. The objective of the tracking system project was to provide the capability to track moving targets more accurately by adjusting parameters in the control system and implementing a predictive algorithm. A computer model was developed to emulate the tracking system. Using this model as a test bed, a self-tuning algorithm was developed to tune the system gains. The model yielded important findings concerning factors that affect the gains. The self-tuning algorithms will provide the concepts to write a program to automatically tune the gains in the real system. The section concerning orbiter position calibration provides a comparison to previous work that had been performed for plant growth. It provided the conceptualized routines required to visually determine the orbiter position and orientation. Furthermore, it identified the types of information which are required to flow between the robot controller and the vision system.

Tonkay, Gregory↗
NASA NTRS2018

Summary of the 1st AIAA Geometry and Mesh Generation Workshop (GMGW-1) and Future Plans

The 1st AIAA Geometry and Mesh Generation Workshop (GMGW-1) was held in conjunction with the AIAA Aviation Forum and Exposition 2017 and in collaboration with the 3rd AIAA Computational Fluid Dynamics (CFD) High Lift Prediction Workshop (HiLiftPW-3). As the first AIAA workshop on these topics, GMGW-1's broad objectives were to assess the current state-of-the art in geometry preprocessing and mesh generation technology as well as software as applied to aircraft and spacecraft systems. The workshop was intended to identify and develop understanding of areas of needed improvement in terms of performance, accuracy, and applicability. It was also to provide a foundation for documenting best practices for geometry preprocessing and mesh generation. The genesis of GMGW-1 is found in the indictments levied against geometry preprocessing and mesh generation - not undeservedly - by the NASA CFD Vision 2030 Study. In order to create a reference against which future progress in geometry preprocessing and mesh generation can be measured, the organizers of GMGW-1, with the assistance of the organizers of HiLiftPW- 3, focused GMGW-1 on generation of meshes of the NASA High Lift Common Research Model (HL-CRM). Some of the generated meshes were provided for use by the participants in HiLiftPW-3. All meshes and the processes by which they were generated were analyzed by GMGW-1 as a first assessment of state of the art practices. The results of GMGW-1 added quantitative detail to known problem areas including geometry modeling, data interoperability, and amount of human intervention. They do provide a clear path toward a vision of geometry preprocessing and mesh generation in the year 2030. The next milepost along this path will be a second workshop.

Chawner, John R.↗
NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗
DOE OSTI2023

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗
DOE OSTI2023

Quantum optical memory for entanglement distribution

Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories are devices designed to store quantum information in the form of stationary excitations, such as atomic coherence, and are capable of coherently mapping these excitations to flying qubits. Quantum memories can effectively store and manipulate quantum states, making them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelities, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single-photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.

Lei, Yisheng↗
DOE OSTI2016

White paper on nuclear astrophysics and low energy nuclear physics Part 1: Nuclear astrophysics

This white paper informs the nuclear astrophysics community and funding agencies about the scientific directions and priorities of the field and provides input from this community for the 2015 Nuclear Science Long Range Plan. It also summarizes the outcome of the nuclear astrophysics town meeting that was held on August 21–23, 2014 in College Station at the campus of Texas A&M University in preparation of the NSAC Nuclear Science Long Range Plan. It also reflects the outcome of an earlier town meeting of the nuclear astrophysics community organized by the Joint Institute for Nuclear Astrophysics (JINA) on October 9–10, 2012 Detroit, Michigan, with the purpose of developing a vision for nuclear astrophysics in light of the recent NRC decadal surveys in nuclear physics (NP2010) and astronomy (ASTRO2010). Our white paper is informed informed by the town meeting of the Association of Research at University Nuclear Accelerators (ARUNA) that took place at the University of Notre Dame on June 12–13, 2014. In summary we find that nuclear astrophysics is a modern and vibrant field addressing fundamental science questions at the intersection of nuclear physics and astrophysics. These questions relate to the origin of the elements, the nuclear engines that drive life and death of stars, and the properties of dense matter. A broad range of nuclear accelerator facilities, astronomical observatories, theory efforts, and computational capabilities are needed. Answers to long standing key questions are well within reach in the coming decade because of the developments outlined in this white paper.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

White Paper on Nuclear Astrophysics and Low Energy Nuclear Physics - Part 1. Nuclear Astrophysics

This white paper informs the nuclear astrophysics community and funding agencies about the scientific directions and priorities of the field and provides input from this community for the 2015 Nuclear Science Long Range Plan. It summarizes the outcome of the nuclear astrophysics town meeting that was held on August 21 - 23, 2014 in College Station at the campus of Texas A&M University in preparation of the NSAC Nuclear Science Long Range Plan. It also reflects the outcome of an earlier town meeting of the nuclear astrophysics community organized by the Joint Institute for Nuclear Astrophysics (JINA) on October 9 - 10, 2012 Detroit, Michigan, with the purpose of developing a vision for nuclear astrophysics in light of the recent NRC decadal surveys in nuclear physics (NP2010) and astronomy (ASTRO2010). The white paper is furthermore informed by the town meeting of the Association of Research at University Nuclear Accelerators (ARUNA) that took place at the University of Notre Dame on June 12 - 13, 2014. In summary we find that nuclear astrophysics is a modern and vibrant field addressing fundamental science questions at the intersection of nuclear physics and astrophysics. These questions relate to the origin of the elements, the nuclear engines that drive life and death of stars, and the properties of dense matter. A broad range of nuclear accelerator facilities, astronomical observatories, theory efforts, and computational capabilities are needed. With the developments outlined in this white paper, answers to long-standing key questions are well within reach in the coming decade.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2015

White Paper on Nuclear Astrophysics and Low Energy Nuclear Physics Part 1: Nuclear Astrophysics

This white paper informs the nuclear astrophysics community and funding agencies about the scientific directions and priorities of the field and provides input from this community for the 2015 Nuclear Science Long Range Plan. It summarizes the outcome of the nuclear astrophysics town meeting that was held on August 21-23, 2014 in College Station at the campus of Texas AM University in preparation of the NSAC Nuclear Science Long Range Plan. It also reflects the outcome of an earlier town meeting of the nuclear astrophysics community organized by the Joint Institute for Nuclear Astrophysics (JINA) on October 9-10, 2012 Detroit, Michigan, with the purpose of developing a vision for nuclear astrophysics in light of the recent NRC decadal surveys in nuclear physics (NP2010) and astronomy (ASTRO2010). The white paper is furthermore informed by the town meeting of the Association of Research at University Nuclear Accelerators (ARUNA) that took place at the University of Notre Dame on June 12-13, 2014. In summary we find that nuclear astrophysics is a modern and vibrant field addressing fundamental science questions at the intersection of nuclear physics and astrophysics. These questions relate to the origin of the elements, the nuclear engines that drive life and death of stars, and the properties of dense matter. A broad range of nuclear accelerator facilities, astronomical observatories, theory efforts, and computational capabilities are needed. With the developments outlined in this white paper, answers to long standing key questions are well within reach in the coming decade.

Nuclear astrophysics; White paper; Nucleosynthesis↗
DOE OSTI2024

Building Stock Models for Embodied Carbon Emissions—A Review of a Nascent Field

Building stock modeling emerges as a critical tool in the strategic reduction of embodied carbon emissions, which is pivotal in reshaping the evolving construction sector. This review provides an overall view of modern methodologies in building stock modeling, homing in on the nuances of embodied carbon analysis in construction. Examining 23 seminal papers, our study delineates two primary modeling paradigms—top-down and bottom-up—each further compartmentalized into five innovative methods. This study points out the challenges of data scarcity and computational demands, advocating for methodological advancements that promise to refine the precision of building stock models. A groundbreaking trend in recent research is the incorporation of machine learning algorithms, which have demonstrated remarkable capacity, improving stock classification accuracy by 25% and urban material quantification by 40%. Furthermore, the application of remote sensing has revolutionized data acquisition, enhancing data richness by a factor of five. This review offers a critical examination of current practices and charts a course toward an environmentally prudent future. It underscores the transformative impact of building stock modeling in driving ecological stewardship in the construction industry, positioning it as a cornerstone in the quest for sustainability and its significant contribution toward the grand vision of an eco-efficient built environment.

Hu, Ming (ORCID:0000000325831161)↗
NASA NTRS1993

Robotic Variable Polarity Plasma Arc (VPPA) Welding

The need for automated plasma welding was identified in the early stages of the Space Station Freedom Program (SSFP) because it requires approximately 1.3 miles of welding for assembly. As a result of the Variable Polarity Plasma Arc Welding (VPPAW) process's ability to make virtually defect-free welds in aluminum, it was chosen to fulfill the welding needs. Space Station Freedom will be constructed of 2219 aluminum utilizing the computer controlled VPPAW process. The 'Node Radial Docking Port', with it's saddle shaped weld path, has a constantly changing surface angle over 360 deg of the 282 inch weld. The automated robotic VPPAW process requires eight-axes of motion (six-axes of robot and two-axes of positioner movement). The robot control system is programmed to maintain Torch Center Point (TCP) orientation perpendicular to the part while the part positioner is tilted and rotated to maintain the vertical up orientation as required by the VPPAW process. The combined speed of the robot and the positioner are integrated to maintain a constant speed between the part and the torch. A laser-based vision sensor system has also been integrated to track the seam and map the surface of the profile during welding.

Jaffery, Waris S.↗
NASA NTRS2010

Ensuring US National Aeronautics Test Capabilities

U.S. leadership in aeronautics depends on ready access to technologically advanced, efficient, and affordable aeronautics test capabilities. These systems include major wind tunnels and propulsion test facilities and flight test capabilities. The federal government owns the majority of the major aeronautics test capabilities in the United States, primarily through the National Aeronautics and Space Administration (NASA) and the Department of Defense (DoD). However, changes in the Aerospace landscape, primarily the decrease in demand for testing over the last 20 years required an overarching strategy for management of these national assets. Therefore, NASA established the Aeronautics Test Program (ATP) as a two-pronged strategic initiative to: (1) retain and invest in NASA aeronautics test capabilities considered strategically important to the agency and the nation, and (2) establish a strong, high level partnership with the DoD. Test facility utilization is a critical factor for ATP because it relies on user occupancy fees to recover a substantial part of the operations costs for its facilities. Decreasing utilization is an indicator of excess capacity and in some cases low-risk redundancy (i.e., several facilities with basically the same capability and overall low utilization). However, low utilization does not necessarily translate to lack of strategic importance. Some facilities with relatively low utilization are nonetheless vitally important because of the unique nature of the capability and the foreseeable aeronautics testing needs. Unfortunately, since its inception, the customer base for ATP has continued to shrink. Utilization of ATP wind tunnels has declined by more than 50% from the FY 2006 levels. This significant decrease in customer usage is attributable to several factors, including the overall decline in new programs and projects in the aerospace sector; the impact of computational fluid dynamics (CFD) on the design, development, and research process; and the reductions in wind tunnel testing requirements within the largest consumer of ATP wind tunnel test time, the Aeronautics Research Mission Directorate (ARMD). Retirement of the Space Shuttle Program and recent perturbations of NASA's Constellation Program will exacerbate this downward trend. Therefore it is crucial that ATP periodically revisit and determine which of its test capabilities are strategically important, which qualify as low-risk redundancies that could be put in an inactive status or closed, and address the challenges associated with both sustainment and improvements to the test capabilities that must remain active. This presentation will provide an overview of the ATP vision, mission, and goals as well as the challenges and opportunities the program is facing both today and in the future. We will discuss the strategy ATP is taking over the next five years to address the National aeronautics test capability challenges and what the program will do to capitalize on its opportunities to ensure a ready, robust and relevant portfolio of National aeronautics test capabilities.

Marshall, Timothy J.↗