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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2004

An Enabling Technology for New Planning and Scheduling Paradigms

The Night Projects Directorate at NASA's Marshall Space Flight Center is developing a new planning and scheduling environment and a new scheduling algorithm to enable a paradigm shift in planning and scheduling concepts. Over the past 33 years Marshall has developed and evolved a paradigm for generating payload timelines for Skylab, Spacelab, various other Shuttle payloads, and the International Space Station. The current paradigm starts by collecting the requirements, called ?ask models," from the scientists and technologists for the tasks that are to be scheduled. Because of shortcomings in the current modeling schema, some requirements are entered as notes. Next, a cadre with knowledge of vehicle and hardware modifies these models to encompass and be compatible with the hardware model; again, notes are added when the modeling schema does not provide a better way to represent the requirements. Finally, the models are modified to be compatible with the scheduling engine. Then the models are submitted to the scheduling engine for automatic scheduling or, when requirements are expressed in notes, the timeline is built manually. A future paradigm would provide a scheduling engine that accepts separate science models and hardware models. The modeling schema would have the capability to represent all the requirements without resorting to notes. Furthermore, the scheduling engine would not require that the models be modified to account for the capabilities (limitations) of the scheduling engine. The enabling technology under development at Marshall has three major components: (1) A new modeling schema allows expressing all the requirements of the tasks without resorting to notes or awkward contrivances. The chosen modeling schema is both maximally expressive and easy to use. It utilizes graphical methods to show hierarchies of task constraints and networks of temporal relationships. (2) A new scheduling algorithm automatically schedules the models without the intervention of a scheduling expert. The algorithm is tuned for the constraint hierarchies and the complex temporal relationships provided by the modeling schema. It has an extensive search algorithm that can exploit timing flexibilities and constraint and relationship options. (3) An innovative architecture allows multiple remote users to simultaneously model science and technology requirements and other users to model vehicle and hardware characteristics. The architecture allows the remote users to submit scheduling requests directly to the scheduling engine and immediately see the results. These three components are integrated so that science and technology experts with no knowledge of the vehicle or hardware subsystems and no knowledge of the internal workings of the scheduling engine have the ability to build and submit scheduling requests and see the results. The immediate feedback will hone the users' modeling skills and ultimately enable them to produce the desired timeline. This paper summarizes the three components of the enabling technology and describes how this technology would make a new paradigm possible.

Jaap, John↗
NASA NTRS2010

Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation

Virtually every NASA space-exploration mission represents a compromise between the interests of two expert, dedicated, but very different communities: scientists, who want to go quickly to the places that interest them most and spend as much time there as possible conducting sophisticated experiments, and the engineers and designers charged with maximizing the probability that a given mission will be successful and cost-effective. Recent work at NASA's Jet Propulsion Laboratory (JPL) seeks to enhance communication between these two groups, and to help them reconcile their interests, by developing advanced modeling capabilities with which they can analyze the achievement of science goals and objectives against engineering design and operational constraints. The analyses conducted prior to this study have been point-design driven. Each analysis has been of one hypothetical case which addresses the question: Given a set of constraints, how much science can be done? But the constraints imposed by the architecture team-e.g., rover speed, time allowed for extravehicular activity (EVA), number of sites at which science experiments are to be conducted- are all in early development and carry a great deal of uncertainty. Variations can be incorporated into the analysis, and indeed that has been done in sensitivity studies designed to see which constraint variations have the greatest impact on results. But if a very large number of variations can be analyzed all at once, producing a table that includes virtually the entire trade space under consideration, then we have a tool that enables scientists and mission architects to ask the inverse question: For a given desired level of science (or any other objective), what is the range of constraints that would be needed? With this tool, mission architects could determine, for example, what combinations of rover speed, EVA duration, and other constraints produce the desired results. Further, this tool would help them identify which technology-improvement investments would be likely to produce the largest or most important return. However, the number of variations that need to be considered for such analysis quickly balloons to an unwieldy size. If three variations are considered for each of six constraints-a very modest example-there are a total of 243 variations to consider. If it takes 40 minutes to compute each variation, as it does with HURON, our automated optimization system, then it would take 162 hours or nearly 7 days of round-the-clock computing to calculate the results. Adding further constraints or variations exponentially increases the amount of time that is needed.

Weisbin, Charles R.↗
DOE OSTI2025

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
NASA NTRSDate not supplied

HRP Data Management Plan

The purpose of Human Research Program Data Management Plan (DMP) is to define the processes and activities required for the overall management of the research data collected and managed by HRP throughout their life cycle. New updates to the Data Management Plan in 2023 include 1. CAPABILITIES AND SERVICES Data Repositories. Principal Investigators (PIs) funded by HRP may be asked to submit data to one of several NASA data repositories. HRP archives data in the NASA Life Sciences Portal (NLSP) that it considers to be unique and high value. This includes data from human subjects in space flight (ISS and commercial flights) and ground analogs to spaceflight; spaceflight tech demos involving humans; human omics data including the microbiome; parabolic flight studies; and the NASA Space Radiation Laboratory (NSRL). The Open Science Data Repository (OSDR) includes The Ames Life Sciences Data Archive (ALSDA), used to archive non-human biological data (e.g., animal) generated by the Human Research program, and GeneLab, available to HRP PIs to archive non-human omics data. Catalog for search and retrieval. A catalog of non-human HRP life science experiments, with all associated descriptions (mission, payload, hardware, and personnel related information), and biospecimens is provided on the NLSP public web site for search and retrieval. 2. IRB ROLE IN RETURN OF INDIVIDUAL RESEARCH RESULTS The NASA IRB manages the process for incidental findings and for returning results to subjects for studies for which NASA IRB is the IRB of record. Omics data, especially genomics data, may generate information significant to the health of or risk to a research subject. These data potentially hold the keys to understand lifetime risks of chronic diseases, such as cancer, as well as risks associated with exposures common in space flight. 3. UPDATE OF TERMS – IDENTIFIABLE AND ATTRIBUTABLE DATA HRP now follows Federal and NASA policy by using “identifiable” instead of “attributable” for Personally Identifiable Information (PII). 4. POLICY ABOUT INTERNAL NON-RESEARCH USE OF DATA The HRP Chief Scientist grants access to data from HRP-funded research for non-research internal use that includes program management, customer facilitation, strategic planning, and risk research planning. Typical HRP personnel granted access to HRP research data for internal use include the Element Scientist, Subject Matter Experts (SME), and Data/bioinformatics Scientists. If data accessed for Internal Use is provided to an intramural or extramural scientist for hypothesis driven research, all Federal and NASA regulations (e.g., IRB review) regarding human subject research apply.

Data Management Plan↗
NASA NTRS2024

Autonomy to Enable NASA Missions from Aeronautics to Space

2024 ASCEND Call for Sessions Session Format: Panel Session Topic: Space Exploration and Infrastructure: Exploring, Living, and Working in Space (The panel must map to one of six Session Topics - https://www.ascend.events/presenters/call-for-sessions/#sessiontopics) Title: Autonomy to Enable NASA Missions from Aeronautics to Space Short Session Description: In this panel discussion the National Aeronautics and Space Administration (NASA) will discuss the role that autonomy and Artificial Intelligence (AI) will play as humanity moves off-world. Recent advances in general autonomy tools are changing the way NASA and its partners leverage autonomy for its air and space initiatives, including Advanced Air Mobility (AAM) concepts and potential lunar and Martian operations. The panelists will consist of autonomy subject matter experts familiar with the current state of the art for autonomy across both aeronautical and space domains. They will discuss how those technologies could evolve as operations become more complex and which autonomy technologies can be used in both the space and aeronautical domains. For example, perhaps autonomy work originally developed for terrestrial applications, like Advanced Air Mobility (AAM), could be applied to off-world lunar and Martian applications and vice versa. Additionally, the panel will address common misconceptions of these technologies, obstacles to implementation, and possible solutions for overcoming those obstacles. Join NASA in exploring how research activities can align to streamline autonomy development efforts, advancing NASA's goals to expand humanity's reach beyond Earth for the benefit of all. Contact Information: • Dr. Adam Yingling • Office of Technology, Policy, and Strategy (OTPS) • Adam.j.yingling@nasa.gov, 703-416-9129 Session Length: 1.25 hours, 75 minutes Extended Description: Moderator: Dr. Adam Yingling, NASA, Office of Technology, Policy, and Strategy Panel Speakers: • Autonomy Forum Principals o Dr. Charles Norton, Deputy Chief Technologist, Jet Propulsion Laboratory (JPL) o Dr. Carolyn Mercer, Chief Technologist, Space Mission Directorate (SMD) o Dr. Parimal Kopardekar (PK), Advanced Air Mobility (AAM) Integration Manager o Danette Alan, NASA, Senior Leader for Autonomous Systems, Space Technology Mission Directorate (STMD) o Duane Armstrong, Intelligent Systems Lead, Autonomous Systems Laboratory (ASL) Panel Format: • Introduction (10 min): The panel moderator will provide a 10-minute session introduction that will include an overview NASA’s Moon to Mars architecture, AAM autonomy research, and an introduction of the principals as panel speakers. • Moderated Session Part 1 (30 min): There will be a 30-minute moderated session among the moderator and the five autonomy principals to discuss the current state of art for autonomy and how work developed in one domain may be applicable to other domains; including the merits and challenges for implementing those technologies. • Moderated Session Part 2 (25 min): The moderator will then ask the principals to consider how technologies developed across all the domains might be able to address the most salient challenges identified in the previous session. • Q&A (10 min): The session will conclude with 10-minutes of audience Q&A. Session Goals and Outcomes: The session goals are 1) to communicate the importance of autonomy for both aeronautical and space mission, 2) Investigate potential synergies across autonomy research efforts that will enable scalable operations, and 3) to receive community feedback as NASA leverages autonomy to evolve aviation on Earth and enable humanity to live and work off-world.

Aerospace↗
NASA NTRS1994

Scientific and technical photography at NASA Langley Research Center

As part of my assignment connected with the Scientific and Technical Photography & Lab (STPL) at the NASA Langley Research Center I conducted a series of interviews and observed the day to day operations of the STPL with the ultimate objective of becoming exposed first hand to a scientific and technical photo/imaging department for which my school prepares its graduates. I was also asked to share my observations with the staff in order that these comments and observations might assist the STPL to better serve its customers. Meetings with several individuals responsible for various wind tunnels and with a group that provides photo-optical instrumentation services at the Center gave me an overview of the services provided by the Lab and possible areas for development. In summary form these are some of the observations that resulted from the interviews and daily contact with the STPL facility. (1) The STPL is perceived as a valuable and almost indispensable service group within the organization. This comment was invariably made by everyone. Everyone also seemed to support the idea that the STPL continue to provide its current level of service and quality. (2) The STPL generally is not perceived to be a highly technically oriented group but rather as a provider of high quality photographic illustration and documentation services. In spite of the importance and high marks assigned to the STPL there are several observations that merit consideration and evaluation for possible inclusion into the STPL's scope of expertise and future operating practices. (1) While the care and concern for artistic rendition of subjects is seen as laudable and sometimes valuable, the time that this often requires is seen as interfering with keeping the tunnels operating at maximum productivity. Tunnel managers would like to shorten down-time due to photography, have services available during evening hours and on short notice. It may be of interest to the STPL that tunnel managers are incorporating ever greater imaging capabilities in their facilities. To some extent this could mean a reduced demand for traditional photographic services. (2) The photographic archive is seen as a Center resource. Archiving of images, as well as data, is a matter of concern to the investigators. The early holdings of the Photographic Archives are quickly deteriorating. The relative inaccessibility of the material held in the archives is problematic. (3) In certain cases delivery or preparation of digital image files instead of, or along with, hardcopy is already being perceived by the STPL's customers as desirable. The STPL should make this option available, and the fact that it has, or will have this capability widely known. (4) The STPL needs to continue to provide expert advice and technical imaging support in terms of application information to users of traditional photographic and new electronic imaging systems. Cooperative demo projects might be undertaken to maintain or improve the capabilities of the Lab. (5) STPL personnel do not yet have significant electronic imaging or electronic communication skills and improvements in this is an area could potentially have a positive impact on the Center. (6) High speed photographic or imaging services are often mentioned by the STPL as being of primary importance to their mission but the lab supports very few projects calling for high speed imaging services. Much high speed equipment is in poor state of repair. It is interesting to note that when the operation of lasers, digital imaging or quantitative techniques are requested these are directed to another NASA department. Could joint activities be initiated to solve problems? (7). The STPL could acquire more technical assignments if examples of the areas where they posses expertise would be circulated around the center. The fact that the STPL owns high speed video capability could be 'advertised' among its customer base if there truly was an interest in building up a customer base in this area. The STPL could participate in events like TOPS as an exhibitor, as well as a documenter, of the event.

Davidhazy, Andrew↗