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NASA NTRS2006

The Apollo Experience Lessons Learned for Constellation Lunar Dust Management

Lunar dust will present significant challenges to NASA's Lunar Exploration Missions. The challenges can be overcome by using best practices in system engineering design. For successful lunar surface missions, all systems that come into contact with lunar dust must consider the effects throughout the entire design process. Interfaces between all these systems with other systems also must be considered. Incorporating dust management into Concept of Operations and Requirements development are the best place to begin to mitigate the risks presented by lunar dust. However, that is only the beginning. To be successful, every person who works on NASA's Constellation lunar missions must be mindful of this problem. Success will also require fiscal responsibility. NASA must learn from Apollo the root cause of problems caused by dust, and then find the most cost-effective solutions to address each challenge. This will require a combination of common sense existing technologies and promising, innovative technical solutions

Wagner, Sandra↗

NASA NTRSDate not supplied

Creating Benchmark Data for Artificial Intelligence and Machine Learning Space Biology Research

To identify an appropriate AI/ML approach for a specific problem, the best practice is to measure algorithm performance through the benchmarking process. A scientific benchmark consists of an AI-ready dataset and a reference implementation on a specific scientific question. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML to create scientific benchmark datasets in three applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. Currently, there are no standardized datasets available to benchmark AI/ML algorithms in the domain of space biology. In this work, we constructed two AI/ML-ready biological datasets from experiments in space-flown mice: cellular imaging and RNA-seq. First, radiation-exposed immune cells harbor DNA damage foci that can be fluorescently marked to visualize the amount of damage following exposure to ionizing radiation. However, such large datasets are difficult to analyze visually, due to imaging inconsistencies and human bias, and classical image processing approaches can fail on imaging artifacts. AI/ML are therefore exciting alternative, providing the speed of machines and the accuracy of humans. We have made this dataset available at https://registry.opendata.aws/bps_microscopy/. Second, high-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. However, most sequencing datasets suffer from high dimensionality and low sample count. In this work, we used a generative adversarial network to synthesize a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data with sufficient space-flown and ground control mouse liver samples from NASA GeneLab. This dataset is available at https://registry.opendata.aws/bps_rnaseq/. These datasets are now fully open the Space Biology community to test their favorite AI/ML approaches.

James Casaletto↗

NASA NTRS2010

Evaluating Heuristics for Planning Effective and Efficient Inspections

A significant body of knowledge concerning software inspection practice indicates that the value of inspections varies widely both within and across organizations. Inspection effectiveness and efficiency can be measured in numerous ways, and may be affected by a variety of factors such as Inspection planning, the type of software, the developing organization, and many others. In the early 1990's, NASA formulated heuristics for inspection planning based on best practices and early NASA inspection data. Over the intervening years, the body of data from NASA inspections has grown. This paper describes a multi-faceted exploratory analysis performed on this · data to elicit lessons learned in general about conducting inspections and to recommend improvements to the existing heuristics. The contributions of our results include support for modifying some of the original inspection heuristics (e.g. Increasing the recommended page rate), evidence that Inspection planners must choose between efficiency and effectiveness, as a good tradeoff between them may not exist, and Identification of small subsets of inspections for which new inspection heuristics are needed. Most Importantly, this work illustrates the value of collecting rich data on software Inspections, and using it to gain insight into, and Improve, inspection practice.

Shull, Forrest J.↗

NASA NTRS2026

Recommended Practices in Laser-Induced Fluorescence (LIF) Diagnostics for Electric Propulsion

Laser-induced fluorescence (LIF) spectroscopy uses Doppler-shifted laser photons to excite a bound electron transition in an atom or ion, with subsequent fluorescence emission detected in order to measure the local velocity distribution function (VDF) and/or particle density. Due to its non-invasive nature, high spatial resolution, and acceptable difficulty of implementation, LIF has become a favored diagnostic for electric propulsion (EP) plasmas, particularly in the study of Hall thrusters. This paper presents recommended best practices for LIF measurements in electric thrusters, drawn from over three decades of implementation heritage in the EP community. Focusing on both single-photon LIF (typically used to measure VDFs) and two-photon LIF (TALIF, typically used to determine densities), the paper covers selection of atomic transitions to target, experimental setups, and interpretation of data. A number of special topics and advanced applications are discussed, including uncertainty analysis, techniques for high-speed measurements, and applications to a variety of propellants.

plasma plume↗

NASA NTRS2022

Adapting a Trusted AI Framework to Space Mission Autonomy

As artificial intelligence (AI) is increasingly pro- posed for new and future capabilities in space missions, the question of how to trust AI-enabled space autonomy has been explored. Recently, a collaboration between The Aerospace Corporation (Aerospace) and NASA’s Jet Propulsion Labora- tory (JPL) investigated how Aerospace’s Trusted AI Frame- work could be applied to two JPL projects that planned on lev- eraging AI for critical autonomous tasks. This combined effort led to many insights in the practical implementation of trusted AI along with considerable updates to the Trusted AI Frame- work that tailored its topic threads to space exploration. This document cohesively summarizes the enhanced framework as tailored to space missions as well as estimation of the level of trust required as a function of mission criticality and key stakeholders. The goal of this work is to provide a set of best practices to inform autonomy researchers, flight engineers, mission and proposal reviewers, and instrument and mission principal investigators (PI’s) to drive AI-based autonomy that maximizes trust and lowers the barriers to mission adoption for both science and engineering applications.

Amini, Rashied↗

NASA NTRS2026

Recommended Practice for Use of ExB Probes in Electric Propulsion Testing

An ExB probe is an electric propulsion plume diagnostic that has at its core a Wien filter. Ions entering the instrument experience perpendicular electric and magnetic fields and are filtered based on their velocity. While the ExB probe can be used to estimate the ion velocity distribution function, in the electric propulsion community, it is commonly used to measure species fractions. There are numerous probe designs, implementation and operation procedures, and data analysis approaches described and in use across the community. This paper provides recommendations and descriptions of best practices for design, implementation, and data analysis for the ExB probe, with a particular emphasis on Hall and ion thrusters. This work contributes to the broader community goal to standardize the use of diagnostics in electric propulsion testing.

ExB probe↗

NASA NTRS2005

Validation of the Small Hot Jet Acoustic Rig for Jet Noise Research

The development and acoustic validation of the Small Hot Jet Aeroacoustic Rig (SHJAR) is documented. Originally conceived to support fundamental research in jet noise, the rig has been designed and developed using the best practices of the industry. While validating the rig for acoustic work, a method of characterizing all extraneous rig noise was developed. With this in hand, the researcher can know when the jet data being measured is being contaminated and design the experiment around this limitation. Also considered is the question of uncertainty, where it is shown that there is a fundamental uncertainty of 0.5dB or so to the best experiments, confirmed by repeatability studies. One area not generally accounted for in the uncertainty analysis is the variation which can result from differences in initial condition of the nozzle shear layer. This initial condition was modified and the differences in both flow and sound were documented. The bottom line is that extreme caution must be applied when working on small jet rigs, but that highly accurate results can be made independent of scale.

Bridges, James↗

NASA NTRS1925

Astronomical Methods in Aerial Navigation

The astronomical method of determining position is universally used in marine navigation and may also be of service in aerial navigation. The practical application of the method, however, must be modified and adapted to conform to the requirements of aviation. Much of this work of adaptation has already been accomplished, but being scattered through various technical journals in a number of languages, is not readily available. This report is for the purpose of collecting under one cover such previous work as appears to be of value to the aerial navigator, comparing instruments and methods, indicating the best practice, and suggesting future developments. The various methods of determining position and their application and value are outlined, and a brief resume of the theory of the astronomical method is given. Observation instruments are described in detail. A complete discussion of the reduction of observations follows, including a rapid method of finding position from the altitudes of two stars. Maps and map cases are briefly considered. A bibliography of the subject is appended.

Beij, K Hilding↗

NASA NTRS2003

A Study of Technical Engineering Peer Reviews at NASA

This report describes the state of practices of design reviews at NASA and research into what can be done to improve peer review practices. There are many types of reviews at NASA: required and not, formalized and informal, programmatic and technical. Standing project formal reviews such as the Preliminary Design Review and Critical Design Review are a required part of every project and mission development. However, the technical, engineering peer reviews that support teams' work on such projects are informal, some times ad hoc, and inconsistent across the organization. The goal of this work is to identify best practices and lessons learned from NASA's experience, supported by academic research and methodologies to ultimately improve the process. This research has determined that the organization, composition, scope, and approach of the reviews impact their success. Failure Modes and Effects Analysis (FMEA) can identify key areas of concern before or in the reviews. Product definition tools like the Project Priority Matrix, engineering-focused Customer Value Chain Analysis (CVCA), and project or system-based Quality Function Deployment (QFD) help prioritize resources in reviews. The use of information technology and structured design methodologies can strengthen the engineering peer review process to help NASA work towards error-proofing the design process.

Chao, Lawrence P.↗

NASA NTRS2020

Interoperability and Concepts of Operation Assessment for Space Relay Services and Partnerships

The United States National Space Policy provides guidance and directives for U.S. Government agencies to purchase commercial space services and capabilities to the maximum extent practical. In alignment with this guidance, NASA is exploring potential industry partnerships to leverage current or planned commercial space communication and navigation infrastructure to provide services to NASA user missions in the mid-2020s. Leveraging commercial infrastructure and reducing NASA’s reliance on government-owned and operated infrastructure should yield substantial development and operations cost savings. Additionally, the commercial services market will offer NASA a variety of service offerings at competitive prices, while simultaneously allowing NASA to benefit from commercial best practices. Under Appendix G of the Next Space Technologies for Exploration Partnerships (NextSTEP-2) Broad Agency Announcement (BAA), NASA awarded contracts to eight study vendors in May 2019 to investigate the feasibility of applying commercial services concepts to the NASA user mission community. The studies, managed by NASA Glenn Research Center, were completed in October 2019 and detailed ten study topic areas, three of which included: service provider interoperability, user terminal interoperability, and commercial services concept of operations. This report provides a summary of the significant (non-proprietary) findings and recommendations relating to those study areas from the BAA study vendors.

Eric J Knoblock↗

NASA NTRS2016

Covariance Manipulation for Conjunction Assessment

The manipulation of space object covariances to try to provide additional or improved information to conjunction risk assessment is not an uncommon practice. Types of manipulation include fabricating a covariance when it is missing or unreliable to force the probability of collision (Pc) to a maximum value ('PcMax'), scaling a covariance to try to improve its realism or see the effect of covariance volatility on the calculated Pc, and constructing the equivalent of an epoch covariance at a convenient future point in the event ('covariance forecasting'). In bringing these methods to bear for Conjunction Assessment (CA) operations, however, some do not remain fully consistent with best practices for conducting risk management, some seem to be of relatively low utility, and some require additional information before they can contribute fully to risk analysis. This study describes some basic principles of modern risk management (following the Kaplan construct) and then examines the PcMax and covariance forecasting paradigms for alignment with these principles; it then further examines the expected utility of these methods in the modern CA framework. Both paradigms are found to be not without utility, but only in situations that are somewhat carefully circumscribed.

Conjunction↗

NASA NTRSDate not supplied

Setting the Bar for the Replacement of the Probability of Collision Metric

To date, satellite conjunction assessment (CA) risk analysis has largely embraced the probability of collision (Pc) as the omnibus metric to evaluate collision likelihood, and its use in such assessments has mostly been straightforward: at the point at which a conjunction mitigation decision is required, the calculated Pc is compared to a threshold; and if the calculated Pc exceeds that threshold, then a mitigation action is warranted. With only minor variation, this approach is employed by major CA risk assessment centers (e.g., NASA, EUSST, CNES, JAXA) and is advanced as the preferred method in the published CA best practices handbooks. Despite this near unanimity of operational practice, there is a major strain of secondary literature critical of the Pc and willing to propose alternatives. Alfano (2005) pointed out the ability of the Pc to underrepresent the risk in certain situations and counselled a maximum Pc construct. Carpenter (2017, 2019) reiterated this criticism and proposed using instead a confidence interval on the miss distance. Balch et al. (2019) identified what they argued was a defect in the entire Bayesian Pc construct and believed that the use of a more conservative methodology based on covariance ellipsoid overlap was necessary. Delande (2022) introduced the framework of collision “plausibility” to the risk assessment process and sketched out how this might be used operationally. Elkantassi (2022) published a full development of the miss distance confidence interval approach and applied it to several worked examples. While these different approaches to collision risk assessment do differ in their details, they all converge on two central points: first, the Pc’s failure to give an adequate expression of the risk in dilution region situations is a fatal flaw; and second, a conjunction should be presumed risky and in need of mitigation until the evidence of the situation can establish otherwise. These criticisms, if correct, would counsel a number of modifications to current CA operational practice; as such, they force a re-examination of fundamental aspects of the CA problem, including the following: 1. Is the CA risk assessment a probability problem, a statistics problem, or something else? 2. If it is a statistics problem, does it lend itself naturally to a hypothesis test construction? 3. If it can be construed as a hypothesis test, what form should the null hypothesis take, to wit: what constraints exist on the choice of the null hypothesis, what selections are in best alignment with all of the attendant parameters of the problem, and what is implied philosophically by different choices? 4. What are the implications of using the different proposed risk assessment parameters for CA? This question should be answered both in determining how frequently the dilution region situation cited by the critics of the Pc actually appears in an operationally significant manner and the missed detection and false alarm rates of all of the proposed risk assessment metrics, compared both to the Pc and to each other. This paper explores and offers preliminary answers to the above questions, presenting a researched treatment of the philosophical nature of the CA problem and the null hypothesis choice that achieves the greatest consistency with all of the different aspects of operational CA conduct. It then profiles all of the different proposed risk assessment metrics enumerated in the earlier paragraph against an extremely large database of conjunction events at both the 550km and 700km altitudes. The combination of the philosophical exploration of the CA problem and the results of the profiling activity articulates what a risk assessment metric will need to demonstrate, in terms of both innate construction and performance, in order to be a true competitor to the Pc.

conjunction assessment↗

NASA NTRS2011

Requirement Assurance: A Verification Process

Requirement Assurance is an act of requirement verification which assures the stakeholder or customer that a product requirement has produced its "as realized product" and has been verified with conclusive evidence. Product requirement verification answers the question, "did the product meet the stated specification, performance, or design documentation?". In order to ensure the system was built correctly, the practicing system engineer must verify each product requirement using verification methods of inspection, analysis, demonstration, or test. The products of these methods are the "verification artifacts" or "closure artifacts" which are the objective evidence needed to prove the product requirements meet the verification success criteria. Institutional direction is given to the System Engineer in NPR 7123.1A NASA Systems Engineering Processes and Requirements with regards to the requirement verification process. In response, the verification methodology offered in this report meets both the institutional process and requirement verification best practices.

Alexander, Michael G.↗

NASA NTRS2008

Enabling Innovation and Collaboration Across Geography and Culture: A Case Study of NASA's Systems Engineering Community of Practice

In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited personnel from sharing experiences and ideas. Mission failures and new directions for the agency demanded better collaborative tools. In addition, with the push to send astronauts back to the moon and to Mars, NASA recognized that systems engineering would have to improve across the agency. Of the ten field centers, seven had not built a spacecraft in over 30 years, and had lost systems engineering expertise. The Systems Engineering Community of Practice came together to capture the knowledge of its members using the suite of collaborative tools provided by the NASA Engineering Network (NEN.) The NEN provided a secure collaboration space for over 60 practitioners across the agency to assemble and review a NASA systems engineering handbook. Once the handbook was complete, they used the open community area to disseminate it. This case study explores both the technology and the social networking that made the community possible, describes technological approaches that facilitated rapid setup and low maintenance, provides best practices that other organizations could adopt, and discusses the vision for how this community will continue to collaborate across the field centers to benefit the agency as it continues exploring the solar system.

NEN↗

NASA NTRS2011

Implicit Priors in Galaxy Cluster Mass and Scaling Relation Determinations

Deriving the total masses of galaxy clusters from observations of the intracluster medium (ICM) generally requires some prior information, in addition to the assumptions of hydrostatic equilibrium and spherical symmetry. Often, this information takes the form of particular parametrized functions used to describe the cluster gas density and temperature profiles. In this paper, we investigate the implicit priors on hydrostatic masses that result from this fully parametric approach, and the implications of such priors for scaling relations formed from those masses. We show that the application of such fully parametric models of the ICM naturally imposes a prior on the slopes of the derived scaling relations, favoring the self-similar model, and argue that this prior may be influential in practice. In contrast, this bias does not exist for techniques which adopt an explicit prior on the form of the mass profile but describe the ICM non-parametrically. Constraints on the slope of the cluster mass-temperature relation in the literature show a separation based the approach employed, with the results from fully parametric ICM modeling clustering nearer the self-similar value. Given that a primary goal of scaling relation analyses is to test the self-similar model, the application of methods subject to strong, implicit priors should be avoided. Alternative methods and best practices are discussed.

Mantz, A.↗

NASA NTRS2025

NASA Planetary Protection Handbook

This handbook provides guidance to mission providers and Planetary Protection (PP) practitioners on implementing PP measures for both robotic and crewed space missions. This handbook represents major updates to PP practices since a previously drafted handbook from 2010. In 2017, NASA reorganized the Office of Planetary Protection (OPP) from the Science Mission Directorate (SMD) to a Technical Authority (TA) within the Office of Safety and Mission Assurance (OSMA). With this organizational change came a complete overhaul of NASA’s PP policy and technical standards. This handbook reflects the latest NASA PP policy updates in NPR 8715.24, Planetary Protection Provisions for Robotic Extraterrestrial Missions and technical requirements of NASA-STD-8719.27, Implementing Planetary Protection Requirements for Space Flight. This handbook is a companion document to the NPR and technical standard and provides guidance, best practices, background information, and advice for practitioners to consider when implementing PP on NASA missions and NASA-partnered missions.

Nick Benardini↗

NASA NTRS2026

Adaptive Curation at NASA Johnson Space Center: Preparing for Artemis Samples by Leveraging Proven Practices and Innovative Solution

The proper curation of returned astromaterial samples is essential to ensure that high-quality scientific investigations can be conducted for decades, enabling future generations to address evolving research questions. The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (hereafter JSC Curation) is responsible for curating all of NASA’s extraterrestrial samples. Under the governing document, NASA Procedural Requirement (NPR) 7100.5 “Curation of Extraterrestrial Materials”, JSC Curation is charged with “The curation of all extraterrestrial material under NASA control, including future NASA missions.” The Directive goes on to define Curation as including “...documentation, preservation, preparation, and distribution of samples for research, education, and public outreach.” JSC Curation has a long-standing legacy of curating extraterrestrial materials, including but not limited to Apollo and Luna lunar samples, Genesis solar wind samples, Stardust comet samples, asteroid samples (Hayabusa1, Hayabusa2, and OSIRIS-REx), and Antarctic Meteorite samples from a variety of parent bodies. Building on this foundation, the Artemis program introduces new challenges and opportunities for sample curation, requiring both the application of proven practices and the development of innovative solutions. The Artemis Collection will be curated using established protocols refined through decades of experience with Apollo and subsequent sample collections, including but not limited to the utilization of cleanrooms, custom nitrogen gloveboxes, specialized storage containers and tools; all of which have strict material utilization and prohibition requirements. These practices provide a robust framework for contamination control, documentation, and long-term preservation. However, Artemis samples may present unique scientific and operational requirements, including enhanced contamination control measures (relative to Apollo) driven by evolving science objectives. To meet these needs, JSC Curation is actively developing new technologies and protocols that extend beyond traditional approaches, ensuring that the integrity of samples is maintained under increasingly stringent standards. One critical area of innovation is the development of cold sample curation capabilities. Certain Artemis samples, particularly those from Permanently Shadowed Regions (PSRs) and cold environments, are expected to contain ices and volatile components that require preservation and handling at sub-zero or even cryogenic temperatures. JSC Curation is leveraging best practices from the cold and cryogenic sample industries, as well as other government agencies and academic experts, to design facilities and handling procedures that maintain sample integrity while enabling scientific access. The goal is to develop capabilities to allow researchers to investigate volatiles and other temperature-sensitive materials while minimizing chemical and physical alterations from their returned state. In summary, adaptive curation at JSC combines the reliability of proven methodologies with forward-looking innovations to meet the scientific and operational demands of Artemis. Through enhanced contamination control, advanced cold curation capabilities, and an understanding of known and evolving future science priorities, NASA is preparing to maximize the scientific return from Artemis samples and preserve their value for generations of researchers.

Andrea D Harrington↗

NASA NTRS1993

Teaching high-performance skills using above-real-time training

The above real-time training (ARTT) concept is an approach to teaching high-performance skills. ARTT refers to a training paradigm that places the operator in a simulated environment that functions at faster than normal time. It represents a departure from the intuitive, but not often supported, feeling that the best practice is determined by the training environment with the highest fidelity. This approach is hypothesized to provide greater 'transfer value' per simulation trial, by incorporating training techniques and instructional features into the simulator. Two related experiments are discussed. In the first, 25 naive male subjects performed three tank gunnery tasks on a simulator under varying levels of time acceleration (i.e., 1.0x, 1.6x, 2.0x, sequential, and mixed). They were then transferred to a standard (1.0x) condition for testing. Every accelerated condition or combination of conditions produced better training and transfer than the standard condition. Most effective was the presentation of trials at 1.0x, 1.6x, and 2.0x in a random order during training. Overall, the best ARTT group scored about 50 percent higher and trained in 25 percent less time compared to the real-time control group. In the second experiment, 24 mission-capable F-16 pilots performed three tasks on a part-task F-16A flight simulator under varying levels of time compression (i.e., 1.0x, 1.5x, 2.0x, and random). All subjects were then tested in a real-time environment. The emergency procedure (EP) task results showed increased accuracy for the ARTT groups. In testing (transfer), the ARTT groups not only performed the EP more accurately, but dealt with a simultaneous enemy significantly better than a real-time control group. Although the findings on an air combat maneuvering task and stern conversion task were mixed, most measures indicated that the ARTT groups performed better and faster than a real-time control group. Other implications for ARTT are discussed along with future research directions.

Guckenberger, Dutch↗