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NASA NTRS2011

Energy Management Programs at the John F. Kennedy Space Center

The Energy Management internship over the summer of 2011 involved a series of projects related to energy management on the John. F. Kennedy Space Center (KSC). This internship saved KSC $14.3 million through budgetary projections, saved KSC $400,000 through implementation of the recycling program, updated KSC Environmental Management System's (EMS) water and energy-related List of Requirements (LoR) which changed 25.7% of the list, provided a incorporated a 45% design review of the Ordnance Operations Facility (OOF) which noted six errors within the design plans, created a certification system and timeline for implementation regarding compliance to the federal Guiding Principles, and gave off-shore wind as the preferred alternative to on-site renewable energy generation.

Huang, Jeffrey H.↗
NASA NTRS2011

Implementing Strategic Planning Capabilities Within the Mars Relay Operations Service

Throughout this development and deployment process we have followed a few guiding principles: (1) Ensure ubiquitous access through ReSTful and web interfaces; (2) Design a system that is mission and even planet agnostic so that future missions may be added with little hassle, and the system itself may be redeployed for other planetary relay networks; (3) Accept constant input and feedback between mission operators and the development team to ensure that there is a useful product that may be used for years to come.

software development↗
NASA NTRS2012

Metrology of Large Parts

As discussed in the first chapter of this book, there are many different methods to measure a part using optical technology. Chapter 2 discussed the use of machine vision to measure macroscopic features such as length and position, which was extended to the use of interferometry as a linear measurement tool in chapter 3, and laser or other trackers to find the relation of key points on large parts in chapter 4. This chapter looks at measuring large parts to optical tolerances in the sub-micron range using interferometry, ranging, and optical tools discussed in the previous chapters. The purpose of this chapter is not to discuss specific metrology tools (such as interferometers or gauges), but to describe a systems engineering approach to testing large parts. Issues such as material warpage and temperature drifts that may be insignificant when measuring a part to micron levels under a microscope, as will be discussed in later chapters, can prove to be very important when making the same measurement over a larger part. In this chapter, we will define a set of guiding principles for successfully overcoming these challenges and illustrate the application of these principles with real world examples. While these examples are drawn from specific large optical testing applications, they inform the problems associated with testing any large part to optical tolerances. Manufacturing today relies on micrometer level part performance. Fields such as energy and transportation are demanding higher tolerances to provide increased efficiencies and fuel savings. By looking at how the optics industry approaches sub-micrometer metrology, one can gain a better understanding of the metrology challenges for any larger part specified to micrometer tolerances. Testing large parts, whether optical components or precision structures, to optical tolerances is just like testing small parts, only harder. Identical with what one does for small parts, a metrologist tests large parts and optics in particular to quantify their mechanical properties (such as dimensions, mass, etc); their optical prescription or design (i.e. radius of curvature, conic constant, vertex location, size); and their full part shape. And, just as with small parts, a metrologist accomplishes these tests using distance measuring instruments such as tape measures, inside micrometers, coordinate measuring machines, distance measuring interferometers; angle measuring instruments such as theodolites, autocollimators; and surface measuring instruments including interferometers, stylus profilers, interference microscopes, photogrammetric cameras, or other tools. However, while the methodology may be similar, it is more difficult to test a large object for the simple reason that most metrologists do not have the necessary intuition. The skills used to test small parts or optics in a laboratory do not extrapolate to testing large parts in an industrial setting any more than a backyard gardener might successfully operate a farm. But first, what is a large part? A simple definition might be the part's size or diameter. For optics and diffuse surface parts alike, the driving constraint is ability to illuminate the part's surface. For reflective convex mirrors, large is typically anything greater than 1 meter. But, for refractive optics, flats or convex mirrors, large is typically greater than 0.5 meter. While a size definition is simple, it may be less than universal. A more nuanced definition might be that a large part is any component which cannot be easily tested in a standard laboratory environment, on a standard vibration isolated table using standard laboratory infrastructure. A micro-switch or a precision lens might be easily measured to nanometer levels under a microscope in a lab, but a power turbine spline or a larger telescope mirror will not fit under that microscope and may not even fit on the table.

Stahl, H. Philip↗
NASA NTRS2011

Systems Integration Challenges for a National Space Launch System

System Integration was refined through the complexity and early failures experienced in rocket flight. System Integration encompasses many different viewpoints of the system development. System Integration must ensure consistency in development and operations activities. Human Space Flight tends toward large, complex systems. Understanding the system fs operational and use context is the guiding principle for System Integration: (1) Sizeable costs can be driven into systems by not fully understanding context (2). Adhering to the system context throughout the system fs life cycle is essential to maintaining efficient System Integration. System Integration exists within the System Architecture. Beautiful systems are simple in use and operation -- Block upgrades facilitate manageable steps in functionality evolution. Effective System Integration requires a stable system concept. Communication is essential to system simplicity

May, Todd A.↗
NASA NTRS2013

The Tailoring of Traditional Systems Engineering for the Morpheus Project

NASA's Morpheus Project has developed and tested a prototype planetary lander capable of vertical takeoff and landing that is designed to serve as a testbed for advanced spacecraft technologies. The lander vehicle, propelled by a LOX/Methane engine and sized to carry a 500kg payload to the lunar surface, provides a platform for bringing technologies from the laboratory into an integrated flight system at relatively low cost. From the beginning, one of goals for the Morpheus Project was to streamline agency processes and practices. The Morpheus project accepted a challenge to tailor the traditional NASA systems engineering approach in a way that would be appropriate for a lower cost, rapid prototype engineering effort, but retain the essence of the guiding principles. The team has produced innovative ways to create an infrastructure and approach that would challenge existing systems engineering processes while still enabling successful implementation of the current Morpheus Project. This paper describes the tailored systems engineering approach for the Morpheus project, including the processes, tools, and amount of rigor employed over the project's multiple lifecycles since the project began in FY11. Lessons learned from these trials have the potential to be scaled up and improve efficiency on a larger projects or programs.

Devolites, Jennifer L.↗
NASA NTRS2014

Transforming the "Valley of Death" into a "Valley of Opportunity"

Transitioning technology from research to operations (23 R2O) is difficult. The problem's importance is exemplified in the literature and in every failed attempt to do so. Although the R2O gap is often called the "valley of death", a recent a Space Weather editorial called it a "Valley of Opportunity". There are significant opportunities for space weather organizations to learn from the terrestrial experience. Dedicated R2O organizations like those of the various NOAA testbeds and collaborative "proving ground" projects take common approaches to improving terrestrial weather forecasting through the early transition of research capabilities into the operational environment. Here we present experience-proven principles for the establishment and operation of similar space weather organizations, public or private. These principles were developed and currently being demonstrated by NASA at the Applied Meteorology Unit (AMU) and the Short-term Prediction Research and Transition (SPoRT) Center. The AMU was established in 1991 jointly by NASA, the U.S. Air Force (USAF) and the National Weather Service (NWS) to provide tools and techniques for improving weather support to the Space Shuttle Program (Madura et al., 2011). The primary customers were the USAF 45th Weather Squadron (45 WS) and the NWS Spaceflight Meteorology Group (SMG who provided the weather observing and forecast support for Shuttle operations). SPoRT was established in 2002 to transition NASA satellite and remote-sensing technology to the NWS. The continuing success of these organizations suggests the common principles guiding them may be valuable for similar endeavors in the space weather arena.

Jedlovec, Gary J.↗
NASA NTRS2014

Rules for Optical Testing

Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task: Fully Understand the Task, Develop an Error Budget, Continuous Metrology Coverage, Know where you are, Test like you fly, Independent Cross-Checks, Understand All Anomalies. These rules have been applied with great success to the inprocess optical testing and final specification compliance testing of the JWST mirrors.

Stahl, H. Philip↗
NASA NTRS2015

Project Morpheus: Lean Development of a Terrestrial Flight Testbed for Maturing NASA Lander Technologies

NASA's Morpheus Project has developed and tested a prototype planetary lander capable of vertical takeoff and landing that is designed to serve as a testbed for advanced spacecraft technologies. The lander vehicle, propelled by a Liquid Oxygen (LOX)/Methane engine and sized to carry a 500kg payload to the lunar surface, provides a platform for bringing technologies from the laboratory into an integrated flight system at relatively low cost. In 2012, Morpheus began integrating the Autonomous Landing and Hazard Avoidance Technology (ALHAT) sensors and software onto the vehicle in order to demonstrate safe, autonomous landing and hazard avoidance. From the beginning, one of goals for the Morpheus Project was to streamline agency processes and practices. The Morpheus project accepted a challenge to tailor the traditional NASA systems engineering approach in a way that would be appropriate for a lower cost, rapid prototype engineering effort, but retain the essence of the guiding principles. This paper describes the tailored project life cycle and systems engineering approach for the Morpheus project, including the processes, tools, and amount of rigor employed over the project's multiple lifecycles since the project began in fiscal year (FY) 2011.

Devolites, Jennifer L.↗
NASA NTRS2014

2014 SRP Integration Transcript

HRP's mission is to reduce the risks to human health and performance during long-duration spaceflight. The HRP Integrated Research Plan (IRP) contains the research plans for the 32 risks that require research to characterize and mitigate. From its inception the "integrate" aspect of the IRP has denoted the integrated nature of risks to human health and performance. Even though each risk in the IRP has its own research plan and is tracked separately, the interrelated nature of health and performance requires that they be addressed in an integrative or holistic fashion so that the connectedness of physiological systems within the human body and the integrated response to spaceflight can be addressed. Common characteristics of the spaceflight environment include altered gravity, atmospheres, and light/dark cycles; space radiation; isolation; noise; and periods of high or low workload. Long-term exposure to this unique environment produces a suite of physiological effects such as stress; vision, neurocognitive, and anthropometric changes; circadian misalignment; fluid shifts; cardiovascular deconditioning; immune dysregulation; and altered nutritional requirements. Expanding cross-disciplinary integrative approaches that synthesize concepts or data from two or more disciplines would improve the identification and characterization risk factors, and enable the development of countermeasures relevant to multiple risks. Cross-disciplinary approaches might also help to illuminate problem areas that may arise when a countermeasure adversely impacts risks other than those which it was developed to mitigate, or to identify groupings of physiological changes that are likely to occur that may impact the overall risk posture. In 2014 HRP embarked on a pilot study that combined four SRPs (and 12 HRP risks) - Behavioral Health, Sensorimotor, Cardiovascular, and Bone/Muscle - specifically to discuss cross-disciplinary integration. The points outlined below were suggested to seed the discussion, within the bounding constraint that research plans must be feasible and relevant to the HRP mission. While these were suggested starting points, the overall guiding principle was to allow free discussion from panel members on any aspect of integrated research that they felt was important, Existing cross-disciplinary integration as documented in the IRP (HRR), Existing or needed integration already identified by HRP, but not yet well defined within the IRP, Areas of integration that are missing.

Steinberg, Susan↗
NASA NTRS2015

Research Methods Tutorial

A guiding principle for conducting research in technology, science, and engineering, leading to innovation is based on our use of research methodology (both qualitative and qualitative). A brief review of research methodology will be presented with an overview of NASA process in developing aeronautics technologies and other things to consider in research including what is innovation.

Research↗
NASA NTRS2015

Research Methods Tutorial

A guiding principle for conducting research in technology, science, and engineering, leading to innovation is based on our use of research methodology (both qualitative and quantitative). A brief review of research methodology will be presented with an overview of NASA process in developing aeronautics technologies and other things to consider in research including what is innovation.

methodology↗
NASA NTRS2016

STAT Overview and SCENIC Functional Concept

This is an overview of the guiding principles of STAT derivation from back in early 2012. This includes a functional view of STAT operations, a STAT demonstration, as well as how the STAT functional view is an excellent model, in my perspective, how the necessary functional view for the SCENIC Analysis Tool.

space communications↗
NASA NTRS2018

Flaring Activity from Quiescent States in Neutron-Star X-Ray Binaries

We examine systematically the observed X-ray luminosity jumps (or flares) from quiescent states in millisecond binary pulsars (MSBPs) and high-mass X-ray binary pulsars (HMXBPs). We rely on the published X-ray light curves of seven pulsars: four HMXBPs, two MSBPs and the ultraluminous X-ray pulsar M82 X-2. We discuss the physics of their flaring activities or lack thereof, paying special attention to their emission properties when they are found on the propeller line, inside the Corbet gap or near the light-cylinder barrier.We provide guiding principles for future interpretations of faint X-ray observations, as well as a method of constraining the propeller lines and the dipolar surfacemagnetic fields of pulsars using a variety of quiescent states. In the process, we clarify some disturbing inaccuracies that have made their way into the published literature.

Christodoulou, Dimitris M.↗
NASA NTRS2020

Operations Concept for Responding to Urgent Requests for NASA-ISRO Synthetic Aperture Radar (NISAR)

The NASA-ISRO Synthetic Aperture Radar, or NISAR, mission is an Earth-mapping radar observatory to be launched from Sriharikota (India) in 2022. This mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organization (ISRO). This spacecraft will carry two instruments that will operate at radar wavelengths (L and Sband) and will provide data for understanding changes in the Earth’s land surface. The scientific data from this mission will revolutionize our understanding of the causes and consequences of land surface changes on Earth, ranging from Solid Earth Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice). A nominal Reference Observation Plan, that repeats roughly every 12-24 days, developed prior to launch by the NISAR Mission Planning team, in consultation with the Science Team, will form the basis of science data collection by the payload instruments onboard the NISAR observatory after launch. Scheduling of science observations for the mission requires accounting for limited spacecraft resources like onboard data storage, downlink capacity, energy/power, thermal limits and instrument duty cycles. In addition to nominal science data collection, the project has a Level 1 requirement to respond to requests for urgent data acquisition over disaster sites (natural or anthropogenic) by scheduling new acquisitions within 24 hrs of notification and delivering science data within 5 hours of data acquisition. This capability is to be exercised on a ‘best-efforts basis’. While the definition of what constitutes an ‘urgent request’, and how such requests would be submitted to the project, is within the domain of the Science Team, the Mission System team is responsible for developing the baseline operations concept and implementation approach for responding to such requests. Given the ‘best-efforts’ nature of this requirement, a few highlevel guidelines have been developed to help guide the formulation of the operations concept, and are presented in this paper. Requests for urgent response data will be accommodated following the guiding principle of minimal to no impact on nominal science and planned engineering activities. No change in satellite orbit or attitude will be made for urgent response. Restricting response approaches to only changing the downlink and/or ground processing priority for existing observations, and adding new observations only in areas where NISAR will not be nominally imaging, allows for minimal impact on the Reference science Observation Plan. No instrument mode changes will be allowed for urgent response (except for high-priority requests), and no new observations that impact either planned science or engineering activities will be scheduled. Additionally, data requests must fit within the available project resource margins (both spacecraft and ground resources are to be evaluated). Both JPL and ISRO will be involved at various steps of the implementation, irrespective of whether the urgent request is for L-SAR (NASA instrument) or S-SAR (ISRO instrument) or a joint dataset.

Sharma, Priyanka↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗
NASA NTRS2021

FRESCO: A Framework for Spacecraft Systems Autonomy

Achieving the science exploration and defense goals of the following decades will require flight systems capable of operations with limited operator contact, system mode changes and retasking based on sensor data, and complex robotic operations. To support these capabilities, increasingly autonomous flight systems are required that can perform dedicated mission functions, e.g. payload targeting and communications, and system-level functions, e.g. planning and goal monitoring. Architecting an autonomous system requires a well-reasoned, self-consistent framework to avoid \textit{ad hoc} design choices that will introduce complexity and risk. The Framework for Robust Execution and Scheduling of Commands On-Board, FRESCO, is the result of lessons learned in developing a software architecture to enable autonomous solar system exploration. FRESCO generalizes this work to offer a modular, software-agnostic approach to developing verifiable architecture for autonomous space systems. FRESCO specifies guiding principles, functions, interfaces, and interactions from which mission-specific autonomous control architectures can be derived. FRESCO is a principled framework relying on explicit, state-based goal definitions, centralized management of state knowledge, clearly separated control boundaries, and hierarchical reasoning. Using components from FRESCO reference architecture, an autonomous decision-making architecture can be designed for spacecraft which can then be mapped to flight software architecture. FRESCO is flexibly defined to enable autonomous control of flight systems built using extensive software and hardware heritage. Finally, FRESCO-derived architectures support a spectrum of operator/spacecraft interactions, ranging from traditional commanding to goal-driven commanding with the ability to change mission goals autonomously. FRESCO has been used in defining the autonomy architectures for the ASTERIA mission and have been demonstrated in laboratory and software simulation for small body rendezvous and in-space servicing missions.

Kolcio, Ksenia↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗
NASA NTRSDate not supplied

Open Science at the Onset of JWST

The characterization of a diverse set of atmospheres, ranging from brown dwarfs to hot gas giants to small temperate rocky worlds will be part of the legacy of JWST and future NASA missions. These technological innovations will enable a plethora of discoveries, unveiling a variety of new chemical and physical regimes that could even point to the first detection of life beyond Earth. However, our ability to fully interpret these results will hinge on how well we can link observations to numerous complex theoretical models that describe, for example, the chemistry and climate. An immediate demonstration of this was executed in the analysis of JWST’s very first exoplanet spectrum. An open collaboration of more than 300 students, postdocs, faculty, and researchers worldwide worked together to analyze the exquisite dataset. The result was the first identification of carbon dioxide in a planet beyond our own Solar System. I will discuss how NASA’s open science guiding principles are centered in our Early Release Science team, supporting an inclusive, transparent, and collaborative scientific process. And ultimately, I will showcase the science that was born from this open process.

Natasha Batalha↗