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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Impact-Identified Medical Capabilities with Largest Effect on Medical Risk for an Extended Duration Artemis Mission

Historically, identifying resources to include in a medical system has been based on heuristically guided clinical subject matter expert assessment. Probabilistic risk assessment (PRA) and tradespace analysis have the power to simplify and increase the fidelity of this traditional approach by providing initial risk estimates and system design solutions that fit within the specified constraints. This will be especially important as the increased mission complexity, distance from Earth, and duration of LDEMs is likely to drive an increase in mission medical risk. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) is designed to do just that. IMPACT uses an evidence based medical database of conditions likely to affect LDEM outcomes and a PRA computational engine to estimate how medical conditions and included medical capabilities affect mission outcomes. We identified the 10 medical conditions with the largest effect on medical risks and determined what medical system capabilities affected risk reduction the greatest.

Anderson A↗
NASA NTRS1999

Reinventing The Design Process: Teams and Models

The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues. Now and in the future, costs are capped and schedules fixed-these two variables must be treated as independent in the design process. Accordingly, JPL has redesigned its design process. At the conceptual level, design times have been reduced by properly defining the required design depth, improving the linkages between tools, and managing team dynamics. In implementation-phase design, system requirements will be held in crosscutting models, linked to subsystem design tools through a central database that captures the design and supplies needed configuration management and control. Mission goals will then be captured in timelining software that drives the models, testing their capability to execute the goals. Metrics are used to measure and control both processes and to ensure that design parameters converge through the design process within schedule constraints. This methodology manages margins controlled by acceptable risk levels. Thus, teams can evolve risk tolerance (and cost) as they would any engineering parameter. This new approach allows more design freedom for a longer time, which tends to encourage revolutionary and unexpected improvements in design.

Wall, Stephen D.↗
NASA NTRS2014

OCCAMS: Optically Controlled and Corrected Active Meta-Material Space Structures

Telescopes require sub-wavelength figure (shape) error in order to achieve acceptable Strehl ratios. Traditional methods of achieving this require rigid and therefore heavy mirrors and reaction structures as well as proportionally heavy and expensive spacecraft busses and launch vehicles. This effectively limits the diameter and therefore resolution and collecting area of space optics. Large diameter telescopes must either be heavy or actively controlled. Space telescopes of the size proposed for missions such as TPF (Terrestrial Planet Finder), TPI (Terrestrial Planet Imager), etc. will likely require large active primaries and structures and corrective optics to implement downstream wavefront control. We propose a novel viable enabling technology. High resolution space imaging requires the production of lightweight large aperture optics subject to design tradespace constraints based on nanometer physical tolerances, low system aerial density, high control authority, suitable thermal and mechanical properties, deployment capability, launch vehicle volume constraints, as well as production cost and schedule risk mitigation. Segmented systems impose additional requirements on segment alignment, wavefront phasing, and telescope mass with increased edge diffraction. Photons weigh nothing. Why must even small space telescopes "weigh" tons? Our team is working to demonstrate that they do not, by leveraging 15 years of effort and a novel advanced concept.The ultimate research goal is to refine technology to produce a mission capable ultra-lightweight membrane optic whose shape can be remotely controlled using a laser beam. Using our novel optically-controlled molecular actuators allows substitution of optically-induced control for rigidity and mirror mass. In analogy with noise-canceling headphones, this technique also potentially provides a way to excite vibratory modes to couple with and damp out normal modes of oscillation induced by slewing, other motion and thermal changes, thus allowing a robust response to repointing of a large aperture.

Astronomy↗
NASA NTRS2020

Artemis Sustained Translational Acceleration Limits: Human Tolerance Evidence from Apollo to ISS

The designers of the next generation of lunar landers may adopt novel, crew-body orientations outside of our flight history or applied to flight durations and environments outside of our experience. Current sustained translational acceleration requirements in NASA-STD-3001 are applicable only to crewmembers in a seated posture and are thus inadequate to address human tolerance in non-seated configurations. Initial designs for the Apollo Lunar Module (LM) included seats for both commander and pilot; however, these were subsequently removed from the vehicle due to mass constraints and a willingness to accept the unknown risks for short-duration missions given the limited human physiologic data at the time. In the years since Apollo, our evidence base has grown immensely. Initial Artemis mission timelines under consideration will be longer than the longest Apollo mission, by a significant margin, with timeframes more analogous to longer Space Shuttle missions. Given the incidence of postflight orthostatic intolerance following shuttle missions, a significant risk may exist for lander design(s) pursuing a standing crew configuration similar to Apollo LM. New sustained translational acceleration limits developed to address this risk are presented herein. These limits were derived from evaluations of Apollo biomedical and flight profile data during lunar descent and ascent operations, Soyuz and Space Shuttle flight profile and post-landing biomedical data, and analogue bed rest post-exposure data on orthostatic intolerance.

James M. Pattarini↗
NASA NTRS2022

Adaptive IV&V for Increasingly Complex Software Systems

As NASA software systems continue to innovate, becoming more complex and nondeterministic, the need for the NASA IV&V Program to become systemically adaptive to ensure mission success is paramount. To ensure adaptability within resource constraints, IV&V has developed an agile, risk-based approach to identify, characterize, scope, focus, and prioritize mission assurance activities. This risk based adaptive framework has been applied to trends such as increased reliance on data driven algorithms for safety and mission critical software behavior, use of MBSE in system design, and application of agile principles to embedded software development. The framework is enabled by continuous innovation of new approaches such as software only test beds, assurance design tools, and initiatives that augment IV&V assurance methods with artificial intelligence and machine learning techniques. This presentation will highlight the trends the NASA IV&V Program is seeing, the innovative steps it is taking to address those challenges, and how it is postured to address evolving risk and constantly changing and new technologies.

Wesley W Deadrick↗
DOE OSTI2024

Gains in operational flexibility, safety margins, and cost efficiencies via integrated Plant Reload Optimization platform

The U.S. Department of Energy Light Water Reactor Sustainability Program Risk-Informed Systems Analysis Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimizing core design. Optimizing the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible core configuration options, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization platform, which supports artificial-intelligence-based reactor core designing, is now fully capable of handling realistic problems. The Plant ReLoad Optimization platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual ENvironment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multiobjective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Pressurized-Water Reactor Core Design using Multi-Objective Plant Fuel Reload Optimization Platform

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Risk-Informed Systems Analysis (RISA) Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimization of core design. The optimization of the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible options of core configuration, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization (PRLO) platform which supports artificial-intelligence-based reactor core designing is now fully capable of handling realistic problems. The PRLO Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual Environment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multi-objective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

42 ENGINEERING↗
NASA NTRS2017

Modeling Meteor Flares for Spacecraft Safety

NASA's Meteoroid Environment Office (MEO) is tasked with assisting spacecraft operators and engineers in quantifying the threat the meteoroid environment poses to their individual missions. A more complete understanding of the meteoroid environment for this application requires extensive observations. One manner by which the MEO observes meteors is with dedicated video camera systems that operate nightly. Connecting the observational data from these video cameras to the relevant physical properties of the ablating meteoroids, however, is subject to sizable observational and theoretical uncertainties. Arguably the most troublesome theoretical uncertainty in ablation is a model for the structure of meteoroids, as observations clearly show behaviors wholly inconsistent with meteoroids being homogeneous spheres. Further complicating the interpretation of the observations in the context of spacecraft risk is the ubiquitous process of fragmentation and the flares it can produce, which greatly muddles any attempts to estimating initial meteoroid masses. In this talk a method of estimating the mass distribution of fragments in flaring meteors using high resolution video observations will be dis- cussed. Such measurements provide an important step in better understanding of the structure and fragmentation process of the parent meteoroids producing these flares, which in turn may lead to better constraints on meteoroid masses and reduced uncertainties in spacecraft risk.

Ehlert, Steven↗
NASA NTRS2010

Full Mission Astronaut Radiation Exposure Assessments for Long Duration Lunar Surface Missions

Risk to astronauts due to ionizing radiation exposure is a primary concern for missions beyond Low Earth Orbit (LEO) and will drive mission architecture requirements, mission timelines, and operational practices. Both galactic cosmic ray (GCR) and solar particle event (SPE) environments pose a risk to astronauts for missions beyond LEO. The GCR environment, which is made up of protons and heavier ions covering a broad energy spectrum, is ever present but varies in intensity with the solar cycle, while SPEs are sporadic events, consisting primarily of protons moving outward through the solar system from the sun. The GCR environment is more penetrating and is more difficult to shield than SPE environments, but lacks the intensity to induce acute effects. Large SPEs are rare, but they could result in a lethal dose, if adequate shielding is not provided. For short missions, radiation risk is dominated by the possibility of a large SPE. Longer missions also require planning for large SPEs; adequate shielding must be provided and operational constraints must allow astronauts to move quickly to shielded locations. The dominant risk for longer missions, however, is GCR exposure, which accumulates over time and can lead to late effects such as cancer. SPE exposure, even low level SPE exposure received in heavily shielded locations, will increase this risk. In addition to GCR and SPE environments, the lunar neutron albedo resulting mainly from the interaction of GCRs with regolith will also contribute to astronaut risk. Full mission exposure assessments were performed for proposed long duration lunar surface mission scenarios. In order to accomplish these assessments, radiation shielding models were developed for a proposed lunar habitat and rover. End-to-End mission exposure assessments were performed by first calculating exposure rates for locations in the habitat, rover, and during extra-vehicular activities (EVA). Subsequently, total mission exposures were evaluated for proposed timelines. A number of computational tools and mathematical models, which have been incorporated into NASA's On-Line Tool for the Assessment of Radiation In Space (OLTARIS), were used for this study. These tools include GCR and SPE environment models, human body models, and the HZETRN space radiation transport code, which is used to calculate the transport of the charged particles and neutrons through shielding materials and human tissue. Mission exposure results, assessed in terms of effective dose, are presented for proposed timelines and recommendations are made for improved astronaut shielding and safer operational practice.

Adamczyk, Anne M.↗
DOE OSTI2022

Stochastic scheduling of generating units with weekly energy storage: A hybrid decomposition approach

We propose a solution method for the large-scale stochastic unit commitment (SUC) problem with weekly-dispatched energy storage and significant weather-dependent stochastic generating capacity. Weekly storage facilities that mostly charge during weekends and discharge during weekdays require a weekly scheduling of generating units, which result in a large-scale optimization problem. This SUC problem is formulated as a two-stage stochastic model and we use the conditional value-at-risk as a risk measure. Using a Benders framework, the proposed solution method decomposes the problem into a mixed-integer linear master problem and linear and continuous subproblems. The master problem corresponds to the first-stage decisions throughout the week and includes all the commitment (binary) variables and their corresponding constraints. The subproblems correspond to the actual dispatch of the generating units on a weekly basis. Based on the success of column-and-constraint generation algorithms to solve robust optimization problems, we improve the low communication between the master problem and the subproblems in the standard Benders decomposition by adding primal variables and constraints from the subproblems to the master problem, which provides a better approximation of the recourse function. Furthermore, our computational experiments demonstrate the effectiveness of the proposed decomposition method using an instance of the South Carolina synthetic system with 90 generating units under 40 scenarios.

25 ENERGY STORAGE↗
NASA NTRS2010

Testing to Transition the J-2X from Paper to Hardware

The J-2X Upper Stage Engine (USE) will be the first new human-rated upper stage engine since the Apollo program of the 1960s. It is designed to carry the Ares I and Ares V into orbit and send the Ares V to the Moon as part of NASA's Constellation Program. This paper will provide an overview of progress on the design, testing, and manufacturing of this new engine in 2009 and 2010. The J-2X embodies the program goals of basing the design on proven technology and experience and seeking commonality between the Ares vehicles as a way to minimize risk, shorten development times, and live within current budget constraints. It is based on the proven J-2 engine used on the Saturn IB and Saturn V launch vehicles. The prime contractor for the J-2X is Pratt & Whitney Rocketdyne (PWR), which is under a design, development, test, and engineering (DDT&E) contract covering the period from June 2006 through September 2014. For Ares I, the J-2X will provide engine start at approximately 190,000 feet, operate roughly 500 seconds, and shut down. For Ares V, the J-2X will start at roughly 190,000 feet to place the Earth departure stage (EDS) in orbit, shut down and loiter for up to five days, re-start on command and operate for roughly 300 seconds at its secondary power level to perform trans lunar injection (TLI), followed by final engine shutdown. The J-2X development effort focuses on four key areas: early risk mitigation, design risk mitigation, component and subassembly testing, and engine system testing. Following that plan, the J-2X successfully completed its critical design review (CDR) in 2008, and it has made significant progress in 2009 and 2010 in moving from the drawing board to the machine shop and test stand. Post-CDR manufacturing is well under way, including PWR in-house and vendor hardware. In addition, a wide range of component and sub-component tests have been completed, and more component tests are planned. Testing includes heritage powerpack, turbopump inducer water flow, turbine air flow, turbopump seal testing, main injector and gas generator, injector testing, augmented spark igniter testing, nozzle side loads cold flow testing, nozzle extension film cooling flow testing, control system testing with hardware in the loop, and nozzle extension emissivity coating tests. In parallel with hardware manufacturing, work is progressing on the new A-3 test stand to support full duration altitude testing. The Stennis A-2 test stand is scheduled to be turned over to the Constellation Program in September 2010 to be modified for J-2X testing also. As the structural steel was rising on the A-3 stand, work was under way in the nearby E complex on the chemical steam generator and subscale diffuser concepts to be used to evacuate the A-3 test cell and simulate altitude conditions.

Byrd, Tom↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗
NASA NTRSDate not supplied

CHP-PRA: Sensorimotor Countermeasures Proof of Concept

The capabilities included in Crew Health and Performance (CHP) systems are designed to keep the crew healthy, happy, and productive. In doing so, the CHP system allows reductions in human related risks to be realized. All human missions, though particularly future Artemis and Mars missions, have constraints on the mass and volume allocated to the CHP system. Thus, trades must be made on how to best buy down risk while still meeting other requirements. Understanding how different CHP capabilities influence medical, performance, and long-term health risks is key to making informed choices among these trades. To address this, an integrated CHP Probabilistic Risk Assessment (PRA) model is being developed. Much like how IMPACT is designed to allow medical resource trades informed by medical risks, CHP PRA will enable analogous trades in human system risks across all CHP functions and capabilities. There are 29 Human System Risk Board (HSRB) risk areas to consider for model implementation. This effort focused solely on the implementation of countermeasures associated with sensorimotor risk. The framework and lessons learned from this proof of concept will benefit the implementation of other risks and countermeasures. Astronauts experience sensorimotor changes when entering or exiting a microgravity environment. While most sensorimotor issues are resolved within a few days, they pose a serious risk to crew health and performance during the adaptation period. This adaptation period aligns with gravity transitions and key mission phases where the crew members may be required to complete challenging tasks ideally with an undisturbed sensorimotor system. Countermeasures such as training or pharmaceuticals can be used to mitigate risk. This effort began by identifying physiological changes to the sensorimotor system that could lead to functional performance decrements or medical conditions and potential countermeasures, so that the overall effect of sensorimotor disturbance on human risk could be captured. We then selected example countermeasures, mapped relationships between countermeasures and outcomes, and used results from existing sensorimotor investigations to define the relationship between a sensorimotor countermeasure and subsequent performance of a sensorimotor-affected task. Specifically, using shuttle landing performance data, we compared the use or absence of inflight training capabilities to yield a relative performance change that can be applied to the prediction of the risk associated with manual control performance in future missions, as depicted in the figure. This sensorimotor proof of concept demonstrates how HRP research information can be transformed into quantifiable relationships to describe changes in HSRB medical and performance risks.

Caroline R Austin↗
NASA NTRS2015

Integrated Medical Model Project - Overview and Summary of Historical Application

Introduction: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project. Methods: Figure 1 [see document] illustrates the IMM modeling system and scenario process. As illustrated, the IMM computational architecture is based on Probabilistic Risk Assessment techniques. Nineteen assumptions and limitations define the IMM application domain. Scenario definitions include crew medical attributes and mission specific details. The IMM forecasts probabilities of loss of crew life (LOCL), evacuation (EVAC), quality time lost during the mission, number of medical resources utilized and the number and type of medical events by combining scenario information with in-flight, analog, and terrestrial medical information stored in the iMED. In addition, the metrics provide the integrated information necessary to estimate optimized in-flight medical kit contents under constraints of mass and volume or acceptable level of mission risk. Results and Conclusions: Historically, IMM simulations support Science and Technology planning, Exploration mission planning, and ISS program operations by supplying simulation support, iMED data information, and subject matter expertise to Crew Health and Safety and the HRP. Upcoming release of IMM version 4.0 seeks to provide enhanced functionality to increase the quality of risk decisions made using the IMM through a more accurate representation of the real world system.

Myers, J.↗
NASA NTRS2010

The J-2X Upper Stage Engine: From Design to Hardware

NASA is well on its way toward developing a new generation of launch vehicles to support of national space policy to retire the Space Shuttle fleet, complete the International Space Station, and return to the Moon as the first step in resuming this nation s exploration of deep space. The Constellation Program is developing the launch vehicles, spacecraft, surface systems, and ground systems to support those plans. Two launch vehicles will support those ambitious plans the Ares I and Ares V. (Figure 1) The J-2X Upper Stage Engine is a critical element of both of these new launchers. This paper will provide an overview of the J-2X design background, progress to date in design, testing, and manufacturing. The Ares I crew launch vehicle will lift the Orion crew exploration vehicle and up to four astronauts into low Earth orbit (LEO) to rendezvous with the space station or the first leg of mission to the Moon. The Ares V cargo launch vehicle is designed to lift a lunar lander into Earth orbit where it will be docked with the Orion spacecraft, and provide the thrust for the trans-lunar journey. While these vehicles bear some visual resemblance to the 1960s-era Saturn vehicles that carried astronauts to the Moon, the Ares vehicles are designed to carry more crew and more cargo to more places to carry out more ambitious tasks than the vehicles they succeed. The government/industry team designing the Ares rockets is mining a rich history of technology and expertise from the Shuttle, Saturn and other programs and seeking commonality where feasible between the Ares crew and cargo rockets as a way to minimize risk, shorten development times, and live within the budget constraints of its original guidance.

Byrd, Thomas↗
NASA NTRS1996

Cassini tour cost reductions

The original design of the Cassini tour violated the cost constraint for the mission operations and data analysis by more than 30 percent. This challenge was addressed by performing tradeoffs in order to establish a modified risk and performance posture for the operations organization. This new posture accepted more data acquisition risk with minimal impact to the mission objectives, and brought the operation costs to within the program's constraints. The methodology employed within the Cassini program in order to address the tour cost, risk and performance parameters is presented.

Duxbury, J. H.↗
DOE OSTI2020

Power Plant Water Risk and Adaptive Measures Database

Project objective was to understand water-related constraints affecting conventional powerplant operations, specifically coal-fired power plants. Of concern were threats related to drought and flood affecting both water supply and ability of plant to discharge wastewater. Also of interest were adaptive measures taken to mitigate identified threats. This spreadsheet contains the responses provided by the power plant operators and owners. Data have been "sanitized" (e.g., random plant ID, binned location and generation capacity information) to ensure anonymity of individual power plants.

Adaptive Measures↗
NASA NTRS2015

Big Software for SmallSats: Adapting CFS to CubeSat Missions

Expanding capabilities and mission objectives for SmallSats and CubeSats is driving the need for reliable, reusable, and robust flight software. While missions are becoming more complicated and the scientific goals more ambitious, the level of acceptable risk has decreased. Design challenges are further compounded by budget and schedule constraints that have not kept pace. NASA's Core Flight Software System (cFS) is an open source solution which enables teams to build flagship satellite level flight software within a CubeSat schedule and budget. NASA originally developed cFS to reduce mission and schedule risk for flagship satellite missions by increasing code reuse and reliability. The Lunar Reconnaissance Orbiter, which launched in 2009, was the first of a growing list of Class B rated missions to use cFS. Large parts of cFS are now open source, which has spurred adoption outside of NASA. This paper reports on the experiences of two teams using cFS for current CubeSat missions. The performance overheads of cFS are quantified, and the reusability of code between missions is discussed. The analysis shows that cFS is well suited to use on CubeSats and demonstrates the portability and modularity of cFS code.

Open Source↗