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NASA NTRS2008

The Ares I Crew Launch Vehicle: Human Space Access for the Moon and Beyond

The National Aeronautics and Space Administration (NASA)'s Constellation Program is depending on the Ares Projects to deliver the crew launch capabilities needed to send human explorers to the Moon and beyond. The Ares Projects continue to make progress toward design, component testing, and early flight testing of the Ares I crew launch vehicle (Figure 1), the United States first new human-rated launch vehicle in over 25 years. Ares I will provide the core space launch capabilities the United States needs to continue providing crew and cargo access to the International Space Station (ISS), maintaining the U.S. pioneering tradition as a spacefaring nation, and enabling cooperative international ventures to the Moon and beyond. This paper will discuss programmatic, design, fabrication, and testing progress toward building this new launch vehicle.

Cook, Stephen A.↗

NASA NTRSDate not supplied

Strategy for Risk Quantification of Spaceflight Crew Health and Performance Using Dynamic Probabilistic Risk Assessment

At NASA, the Crew Health and Performance (CHP) system represents the span of countermeasures, capabilities, interventions, and tested processes and procedures that in combination work to mitigate the human component of spaceflight mission risk. Across the varying NASA mental models of the CHP system, the different functionalities needed to meet human flight systems standards can be broken down into specific categories (i.e. medical capability, environmental health, behavioral health). These categories can be further broken down into specific subgroups generally associated with the CHP functionalities meant to mitigate or buy down individual human system risks. Taking a similar development approach we seek to leverage dynamic probabilistic risk assessment as a means to quantify and relatively assess the human risk state within the crew health and performance domain. By utilizing existing tools as integrators, we propose a rapid development strategy for incorporating research and operational data that represent the influence of the CHP system functionalities, in order to provide order of magnitudes estimates of the influence on most human system risks outcomes. The model system utilizes a modest cumulative risk approach and that limits the scope to primary paths of influence between the CHP functionalities and human system risks, thus enabling quick prototypes of the integrative effects of CHP functional combinations to solicit valuable feedback from stakeholders and customers on the data, relationship, and structure of the integration.

Drayton Munster↗

NASA NTRSDate not supplied

Asymmetric Flow State Switching on the Space Launch System (SLS) Block 2 Crew Vehicle

An in-depth investigation was conducted at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel to evaluate flow state switching in the liftoff flow environment of the Space Launch System Block 2 Crew launch vehicle using side force measurements, two-component particle image velocimetry, and tufts flow visualization. Multimodal flow states were observed in the gap flow between the centerbody and solid rocket boosters at a range of incoming flow angles and were characterized for the relative strength of state switches. When flow switches occur, the flow is predominantly bimodal, but trimodal flow states are observed with the launch tower downstream of the vehicle. Tufts visualization indicates three-dimensionality during flow state switching, which initiates at one part of the gap and quickly transitions throughout the length of the booster. Due to the long time scales between switches, statistics such as frequency of flow state switches and converged state probabilities cannot be established without significantly increased acquisition times.

Lee J. Mears↗

NASA NTRSDate not supplied

Development of A Crew Health and Performance System Probabilistic Risk Assessment Tool: Proof-of-Concept Approach

The crew health and performance (CHP) system represents the span of technological interventions and tested processes and procedures that in combination address the human risk to space flight. The Human Research Program (HRP) mental model of the CHP system breaks the capabilities needed to meet NASA human flight systems standards into specific categories (i.e., countermeasures, behavioral health, medical intervention). These categories are further broken down into specific sub-groups generally associated with the human system risks that these capabilities seek to mitigate. Like the approach used to develop the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Analysis Tool (MEDPRAT), HRP tasked NASA GRC’s Cross-Cutting Computational Modeling Project with developing a CHP probabilistic risk assessment tool, the CHP-PRA. The CHP-PRA model seeks to quantify and relatively assess the human risk state within the crew health and performance domain, using a combination of knowledge about human system risks and technology and practices likely to be applied during space flight missions. This modeling system will incorporate customer and stakeholder feedback and be flexible enough to address multiple different questions about important low-level mission-specific parameters. This presentation will introduce the initial concept and development timeline for this tool and demonstrate proof-of-concept through an application addressing a specific human risk question posed within the Artemis program.

Risk analysis↗

NASA NTRS2020

Medics: Medical Decision Support System for Long-Duration Space Exploration

The Autonomous Medical Operations (AMO) group at NASA Ames is developing a “medical decision support system” to enable astronauts on long-duration exploration missions to operate autonomously. The system will support clinical actions by providing medical interpretation advice and procedural recommendations during emergent care and clinical work performed by crew. The current state of development of the system, called MedICS (Medical Interpretation Classification and Segmentation) includes two separate aspects: a set of machine learning diagnostic models trained to analyze organ images and patient health records, and an interface to ultrasound diagnostic hardware and to medical repositories. Three sets of images of different organs and medical records were utilized for training machine learning models for various analyses, as follows: 1. Pneumothorax condition (collapsed lung). The trained model provides a positive or negative diagnosis of the condition. 2. Carotid artery occlusion. The trained model produces a diagnosis of 5 different occlusion levels (including “normal”). 3. Ocular retinal images. The model extracts optic disc pixels (image segmentation). This is a precursor step for advanced autonomous fundus clinical evaluation algorithms to be implemented in FY20. 4. Medical health records. The model produces a differential diagnosis for any particular individual, based on symptoms and other health and demographic information. A probability is calculated for each of 25 most common conditions. The same model provides the likelihood of survival. All results are provided with a confidence level. Item 1 images were provided by the US Army and were part of a data set for the clinical treatment of injured battlefield soldiers. This condition is relevant to possible space mishaps, due to pressure management issues. Item 2 images were provided by Houston Methodist Hospital, and item 3 health records were acquired from the MIT laboratory of computational physiology. The machine learning technology utilized is deep multilayer networks (Deep Learning), and new models will continue to be produced, as relevant data is made available and specific health needs of astronaut crews are identified. The interfacing aspects of the system include a GUI for running the different models, and retrieving and storing data, as well as support for integration with an augmented reality (AR) system deployed at JSC by Tietronix Software Inc. (HoloLens). The AR system provides guidance for the placement of an ultrasound transducer that captures images to be sent to the MedICS system for diagnosis. The image captured and the associated diagnosis appear in the technician’s AR visual display.

Colombano, Silvano↗

NASA NTRS1978

Formulation of consumables management models. Volume 2: Mission planning processor user guide

A user guide for the MPP (Mission Planning Processor) is presented. The MPP is used in the evaluation of particular missions, with appropriate display and storage of related consumables data. Design goals are accomplished by the use of an on-line/demand mode computer terminal Cathode Ray Tube Display. The process is such that the user merely adds specific mission/flight functions to a skeleton flight and/or alters the skeleton. The skeleton flight includes operational aspects from prelaunch through ground support equipment connect after rollout as required to place the STS (Space Transportation System) in a parking orbit, maintain the spacecraft and crew for the stated on-orbit period and return.

Daly, J. K.↗

NASA NTRS2009

NASA Space Life Sciences

This slide presentation reviews the requirements that NASA has for the medical service of a crew returning to earth after long duration space flight. The scenarios predicate a water landing. Two scenarios are reviewed that outline the ship-board medical operations team and the ship board science reseach team. A schedule for the each crew upon landing is posited for each of scenarios. The requirement for a heliport on board the ship is reviewed and is on the requirement for a helicopter to return the Astronauts to the Baseline Data Collection Facility (BDCF). The ideal is to integrate the medical and science requirements, to minimize the risks and Inconveniences to the returning astronauts. The medical support that is required for all astronauts returning from long duration space flight (30 days or more) is reviewed. The personnel required to support the team is outlined. The recommendations for medical operations and science research for crew support are stated.

Hayes, Judith↗

NASA NTRS2018

Payload Operations Center - Lessons from Commercial Engagement

The International Space Station (ISS) Payload Operations and Integration Center (POIC) at NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama, United States, has gone through an evolution from supporting exclusively government ISS users to providing 50% (or more) of their support to commercial users. At the same time, they have expanded ground and facility operations to support a United States Orbital Segment crew expansion from three to four astronauts allowing an additional of 34 hours crew time per week. These additional hours are dedicated to utilization and have already surpassed the 100 hour peak weekly milestone in July 2018. This paper discusses the Center's changes in planning, staffing, coordination, and operations while addressing topics from the addition of secondary flight control positions to dynamic operations product reviews. MSFC's Human Exploration and Development Operations Office, which manages payload operations, seeks through this paper to highlight the higher priority commercial users now receive in replanning and in additional crew time.

Watkins, Bobby J.↗

NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗

NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

Robert C. Dempsey↗

NASA NTRSDate not supplied

Overview of the NASA Terrestrial Environments Support Role: Data and Applications

This presentation focuses on the terrestrial environment component of the Natural Environments Branch’s (NEB’s) support role and highlights the instrumentation and data sources used, how the data are quality controlled and archived, and the analyses and use-cases of these datasets. A detailed overview is provided about some individual data sources that are used by the branch, which includes a network of instruments (e.g., wind towers, balloons, and profilers) and models, such as the Earth Global Reference Atmospheric Model (Earth-GRAM). Additionally, the data archival and quality control processes that maintain the high-quality climatological datasets from these sources are discussed, as are the implemented and pending updates to this process. Examples of the different applications for these datasets are presented to showcase the analytical and operational capabilities of the NEB and demonstrate the culmination of the entire process. This includes the Range Reference Atmospheres created and maintained by the NEB, sea-state analyses for crewed return, certification of observation systems for space flight, and the day-of-launch support process. The NEB at NASA Marshall Space Flight Center (MSFC) supports the NASA Engineering Directorate (ED) and Exploration Systems Development Mission Directorate (ESDMD) by providing the necessary environmental constraints to facilitate the safe design and operation of assets required for space travel. This includes, but is not limited to, the environmental considerations for assets residing at the launch sites, temporarily stationed at a launch site, traversing the [extra-]terrestrial atmosphere and open space, and arriving at their destination. As such, the Terrestrial and Planetary Environments Team within the NEB is but a part of the whole, delegated to quantify the environment that assets may encounter whilst on Earth and within its atmosphere. However, nearly all ESDMD assets are subjected to terrestrial conditions, which cover a diverse range of meteorological regimes and extremes. The team also supports day-of-launch operations for the Space Launch System (SLS), providing real-time monitoring of the winds and thermodynamics along the launch path using an amalgamation of observed, remotely sensed, and modeled output.

Systems Engineering↗

NASA NTRS1984

HH-65A Dolphin digital integrated avionics

Communication, navigation, flight control, and search sensor management are avionics functions which constitute every Search and Rescue (SAR) operation. Routine cockpit duties monopolize crew attention during SAR operations and thus impair crew effectiveness. The United States Coast Guard challenged industry to build an avionics system that automates routine tasks and frees the crew to focus on the mission tasks. The HH-64A SAR avionics systems of communication, navigation, search sensors, and flight control have existed independently. On the SRR helicopter, the flight management system (FMS) was introduced. H coordinates or integrates these functions. The pilot interacts with the FMS rather than the individual subsystems, using simple, straightforward procedures to address distinct mission tasks and the flight management system, in turn, orchestrates integrated system response.

Huntoon, R. B.↗

NASA NTRS1973

Crew microbiology (DTO 71-19)

States of microbial imbalance as a result of human altitude chamber confinement occurred, for the most part, only in those genera and species of bacteria, yeast, and fungi which are classified as transients and are not part of the true indigenous flora of the crewmembers. Inasmuch as no crew illness events occurred and only subtle changes in the indigenous flora were noted, it appears that confinement of 56-days in a Skylab simulated environment does not mediate toward shifts in bacterial populations which have obvious clinical significance.

Wooley, B. C.↗

NASA NTRS1994

Operator modeling in commerical aviation: Cognitive models, intelligent displays, and pilot's assistants

One of the goals of the National Aviation Safety/Automation program is to address the issue of human-centered automation in the cockpit. Human-centered automation is automation that, in the cockpit, enhances or assists the crew rather than replacing them. The Georgia Tech research program focused on this general theme, with emphasis on designing a computer-based pilot's assistant, intelligent (i.e, context-sensitive) displays, and an intelligent tutoring system for understanding and operating the autoflight system. In particular, the aids and displays were designed to enhance the crew's situational awareness of the current state of the automated flight systems and to assist the crew's situational awareness of the current state of the automated flight systems and to assist the crew in coordinating the autoflight system resources. The activities of this grant included: (1) an OFMspert to understand pilot navigation activities in a 727 class aircraft; (2) an extension of OFMspert to understand mode control in a glass cockpit, Georgia Tech Crew Activity Tracking System (GT-CATS); (3) the design of a training system to teach pilots about the vertical navigation portion of the flight management system -VNAV Tutor; and (4) a proof-of-concept display, using existing display technology, to facilitate mode awareness, particularly in situations in which controlled flight into terrain (CFIT) is a potential.

Govindaraj, T.↗

NASA NTRS2017

Prediction of Cognitive States During Flight Simulation Using Multimodal Psychophysiological Sensing

The Commercial Aviation Safety Team found the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness (ASA), and distraction was involved in all of them. Research on attention-related human performance limiting states (AHPLS) such as channelized attention, diverted attention, startle/surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors was implemented to simultaneously measure their physiological markers during a high fidelity flight simulation human subject study. Twenty-four pilot participants were asked to wear the sensors while they performed benchmark tasks and motion-based flight scenarios designed to induce AHPLS. Pattern classification was employed to predict the occurrence of AHPLS during flight simulation also designed to induce those states. Classifier training data were collected during performance of the benchmark tasks. Multimodal classification was performed, using pre-processed electroencephalography, galvanic skin response, electrocardiogram, and respiration signals as input features. A combination of one, some or all modalities were used. Extreme gradient boosting, random forest and two support vector machine classifiers were implemented. The best accuracy for each modality-classifier combination is reported. Results using a select set of features and using the full set of available features are presented. Further, results are presented for training one classifier with the combined features and for training multiple classifiers with features from each modality separately. Using the select set of features and combined training, multistate prediction accuracy averaged 0.64 +/- 0.14 across thirteen participants and was significantly higher than that for the separate training case. These results support the goal of demonstrating simultaneous real-time classification of multiple states using multiple sensing modalities in high fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Harrivel, Angela R.↗

NASA NTRSDate not supplied

Challenges, Considerations, and Opportunities for Exercise and Medical Accommodation Inside a Small Pressurized Rover

Pressurized Rovers (PR) can enable crew to explore away from a lander or surface habitat at distances not possible on foot or even in unpressurized rovers. Sustaining crew for multiple days, they can rove for weeks, independent of other surface elements. Because these are essentially mobile habitats, it is critical that they provide sufficient volume to accommodate the exercise and medical systems to maintain human health in remote, low gravity environments such as the Moon and Mars. This is an area of extensive unknowns as requirements have not yet been developed for exercise or medical systems in pressurized rovers. Yet they must be considered in vehicle sizing studies as they are significant volume drivers, requiring allocation for stowed and deployed hardware inside the rover cabin. Previously flown spacecraft have allocated varying amounts of volume based on the expected crew mission and the state of the art in these systems. NASA-STD-3001 provides high-level requirements for standards of medical care and exercise capabilities. Crew injuries are possible both inside the cabin and on extravehicular activities (EVA), therefore requiring medical capability. Exercise countermeasures are needed to counteract the debilitating effects of lowered gravity. This may include both reconditioning following a lengthy microgravity transit as well as ongoing countermeasures against the effect of low surface gravity. The NASA reference concept for the PR dates back to the Constellation Program and prototypes have been extensively tested in NASA’s Desert Research and Technology Studies (DRATS) program as well as at the NASA Johnson Space Center. The PR cabin is designed to accommodate two crewmembers and is subdivided into a forward cockpit area and a main body for crew habitation. EVAs are accomplished by transitioning through suit ports in the aft bulkhead into spacesuits. While no exercise devices have been developed for the PR, some have been prototyped and demonstrated in DRATS analog missions. A cycle ergometer performed reasonably well in DRATS testing as an aerobic exercise device and recent analysis work has theorized that a combination aerobic and resistive device could be packaged into a form factor similar to the DRATS ergometer. It is therefore suitable for use as an initial volumetric placeholder. No sensorimotor devices have been considered for the PR to aid in adaptation to surface gravity. However, there are commercially available treadmills that at minimum represent examples of the type of exercise system that could potentially be used for such a purpose. A combination of field test data, analysis, and CAD modeling will be used to perform a first pass assessment of whether these exercise devices can be stowed and deployed within the PR. Medical inventories from the International Space Station will be used as a volume placeholder for the PR medical system. A configuration will be discussed for medical deployment, including positioning of caregiver, patient, and medical equipment / supplies.

Pressurized Rover↗

NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗

NASA NTRS2015

Piloted Simulator Evaluation of Maneuvering Envelope Information for Flight Crew Awareness

The implementation and evaluation of an efficient method for estimating safe aircraft maneuvering envelopes are discussed. A Bayesian approach is used to produce a deterministic algorithm for estimating aerodynamic system parameters from existing noisy sensor measurements, which are then used to estimate the trim envelope through efficient high- fidelity model-based computations of attainable equilibrium sets. The safe maneuverability limitations are extended beyond the trim envelope through a robust reachability analysis derived from an optimal control formulation. The trim and maneuvering envelope limits are then conveyed to pilots through three axes on the primary flight display. To evaluate the new display features, commercial airline crews flew multiple challenging approach and landing scenarios in the full motion Advanced Concepts Flight Simulator at NASA Ames Research Center, as part of a larger research initiative to investigate the impact on the energy state awareness of the crew. Results show that the additional display features have the potential to significantly improve situational awareness of the flight crew.

maneuvers↗