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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗
NASA NTRSDate not supplied

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗
NASA NTRS1994

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Computer systems design↗
NASA NTRS2006

Control Software for Advanced Video Guidance Sensor

Embedded software has been developed specifically for controlling an Advanced Video Guidance Sensor (AVGS). A Video Guidance Sensor is an optoelectronic system that provides guidance for automated docking of two vehicles. Such a system includes pulsed laser diodes and a video camera, the output of which is digitized. From the positions of digitized target images and known geometric relationships, the relative position and orientation of the vehicles are computed. The present software consists of two subprograms running in two processors that are parts of the AVGS. The subprogram in the first processor receives commands from an external source, checks the commands for correctness, performs commanded non-image-data-processing control functions, and sends image data processing parts of commands to the second processor. The subprogram in the second processor processes image data as commanded. Upon power-up, the software performs basic tests of functionality, then effects a transition to a standby mode. When a command is received, the software goes into one of several operational modes (e.g. acquisition or tracking). The software then returns, to the external source, the data appropriate to the command.

Howard, Richard T.↗
NASA NTRS2014

GeoLab: A Geological Workstation for Future Missions

The GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance theThe GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance the early scientific returns from future missions and ensure that the best samples are selected for Earth return. The facility was also designed to foster the development of instrument technology. Since 2009, when GeoLab design and construction began, the GeoLab team [a group of scientists from the Astromaterials Acquisition and Curation Office within the Astromaterials Research and Exploration Science (ARES) Directorate at JSC] has progressively developed and reconfigured the GeoLab hardware and software interfaces and developed test objectives, which were to 1) determine requirements and strategies for sample handling and prioritization for geological operations on other planetary surfaces, 2) assess the scientific contribution of selective in-situ sample characterization for mission planning, operations, and sample prioritization, 3) evaluate analytical instruments and tools for providing efficient and meaningful data in advance of sample return and 4) identify science operations that leverage human presence with robotic tools. In the first year of tests (2010), GeoLab examined basic glovebox operations performed by one and two crewmembers and science operations performed by a remote science team. The 2010 tests also examined the efficacy of basic sample characterization [descriptions, microscopic imagery, X-ray fluorescence (XRF) analyses] and feedback to the science team. In year 2 (2011), the GeoLab team tested enhanced software and interfaces for the crew and science team (including Web-based and mobile device displays) and demonstrated laboratory configurability with a new diagnostic instrument (the Multispectral Microscopic Imager from the JPL and Arizona State University). In year 3 (2012), the GeoLab team installed and tested a robotic sample manipulator and evaluated robotic-human interfaces for science operations.

Evans, Cynthia↗
NASA NTRS2017

NASA's Space Launch System Takes Shape

Major hardware and software for NASA's Space Launch System (SLS) began rolling off assembly lines in 2016, setting the stage for critical testing in 2017 and the launch of a major new capability for deep space human exploration. SLS continues to pursue a 2018 first launch of Exploration Mission 1 (EM-1). At NASA's Michoud Assembly Facility near New Orleans, LA, Boeing completed welding of structural test and flight liquid hydrogen tanks, and engine sections. Test stands for core stage structural tests at NASA's Marshall Space Flight Center, Huntsville, AL. neared completion. The B2 test stand at NASA's Stennis Space Center, MS, completed major structural renovation to support core stage green run testing in 2018. Orbital ATK successfully test fired its second qualification solid rocket motor in the Utah desert and began casting the motor segments for EM-1. Aerojet Rocketdyne completed its series of test firings to adapt the heritage RS-25 engine to SLS performance requirements. Production is under way on the first five new engine controllers. NASA also signed a contract with Aerojet Rocketdyne for propulsion of the RL10 engines for the Exploration Upper Stage. United Launch Alliance delivered the structural test article for the Interim Cryogenic Propulsion Stage to MSFC for tests and construction was under way on the flight stage. Flight software testing at MSFC, including power quality and command and data handling, was completed. Substantial progress is planned for 2017. Liquid oxygen tank production will be completed at Michoud. Structural testing at Marshall will get under way. RS-25 hotfire testing will verify the new engine controllers. Core stage horizontal integration will begin. The core stage pathfinder mockup will arrive at the B2 test stand for fit checks and tests. EUS will complete preliminary design review. This paper will discuss the technical and programmatic successes and challenges of 2016 and look ahead to plans for 2017.

Askins, Bruce↗
DOE OSTI2020

Improvements to the New CTH Code Verification & Validation Test Suite (FY2020)

The CTH multiphysics hydrocode, which is used for a wide range of important calculations, has undertaken in recent years to overhaul its software quality and testing processes. A key part of this effort entailed building a new, robust V&V test suite made up of traditional hydrocode verification problems, such as those listed in the ASC Tri-Lab Test Suite and the Enhanced Tri-Lab Test Suite, as well as validation problems for some of CTHs most frequently used equations of state, materials models, and other key capabilities. Substantial progress towards this goal was made in FY19. In FY20, this test suite has been expanded to include verification and validation tests of the Sesame and JWL equation of state models as well as the Mader verification problem from the Tri-Lab Test Suite and the Blake verification problem - a linear elastic analog to the Hunter problem from the Enhanced Tri-Lab Test Suite. This report documents CTH performance on the new test suite problems. Verification test results are compared to analytic solutions and, for most tests, convergence results are presented. Validation test results are compared to experimental data and mesh refinement studies are included. CTH performs well overall on the new test problems. Convergence rates for the Blake and Mader problems are comparable to those for similar ASC codes. The JWL and Sesame verification tests show good agreement with analytic solutions. Likewise, CTH simulation results show good agreement with experimental validation data for the Sesame and JWL equations of state for the materials tested. Future V&V work will focus on adding tests for other key capabilities like fracture and high explosive models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2009

Importance of Model Simulations in Cassini In-Flight Mission Events

Simulation environments have been an integral part of Cassini's heritage. From the time of flight software development and testing to the beginning of the spacecraft's extended mission operations, both softsim and hardware-in-the-loop testbeds have played vital roles in verifying and validating key mission events. Satellite flybys and mission-critical events have established the need to model Titan's atmospheric torque, Enceladus' plume density, and other key parametric spacecraft environments. This paper will focus on enhancements to Cassini's Flight Software Development System (FSDS) and Integrated Test Laboratory (ITL) to model key event attributes which establish valid test environments and ensure safe spacecraft operability. Comparisons between simulated to in-flight data are presented which substantiate model validity.

FSDS↗
NASA NTRS2014

More Than A SketchUp

This 2014 summer internship assignment at John F. Kennedy Space Center (K.S.C) was conducted with the National Aeronautics and Space Administration (NASA) Engineering and Technology (NE) group in support of the Control and Data Systems Division (NE-C) within the Test, Operations & Support Software Engineering Branch (NE-C2). The primary focus of this project was to assist Branch Chief Laurie B. Griffin, to support NASA's Small Payload Launch Integrated Testing Services (SPLITS) mission, by mastering the capabilities of 3-D modeling software called SketchUp. I used SketchUp to create a virtual environment for different laboratories of the NE-00 Division. My mission was to have these models uploaded into a K.S.C Partnerships Website and be used as a visual aid to viewers who browsed the site. The leads of this project were Kay L. Craig, Business and Industry Specialist (AD-A) and Steven E. Cain, (FA-C). I teamed with fellow intern Tait Sorenson of the Flight Structures and Thermal Protection Systems Branch (NE-M5) and met with many K.S.C lab managers willing to display their lab's structure and capabilities. The information collected during these lab tours was vital to the building of the K.S.C Partnerships Website. To accomplish this goal Sorenson and I later teamed with fellow Marketing intern Marlee Pereda-Ramos, of the Spaceport Planning Office In Center Planning And Development (AD-A) Along with Ramos, Tait and I toured an array of laboratories and got first hand exposure to their functions and capabilities.

Trimble Corporation↗
NASA NTRS2012

Development of the GPM Observatory Thermal Vacuum Test Model

A software-based thermal modeling process was documented for generating the thermal panel settings necessary to simulate worst-case on-orbit flight environments in an observatory-level thermal vacuum test setup. The method for creating such a thermal model involved four major steps: (1) determining the major thermal zones for test as indicated by the major dissipating components on the spacecraft, then mapping the major heat flows between these components; (2) finding the flight equivalent sink temperatures for these test thermal zones; (3) determining the thermal test ground support equipment (GSE) design and initial thermal panel settings based on the equivalent sink temperatures; and (4) adjusting the panel settings in the test model to match heat flows and temperatures with the flight model. The observatory test thermal model developed from this process allows quick predictions of the performance of the thermal vacuum test design. In this work, the method described above was applied to the Global Precipitation Measurement (GPM) core observatory spacecraft, a joint project between NASA and the Japanese Aerospace Exploration Agency (JAXA) which is currently being integrated at NASA Goddard Space Flight Center for launch in Early 2014. From preliminary results, the thermal test model generated from this process shows that the heat flows and temperatures match fairly well with the flight thermal model, indicating that the test model can simulate fairly accurately the conditions on-orbit. However, further analysis is needed to determine the best test configuration possible to validate the GPM thermal design before the start of environmental testing later this year. Also, while this analysis method has been applied solely to GPM, it should be emphasized that the same process can be applied to any mission to develop an effective test setup and panel settings which accurately simulate on-orbit thermal environments.

Yang, Kan↗
NASA NTRSDate not supplied

NEUROSPF: A Tool For the Symbolic Analysis of Neural Networks

This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and translates them into a Java representation that is amenable for analysis using the Symbolic PathFinder symbolic execution tool. Notably, NEUROSPF encodes specialized peer classes for parsing the model’s parameters, thereby enabling efficient analysis. With NEUROSPF the user has the flexibility to specify either the inputs or the network internal parameters as symbolic, promoting the application of program analysis and testing approaches from software engineering to the field of machine learning. For instance, NEUROSPF can be used for coverage-based testing and test generation, finding adversarial examples and also constraint-based repair of neural networks, thus improving the reliability of neural networks and of the applications that use them.

neural networks↗
NASA NTRS1977

Data processing system and interfacing elements time base analysis

The processing of time in the Orbiter System Services software and the associated facilities provided to the user community are described. The descriptions are directed toward showing the functional intent of the design rather than the actual implementation. Simplified flow diagrams are included. Based upon detailed analysis of a preliminary review copy of the Approach and Landing Test (ALT) System Software Detailed Design Specification and the Program Listings for Version 17 Prime, the processing of time has the potential for error free operations. The processing of time is not expected to change between ALT and the Operational Flight Test (OFT) other than differences in value of some constants for control and limit checking. Due to the dynamic nature of onboard time processing and its criticality to the successful operation of the orbiter, it is recommended that a comprehensive list of external variables, their locations, initial values, and a 'where used' listing be produced, as a by-product of the link edit process, for all non-HAL coding. In addition, a careful review of the verification test procedures for the System Services time-related software is recommended.

Blackburn, J. D.↗
NASA NTRSDate not supplied

cFS Test Framework (CTF)

NASA's Core Flight System (cFS) provides a generic flight software framework architecture for developing flight software. As the cFS framework has gained popularity over the years within the flight software community, supporting software tools have been developed to assist in the design, development, testing and verification of flight software. The cFS Test Framework (CTF) is a recently developed cFS tool with capabilities to develop and run automated test and verification scripts against flight software targets. The CTF tool parses and executes JSON-based test scripts containing test instructions, while logging and reporting the results. CTF utilizes a plugin-based architecture to allow developers to extend CTF with new test instructions, external interfaces, and custom functionality. To interface with flight software, CTF parses a set of CCSDS message definition files to create the necessary command and telemetry structures for use during the test run. Additionally, CTF also supports interfacing with multiple cFS instances, allowing a test script to verify requirements that involve multiple flight software targets. Lastly, CTF provides support for executing test scripts against FSW running on remote or embedded hardware. This allows CTF to execute the same test scripts across different target configurations throughout the development process. In this presentation, we will introduce the cFS Test Framework (CTF) architecture, discuss the history of cFS testing frameworks, and present the features and capabilities currently provided by CTF. Lastly, we will show a demo of the CTF tool being used to execute test scripts against flight software.

Aly I Shehata↗
DOE OSTI2024

Promoting regulatory acceptance of combined ion and neutron irradiation testing of nuclear reactor materials: Modeling and software considerations

As the needs for the nuclear energy industry continue to evolve in the 21st century, timely adoption of new technological solutions acceptable to regulatory agencies is critical. Quantitative prediction of radiation damage in materials and its impact on mechanical properties is a key component of licensing and regulatory decisions regarding nuclear power plants. Accelerated testing methodologies such as combined ion and neutron irradiation data sets are crucial for the development and deployment of new materials and new manufacturing methods (e.g., additive manufacturing). However, regulatory acceptance of accelerated testing methodologies is necessary for their adoption. Further, the present work discusses the fundamental basis for comparing ion- and neutron-induced material microstructures, the theory behind interpreting radiation damage across length and time scales and radiation types, and the codes, standards, and quality assurance concerns surrounding different modeling methods and software. In particular, recommendations are given as to the path forward that will enable national laboratories, academia, and industry to develop the modeling and software basis for regulatory acceptance of the combined use of ion and neutron irradiation for material performance evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Parallel Processing with Digital Signal Processing Hardware and Software

The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development.

Swenson, Cory V.↗
NASA NTRSDate not supplied

Astrobee: Five years of Completed, Current, and Future Research on the International Space Station using Free Flying Robots.

After five years on the International Space Station (ISS), the Astrobee Research Facility, has completed over 160 Test Sessions logging over 1200 hours of operations. Managed by the NASA ISS Program OZ office and supported by NASA Ames Research Center (ARC) in California, the Astrobee Team currently maintains two identical free-flying Astrobee robots and a Docking Station for research on the ISS. As a technology demonstration platform, the Astrobee Robots are available for Guest Scientists to use for a spectrum of research capabilities. Using ambient air on the ISS, propelled by battery-operated fans, Astrobee is designed to autonomously operate throughout most of the USOS (US Orbital Segment), with the objective of minimizing the need for astronaut support. Astrobee carries a suite of six cameras, a two degree-of-freedom (DOF) arm with a gripper that can grasp ISS handrails and other objects, and three payload bays that provide power and data for guest science hardware. Astrobee can autonomously execute hours-long flight plans or be tele-operated from the ground. While the Astrobee Team continues to improve mapping and autonomous flight capabilities, one of the main goals of Astrobee Robots is to provide research opportunities for Guest Scientists. The Astrobee Robot Software (ARS) makes extensive use of the open-source Robot Operating System (ROS). The ARS can be used interchangeably with an Astrobee Simulator or as Astrobee’s onboard software. ARS features include autonomous docking and perching, real-time teleoperations from the ground, plan based autonomous tasks, multi Astrobee communication, among other capabilities. Through simulation software and ground testing laboratories, the Astrobee Team is available to support Guest Scientists during development and testing and lead real-time ISS operations. The Astrobee Team and Guest Scientists have completed research including Astrobatics maneuvers, RFID and sound sensing capabilities, Gecko materials studies, student Robotics Programming Challenges, and Free Flyer formation flight investigations. Current science with the Astrobee Robots is investigating new docking capabilities through software only research as well as testing new docking hardware installed on the Astrobees. The Astrobee Team and other researchers at NASA Ames continue to explore robotics applications for future NASA missions such as Gateway and potential experiments involving human-robot interactions. Continued advanced mapping resolution capabilities, and high-resolution panoramic imagery also remains areas of research. Exciting in development research involves docking for rendezvous proximity operation (CLINGERS), multi resolution 3D scanning (MRS), space debris removal in microgravity (REACCH). This presentation will mainly focus on completed research over the past year and current science being performed on the Astrobees. This presentation will also focus on how a Guest Scientist/Researcher progresses from conception to running their science on the Astrobees on the ISS, as well as discuss the Astrobee Facility resources available for supporting ground testing and real-time ISS operations.

Astrobee↗
NASA NTRSDate not supplied

Increasing Cognitive Ability/Reserve Using Software – Pilot (ICARUS-Pilot)

BACKGROUND This research study was competitively awarded under the 2022 JSC Innovation Charge Account (ICA) program administered by NASA Johnson Space Center’s Joint Technology Working Group. Study period of performance was May through September 2022, with a maximum allowed procurement budget of $10K. The study sought to quantify and assess the potential benefit of using commercial-off-the-shelf (COTS) cognitive training software to improve cognitive performance in an astronaut-like terrestrial population. METHODS Five volunteer research participants were recruited from the JSC employee population to mimic certain demographic characteristics of the NASA astronaut population (age, education/discipline). Participant cognitive performance was assessed before and after executing eighteen sessions of remote cognitive training executed nominally three times per week using six exercises within an adaptive app-based COTS software package (BrainHQ, Posit Science) on study-provided tablets. Pre- and post-training cognitive performance was measured using internal assessments in BrainHQ as well as Cognition Test Battery (CTB) version ISS B01 v3 (3.0.9-201710021500), an independent software test developed specifically for NASA and used currently in research studies on astronauts. BrainHQ exercises were posited to map well or partially to several CTB sub-tests. Participants provided feedback on their study experience formally via semi-structured interview at the conclusion of testing and informally throughout the study if they encountered issues. RESULTS The enrolled ICARUS-Pilot study participants generally matched Artemis crew demographic characteristics. Four of five participants have completed study training and assessment activities as of the writing of this abstract. These test participants complied well with desired training session frequency and duration yielding an average cumulative active training duration of 15 hours over an average of 45 days; participants showed 78% average improvement in metric performance for the six trained exercises, with an associated overall 33%ile ranking increase against performance of the entire BrainHQ subscribing population for internal pre/post assessment, agreeing with post-study survey self-reported performance increases. CTB overall feedback scoring, not corrected for learning effects, showed an average of 19% performance improvement across its 10 performance measures over the training period for the completed participants. Detailed analyses will be conducted once participant data collection for the study is complete and the resulting dataset is fully populated. DISCUSSION These preliminary results provide a positive trend for the effectiveness of the training approach, but further analysis will be needed to establish significance, investigate far transfer, and suggest the needed participant pool size for subsequent efforts to achieve statistically significant outcomes given similar results. The pilot study has already been helpful by allowing the study team to learn a great deal about the capabilities and limitations of the COTS software package that will be reflected in future proposals along with revised timelines for study execution and test participant management. From participant feedback, one common thread regarding the COTS training was that it felt overly repetitive – future proposals should reassess overall training duration, available levels for each trained exercise, and the behavior of the BrainHQ internal scheduler in determining which exercises should be trained and for how long. If the final analysis of this feasibility study ultimately supports it, the study team will recommend further investigation to fully evaluate this potential countermeasure and optimize its implementation. Future proposals would cite this feasibility study’s outcome and would seek to refine the training protocol and obtain statistically significant results for cognitive performance increases as well as retention data.

cognitive training↗