Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “usability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,801 records · Page 100

Modeling the Uncertainties of Solar System Ephemerides for Robust Gravitational-wave Searches with Pular-timing Arrays

The regularity of pulsar emissions becomes apparent once we reference the pulses’ times of arrivals to the inertial rest frame of the solar system. It follows that errors in the determination of Earthʼs position with respect to the solar system barycenter can appear as a time-correlated bias in pulsar-timing residual time series, affecting the searches for low-frequency gravitational waves performed with pulsar-timing arrays. Indeed, recent array data sets yield different gravitational-wave background upper limits and detection statistics when analyzed with different solar system ephemerides. Crucially, the ephemerides do not generally provide usable error representations. In this article, we describe the motivation, construction, and application of a physical model of solar system ephemeris uncertainties, which focuses on the degrees of freedom (Jupiterʼs orbital elements) most relevant to gravitational-wave searches with pulsar-timing arrays. This model, BAYESEPHEM, was used to derive ephemeris-robust results in NANOGravʼs 11 yr stochastic-background search, and it provides a foundation for future searches by NANOGrav and other consortia. The analysis and simulations reported here suggest that ephemeris modeling reduces the gravitational-wave sensitivity of the 11 yr data set and that this degeneracy will vanish with improved ephemerides and with pulsar-timing data sets that extend well beyond a single Jovian orbital period.

M Vallisneri↗

Management of Operations under Visual Flight Rules in UTM for Disaster Response Missions

The disaster response domain has experienced an increased focus in recent years due to the rise in number and scale of events, lessons learned from past experience, and emerging technologies that make possible a more coordinated and effective response. As part of this focus, JAXA and NASA have been collaborating on the integration of manned and unmanned aircraft in support of disaster response operations through integrated testing of their respective mission planning and optimization system (Disaster Relief Aircraft Information Sharing Network, or D-NET) and an automated UAS traffic management system (e.g., UTM). In 2018, JAXA and NASA jointly participated in a large-scale disaster drill in Japan where the integration of systems was successfully demonstrated through real-time data exchanges, visualization, and decision making as part of the coordinated airspace management of a manned helicopter in VFR conditions and unmanned small UAS operating in common areas. This work details a flight test consisting of two flights that were conducted December 2019 near the Chofu Aerodrome in Tokyo, which focused on the evaluation of pilots operating under Visual Flight Rules (VFR) communicating through D-NET and sharing intent and position information within UTM. This work contributes to defining the necessary requirements for digital coordination between manned and unmanned operations. UTM requires the use of operation volumes, which are spatial and temporal volumes that encompass UAS flight trajectories and account for technical performance errors and deviations due to disturbances (e.g., wind). A series of flights, representing different missions, used landmark-based operation volumes and conformance of the aircraft to those operation volumes were tracked within UTM. Experienced disaster response helicopter pilots provided insight on the development of the operation plans and their usability during disaster response operations. Results from the flight test supported the suggested benefits of using landmarks for planning and positional awareness and highlighted the need for future research in advanced visualization capabilities to support operations that consider both system constraints and flight deck/airspace management interaction.

disaster response↗

Landsat 9 pre-launch sensor characterization and comparison with Landsat 8 results

Landsat 9 is planned for launch in December 2020 to continue the mission of observing changes on the Earth’s surface that began in 1972 with the launch of Landsat 1. Like Landsat 8, Landsat 9 will carry two imaging instruments: Operational Land Imager 2 (OLI-2), designed and built by Ball Aerospace, and Thermal Infrared Sensor 2 (TIRS-2), manufactured by NASA Goddard Space Flight Center (GSFC). As of this writing, both sensors have completed the instrument-level ground testing and are ready for integration into the spacecraft. Data collected during the pre-launch performance testing are analyzed to assess the usability of responses of the video reference pixels (VRPs)located on the focal planes of OLI-2 and Landsat 8 OLI for more accurate detector bias estimates, develop a methodology to correct for nonlinearities in the OLI-2 response and compare it to the OLI correction approach, and determine the spatial performance of TIRS-2.

Esad Micijevic↗

On-Orbit Cryogenic Refueling: Potential Mission Benefits, Associated Orbital Mechanics, and Fuel Transfer Thermodynamic Modeling Efforts

The placement of cryogenic fuel/propellant depot stations in Earth orbit has the potential to transform the nature and operations for many types of spaceflight missions. Today, spaceflight missions are almost universally required to carry the entire amount of fuel required for the mission, for the entire duration of the mission, from the point of launch. This is the rough equivalent of making a drive from Ohio to California, requiring the traveler to bring along the total sum of gasoline required for the entire trip, without being able to ‘fill-up’ anywhere along the route. Obviously, this framework of travel greatly encumbers the breadth, scope, and efficiency of potential journeys. Cryogenic fuel/propellant depots have not been implemented because many technical, operational, and engineering challenges still exist. These must be overcome prior to the placement of usable on-orbit propellant depots. This thesis investigates three specific engineering challenges related to on-orbit propellant depots, and presents the current state, technological challenges, and ultimate benefits of on-orbit cryogenic refueling.

No vent fill↗

EnDEVR: An Environment for Data Engineering in VR

Organizations within the public and private sectors are looking to improve their data science operations for research, development, and operational purposes. As this interest in data science grows, so too does interest in tools and programs that facilitating such operations. This paper presents EnDEVR, the Environment for Data Engineering in Virtual Reality, a user-extensible system that allows for the execution of custom data science functions. We describe the user-centered design process for the EnDEVR system, based on the needs of subject matter experts within the aerospace and aviation industries. Fundamental to this design is a method for users to integrate their existing analysis code (that may leverage third-party vendors) as usable objects in the virtual environment; this allows organizations to operate without the price tag and lifetime obligations associated with commercial data science toolkits, a concept known as “vendor lock-in”. We then present our system design with iterative implementations, and conclude with lessons learned. The presented work may provide insight into future user-centered design processes for VR applications, particularly for digital transformation stakeholders to circumvent vendor lock-in.

Human-centered computing↗

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗

IMPACT User Experience

NASA Human Research Project (HRP) and Exploration Medical Capabilities (ExMC) team identified a need to implement a human-centered design approach for a computational tool that performs detailed trade space analysis and research prioritization, known as Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT). IMPACT processes numerous parameters such as space vehicle design, mission objectives, evacuation capability, medical events, and mission constraint, including but not limited to; duration, mass, volume, equipment, and medical capability, each with complex and interconnected relationships. The ability for users to navigate through these complexities and provide an intuitive report is critical to aiding stakeholders in the decision-making process of future missions. In this presentation we will discuss how the IMPACT team has applied human-centered design strategies to improve system usability by modelling human-system integration (i.e., task analysis) with the MagicDraw SysML modelling application and performing A/B testing of user interface prototypes.

S Ozbek↗

Lunar Surface Cargo Offloading Concepts

A sustainable presence on the lunar surface will serve as a vital training ground and technology demonstration test site in preparation for future human missions to Mars. Robotic lunar surface campaigns will focus on the exploration of resources providing information on the availability and extraction of usable resources, such as oxygen and water, and prepare the surface for a sustained human presence. Landers, outfitted with sensor packages, will be used to conduct risk-reduction activities and aid in the development of technologies prior to the crewed lunar missions that drive the need to for a logistics supply chain that requires offloading. A series of landers will be required on other planetary surfaces to build up the capabilities, capitalizing on those resources, required for sustained human presence. In each of those landers will be cargo including ascent vehicles, habitats, supplies, science packages, spare parts, fluids commodities for fuel and life support, and others varying in volume and ranging from mass in hundreds of kilograms to an estimated 6-14 metric tons to support Human Landing Systems and surface logistics requirements. This paper will examine the challenge of offloading examples of these cargo elements from different categories of landers on the lunar surface using a variety of methodologies. Challenges on the lunar surface arise with the conditions present (thermal, lighting, communications, regolith consistency), the desire to minimize mass of all landed systems, the desire to perform much of the activities with limited to minimal human interaction, and the overall configuration of the landers that are responsible for landing the cargo.

Lunar↗

pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment

Metadata quality is essential to effective data discovery and has become increasingly vital as more Earth Science data sets become available. The Common Metadata Repository (CMR) hosts metadata describing NASA’s Earth Observation data products, which are archived across 12 Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, conducts metadata quality assessments to ensure that these data products are discoverable, accessible, and usable. To achieve these goals, the ARC team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency. ARC uses a combination of manual and automated methods to assess these three components and identify areas of improvement; the team then collaborates with the DAACs to resolve any findings. To streamline this process, ARC is currently developing a host of scripts, known as pyQuARC, to automate metadata quality assessments as much as possible. pyQuARC is an open source library for Earth Observation Metadata Quality Assessment, and the tool utilizes ARC’s metadata quality assessment framework to make basic validation checks, pinpoint inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identify opportunities for more descriptive and robust information. Since pyQuARC is also customizable, other users can make modifications as needed, and future metadata standards can also be implemented. Once pyQuARC is fully developed, it will support multiple schema types to serve the broader EOSDIS metadata community. This presentation will provide an overview of pyQuARC and its process of development while showcasing the tool’s valuable features and uses.

Jenny Wood↗

Turning Limitations into Opportunities in the Development of the Orion Medical System: Incorporation of mHealth Devices

INTRODUCTION: Selection of medical devices for the Orion medical system is a complex task which is dependent on the current state of terrestrial technology. In this work we review the interplay between NASA requirements, constraints, and opportunities for synergy during the development of the Orion medical system. METHODS: The “plan to treat” list of conditions, and subsequently the medical resource list for the Orion Artemis II lunar flyby mission was completed using semi-quantitative methods. During this process, some medical resources were excluded to comply with mass and volume limits, while other resources applicable to multiple medical requirements were prioritized for inclusion. Choices were also examined considering NASA level of care standards for the Artemis design reference missions. As a means to optimize capabilities in spite of mass and volume constraints, ideas for integration of multiple devices into a single platform were explored, including a ‘hackathon’ challenge which was conducted to generate and evaluate concepts for combining medical devices into a single app-based mobile device (ultrasound, ECG, etc.). RESULTS: The Orion team identified 128 medical conditions that we “plan to treat”, with 139 unique medical resources to address these conditions, including 5 digital diagnostic devices (ECG, otoscope, stethoscope, pulse oximeter, and blood pressure monitor). During selection of these digital devices the team noted that miniaturized medical devices often use mobile device platforms (mHealth), some displaying and transmitting data exclusively via mobile device. Of the 5 initially selected devices, all are capable of mobile connection, one which cannot function without a mobile device (ECG). Furthermore, only one of these devices connects natively to a Windows platform, which is currently the only operating system available on Orion. DISCUSSION: Significant savings in mass and volume as well as training and usability improvements can be achieved by leveraging mHealth technologies. However, the platform presents significant challenges for deployment within the Artemis Program including lack of internet connectivity, incompatible operating systems, and radiation concerns. Each of these drawbacks are surmountable with investment in the supporting vehicle architecture, which may become necessary to support the technology trends seen in commercially available medical devices today. Objective: Learn about the opportunities and challenges of leveraging mHealth devices in the development of medical capabilities for austere environments. Learn about the constraints of the NASA spaceflight environment with regards to digital medical device integration.

Douglas Ebert↗

A Framework for Assessing Earth Observation Metadata Quality: Implications for Data Discovery and Open Science

The Common Metadata Repository (CMR) contains metadata records describing NASA’s collection of over 8,000 Earth observation data products. The Analysis and Review of CMR (ARC) Team at Marshall Space Flight Center assesses the quality of these metadata records. Metadata, rather than the data itself, is indexed for search in both discipline-specific datacenters and global or aggregated catalogs (such as Earth data Search), making it essential for determining whether a data product is appropriate for a given research question or application need. Since metadata connects users to data, it should be as accurate and complete as possible in addition to meeting minimum database requirements. The ARC team has developed a metadata quality framework by which to assess quality. The framework consists of a set of quality criteria that converge around the dimensions of correctness, completeness, and consistency, with the goal of improving the discoverability, accessibility, and usability of NASA’s Earth Observation data. The application of the framework has resulted in a measurable improvement in NASA’s metadata quality. Key aspects of the framework’s success are the ability to systematically evaluate metadata and provide actionable quality improvement recommendations. Lessons learned from the project will be shared along with implementation details which may be relevant to other science disciplines. By aiming to make data more discoverable and accessible to a broad user community, the ARC metadata quality framework helps contribute to NASA’s commitment to open science.

Jeanne Le Roux↗

OSIRIS-REx Orbit Trim Strategy

One of the more challenging aspects of the trajectory design for the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) mission at asteroid Bennu was maneuvering while in orbit. The orbital dynamics were highly perturbed by various sources, most notably solar radiation pressure, which degraded accuracy of long term predictions of the spacecraft’s location in orbit. Generally, the Navigation team had to solve three separate issues: correcting a perturbed orbit, changing to a different orbit, or phasing the or bitto place the spacecraft at a specific location at a specific time. The team composed a common framework using up to two maneuvers that could solve all of these problems using an identical schedule that allowed for consistent planning long before the final trajectory could be designed. This orbit trim strategy was successfully used for the first time in the Orbital B phase of the mission to maximize the duration of usable observing geometry in a time-variable orbit with strict operational limits. It was used an additional 3 times throughout the mission to adjust and/or change the orbit, most notably altering the orbit in the weeks prior to the successful Touch-And-Go (TAG)sample collection attempt. This same strategy was used to phase the orbit a total 10 times in preparation for each of the science sorties over potential sample sites, the TAG Rehearsals, and TAG. The trim strategy was demonstrated to be robust and performed exceptionally well in all aspects, which proved critical to a successful sample collection.

Daniel R. Wibben↗

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗

NASA GLOBE CLOUD GAZE: Creating Data Quality Flags for Citizen Science Cloud Observations Matched to NASA Satellite Data

The GLOBE Program, NASA’s largest and longest lasting citizen science program about the Earth, has been collecting cloud observations matched to multiple satellite data daily. The program’s cloud protocol is historically the most popular protocol as your eyes are the only instruments you need to collect observations of the sky. This dataset includes over 3,300,000 cloud observations with variables like total cloud cover, cloud type and opacity that are collocated to the nearest overpass times of geostationary satellites (GOES-15, GOES-16, GOES-17, Meteosat-8, Meteosat-11, or Himawari-8), or to Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard Aqua and Terra, or the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In order to increase the usability of this dataset, the Community science project Leveraging Online and User Data through GLOBE And Zooniverse Engagement (CLOUD GAZE) has been developed to generate data quality flags of these ground-up and top-down perspectives of sky and clouds. Recently funded through NASA’s Citizen Science for Earth Systems Program, CLOUD GAZE has partnered with the Zooniverse online platform to obtain reference data and image tagging of sky photographs collected through The GLOBE Program’s clouds protocol. This paper will present the GLOBE Clouds dataset matched to NASA satellite data, integration of CLOUD GAZE to develop data quality flags, and research applications of the dataset (includes ground-up and top-down perspective comparisons, ground observations of dust storms and smoke plumes, and cloud observations in polar regions). The paper will also present on techniques and recommendations for classroom use and for community engagement, particularly for those looking to online resources.

Marilé Colón Robles↗

Automation & Autonomy Standards and Guidelines for Space Vehicles

The NASA Office of the Chief Health and Medical Officer (OCHMO) requested HRP conduct a survey of industry and government standards and guidelines for the interaction of automation/autonomy with humans. Guidance for verification testing of human-automation designs was also requested. A rapid response was requested so that the deliverables could be provided as part of a future NASA solicitation for automated systems for HLS. The project began with a broad review and analysis of prior NASA work in this area, as well as external standards related to human interaction with automation/autonomy. The team reviewed approximately 200 documents, and interviewed multiple industry and government subject matter experts (SMEs). “Gold standard” documents were selected for focus and key categories were identified. A cross-walk of standards was created, and common standards and guidelines were selected and rephrased (where necessary) to be information-rich, concise, and usable. Verification guidelines and examples were also developed. The final report includes an introduction to automation and autonomy, selected standards and guidelines, verification method guidance, and research gaps. In addition to the report, the team delivered a list of candidate standards for autonomous vehicles, as well as a list of candidate standards for a future NASA-STD-3001 update on automation/autonomy. The presentation will describe the rapid response project approach and methods, examples of standards and guidelines identified and delivered to OCHMO, and research needed to develop additional automation/autonomy design guidance where gaps currently exist.

automation↗

Trust in Collaborative Automation in High Stakes Software Engineering Work

The amount of autonomy in software engineering tools is increasing as developers build increasingly complex systems. Research in other domains shows that too much or too little trust in autonomous tools can have negative consequences, but we are not aware of any study that has investigated trust in autonomous tools in the highly interactive context of a software engineering workplace. We present the results of a ten week ethnographic case study of engineers collaborating with autonomous tools to write flight software at a large national space exploration organization to support high stakes missions. We find that trust in an autonomous software engineering tool in this setting was influenced by four main factors: the tool’s transparency, social context, an organization’s associated processes, and its usability. We outline theoretical implications for future research into trust in autonomous software engineering tools, and practical implications for tool designers and organizations conducting high stakes work with autonomous tools.

Davidoff, Scott↗

The Io GIS Database 1.0: A Proto-Io Planetary Spatial Data Infrastructure

We collected a set of published, higher-order data products of Jupiterʼs volcanic moon Io and assembled them in an ArcGISTM database we are calling the Io GIS Database, version 1.0. The purpose of this database is to collect image, topographic, geologic, and thermal emission data of Io in one geospatially registered location to form the data component of an Io planetary spatial data infrastructure (PSDI). The goals of an Io PSDI are (1) to make higher-order data products more accessible and usable to the broader planetary science community, particularly to new scientists that were not associated with the projects that obtained the data; (2) to enable new scientific studies with the data; and (3) to create a tool to support observation planning for future Io-focused planetary missions. In this paper we describe the motivation behind our project, discuss the data sets acquired for this first version of the database, and demonstrate how they can be used. We conclude with a discussion of how our database relates to other PSDIs, our plans for future updates, and a request for additional Io data sets.

David A Williams↗

Remote Concurrent Engineering: A-Team Studies in the Virtual World

NASA Jet Propulsion Laboratory’s (JPL’s)Architecture Team (A-Team) has nearly a decade of experiencein maturing early formulation mission and technology conceptsby combining innovative collaborative engineering methodswith cutting-edge subject matter expertise and advancedanalysis tools in an in-person environment. When COVID-19forced JPL’s workforce to work remotely in March 2020, ATeamhad to quickly pivot from an in-person collaborativeenvironment to a remote working environment.Through introspection, careful planning, and considerablepractice, A-Team was able to develop new operating proceduresto effectively continue early formulation studies in a virtualenvironment. A-Team has held over 57 remote studies in the 10months since the start of mandatory telework at JPL in March2020. In the remote setting, A-Team conducts studies in half-daysessions with clients and subject matter experts (SMEs) viavideoconferencing, shared computer screens, and digitalcollaborative tools.The key lesson is that increased staffing and planning is neededto prepare and successfully run remote A-Team studies. RemoteA-Team studies require careful selection of the appropriatetools for security, accessibility, and usability within theNASA/JPL environment. Knowledge capture methods andtemplates need to be thought out and agreed upon in advance asthere is less room for improvising in a remote format. Variouscommunication channels have to be monitored to allow for teamcoordination while maintaining fruitful participant engagementduring a session. In addition, technical backup for all roleswithin the A-Team have to be identified to allow the study tocontinue even if a team member’s connectivity is temporarilyinterrupted. Finally, careful thought has to be put into methodsand processes to create a collaborative environment in a virtualspace such that a group of experts who are only connected viathe internet can experience the creative spark and flow of a greatcollaborative and innovative study.

Zusack, Steven↗

Refine your search to explore more results.