Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “INTERFACES”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Best Practices for Evaluating Flight Deck Interfaces for Transport Category Aircraft with Particular Relevance to Issues of Attention, Awareness, and Understanding CAST SE-210 Output 2 Report 6 of 6

Attention, awareness, and understanding of the flight crew are a critical contributor to safety and the flight deck plays a critical role in supporting these cognitive functions. Changes to the flight deck need to be evaluated for whether the changed device provides adequate support for these functions. This report describes a set of diverse evaluation methods. The report recommends designing the interface-evaluation to span the phases of the device development, from early to late, and it provides methods appropriate at each phase. It describes the various ways in which an interface or interface component can fail to support awareness as potential issues to be assessed in evaluation. It summarizes appropriate methods to evaluate different issues concerning inadequate support for these functions, throughout the phases of development.

Billman, Dorrit O.↗
NASA NTRS2018

Towards Informing an Intuitive Mission Planning Interface for Autonomous Multi-Asset Teams via Image Descriptions

Establishing a basis for certification of autonomous systems using trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Human-Machine Interface (HMI) team is working to capture and utilize the multitude of ways in which humans are already comfortable communicating mission goals and translate that into an intuitive mission planning interface. Several input/output modalities (speech/audio, typing/text, touch, and gesture) are being considered and investigated in the context human-machine teaming for the ATTRACTOR design reference mission (DRM) of Search and Rescue or (more generally) intelligence, surveillance, and reconnaissance (ISR). The first of these investigations, the Human Informed Natural-language GANs Evaluation (HINGE) data collection effort, is aimed at building an image description database to train a Generative Adversarial Network (GAN). In addition to building an image description database, the HMI team was interested if, and how, modality (spoken vs. written) affects different aspects of the image description given. The results will be analyzed to better inform the designing of an interface for mission planning.

Generative Adversarial Network (GAN)↗
NASA NTRS2020

Ultrafast Melting at Metal-Semiconductor Interfaces: A Molecular Dynamics Study

Quantifying the thermodynamics of interfacial melting is important for several applications such as laser machining and designing radiation hardened electronic devices. Due to the short time and length scales that are involved in the process, molecular simulations provide an ideal path for understating the interfacial melting phenomena. In this work we investigate tungsten (W) – silicon carbide (SiC) interfaces which are relevant in modern high-power electronic devices. Classical molecular dynamics simulations along with the two-temperature model (TTM) were used to study the radiation induced melting of the interface while a neural network-based machine learning framework was used to track the transient re-crystallization process. The damage endured by the semiconductor at the interface following the radiation event is discussed in detail while the re-crystallization of the metal is described in terms of the classical nucleation theory.

Ashwin Ravichandran↗
NASA NTRSDate not supplied

Extending the Capabilities of Thermal Desktop with the OpenTD Application Programming Interface

With the release of Thermal Desktop 6.0, users now had the ability to interface with some of the many elements and constructs of a Thermal Desktop model through external applications developed using the TD API (Application Programming Interface). This file allows applications to be developed in the .NET framework and interface to a number of object types within a Thermal Desktop model. The release of 6.1 expands the subset of objects able to be manipulated and now includes the raw geometrical information of surfaces. With the release of 6.1, the API was now referred to as OpenTD. This paper discusses some of the utilities and capabilities developed using the OpenTD API at the NASA Goddard Space Flight Center. These include utilities to help with configuration control of models and case sets, addition of logic to better process heater performance, and a methodology implemented to allow for submodel level processing of radiation couplings to include smaller radks where needed in a cryogenic region without using the same criteria for the warmer portions of the model. This last utility is targeting a reduction in run time without sacrificing accuracy. Lastly, some lessons learned, work-arounds, and wishes for the next release of the OpenTD API are also presented.

Thermal Desktop↗
NASA NTRS1993

Graphical Operator Interface for Space Telerobotics

This paper addresses potential applications of advanced graphical operator interfaces using graphics and graphical user interfaces in space telerobotic operations. Possible applications are illustrated with examples of graphics visualization displays developed for advanced teleoperation and with an example of an operator interface design developed for remote surface inspection at the Jet Propulsion Laboratory

Telerobotics↗
NASA NTRS2021

Teleoperation and Visualization Interfaces for Remote Intervention in Space

Approaches to robotic manufacturing, assembly, and servicing of in-space assets range from autonomous operation to direct teleoperation, with many forms of semi-autonomous teleoperation in between. Because most approaches require one or more human operators at some level, it is important to explore the control and visualization interfaces available to those operators, taking into account the challenges due to significant telemetry time delay. We consider one motivating application of remote teleoperation, which is ground-based control of a robot on-orbit for satellite servicing. This paper presents a model-based architecture that: 1) improves visualization and situation awareness, 2) enables more effective human/robot interaction and control, and 3) detects task failures based on anomalous sensor feedback. We illustrate elements of the architecture by drawing on 10 years of our research in this area. The paper further reports the results of several multi-user experiments to evaluate the model-based architecture, on ground-based test platforms, for satellite servicing tasks subject to round-trip communication latencies of several seconds. The most significant performance gains were obtained by enhancing the operators’ situation awareness via improved visualization and by enabling them to precisely specify intended motion. In contrast, changes to the control interface, including model-mediated control or an immersive 3D environment, often reduced the reported task load but did not significantly improve task performance. Considering the challenges of fully autonomous intervention, we expect that some form of teleoperation will continue to be necessary for robotic in-situ servicing, assembly, and manufacturing tasks for the foreseeable future. We propose that effective teleoperation can be enabled by modeling the remote environment, providing operators with a fused view of the real environment and virtual model, and incorporating interfaces and control strategies that enable interactive planning, precise operation, and prompt detection of errors.

space robotics↗
NASA NTRS2022

pyCRTM: A Python Interface for the Community Radiative Transfer Model

The Community Radiative Transfer Model (CRTM) is a powerful and versatile scalar radiative transfer model for satellite data assimilation and remote sensing applications. It is implemented as an object-oriented Fortran library, enabling flexible code development and optimal runtime performance on clusters. The downsides of the Fortran interface are a steep learning curve for students and the reduced productivity of users that is typical for static compiled languages, in contrast to dynamic interpreted languages like Python. pyCRTM is a new software framework that directly interfaces the CRTM Fortran data structures and procedures in Python, leveraging both the simplicity and ease of use of Python syntax as well as the flexibility arising from the vast contemporary Python ecosystem. The goal of pyCRTM is to lower the barrier of entry for university students to learn and use the CRTM and to boost the productivity of researchers seeking to create new methods in radiative transfer and data assimilation, or seeking to apply the CRTM to study atmospheric phenomena without having to go through the pre-existing complexity of the CRTM Fortran interface.

Python↗
NASA NTRS2021

Thermoelectric System Economics - The Apex: New Paradigms in Manufacturing and Interface Performance Relationships Driving System Cost Optimizations

Thermoelectric energy recovery systems require cost-optimized designs with high thermal and thermoelectric (TE) performance to surmount common commercialization barriers controlling the acceptance of thermoelectric generator (TEG) systems. Recent work has addressed this requirement with new analytic tools and paradigms that allow integrated TEG cost-performance analysis and optimization. New work herein has identified the existence of optimized TE element design (i.e., TE element length) for minimizing TEG cost and provides design guidelines associated with critical thermal and electrical contact resistance effects and TE manufacturing sensitivities. Once optimum hot-side heat flux criteria are satisfied, this work highlights the tradeoffs between interface resistance effects and manufacturing cost effects in determining optimum-cost TE element lengths, and then quantifies the increase in optimum-cost TE lengths as manufacturing costs become more sensitive to TE element lengths. Optimized TE element design criteria and key non-dimensional design parameters (i.e., [𝐶′′′LTE/𝐶′′], [TE/con], [con/(TE,aveLTE)]) driving the design are presented and explained showing the interdependencies between manufacturing cost parameters and thermal and electrical interface impacts on integrated TE cost-performance analysis and design. Comprehensive TEG system cost-performance relationships clearly demonstrate the two parameters that most greatly impact the TEG system cost are heat exchanger costs ($/(W/K)) and TE hot side heat flux. Reducing heat exhanger cost from $1/(W/K) to $0.5/(W/K) can decrease TEG system cost by $2/W to $4/W depending on TE hot side heat fluxes from 4-10 W/cm2. The impact of TE hot side heat flux on TEG system cost is larger; reducing TE system cost by factors of 2-4 as TE hot side heat flux increases from 4 W/cm2 to high levels around 18 W/cm2. The levels of thermal contact resistance and electrical contact resistance required to even approach the critical TEG system cost level of $1/W are characterized by con = 1.0 x 10-10 -m2 and r = 0.1, respectively. This not only lowers TEG costs, but it also makes the TEG system costs less sensitive to TE manufacturing dependences on TE element length. New design paradigms and relationships create holistic, integrated TE performance-cost models that enhance understanding of crucial interrelationships between component costs, TE design parameters and material properties, heat exchanger design parameters, interfacial heat flux, and now thermal and electrical interface effects in minimizing TEG system costs.

Hendricks, Terry J.↗
NASA NTRSDate not supplied

Cross-Scale and Cross-Interface Processes and Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last 40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C. Taylor↗
NASA NTRS2023

An Interface Specification for Urban Air Mobility Performance Models to Support Air Traffic Management Research

Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.

Trajectory Prediction↗
NASA NTRSDate not supplied

The Importance of Cross-Scale and Cross-Interface Processes on Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last >40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C Taylor↗
NASA NTRS2023

An Interface Specification for Urban Air Mobility Performance Models to Support Air Traffic Management Research

Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.

Trajectory Prediction↗
NASA NTRSDate not supplied

Cross-Scale and Cross-Interface Processes and Arctic Amplification

The Arctic is a dynamic region, demonstrated by its remarkable internal variability and rapid response to anthropogenic climate change over the last >40 years. Actionable predictions and projections hold significant value for managing both natural and human systems. The value of these model outputs only grows in a warmer, less icy Arctic. However, substantial gaps exist in our understanding of cross-scale and cross-interface (air-sea ice-ocean) interactions that limit our predictive capabilities. Studies dating back at least 40 years provide evidence that the evolution of the Arctic climate system is sensitive to these cross-scale and cross-interface interactions. This presentation summarizes our understanding of cross-scale and cross-interface interactions relevant to the Arctic’s response to anthropogenic climate change—Arctic Amplification. The presentation emphasizes the influence of surface-type dependent turbulent flux exchanges of heat and moisture, the rectification of episodic atmospheric heat transport events on time-averaged changes, local and remote feedback interactions, and cross-seasonal energy transfers. The presentation concludes with a summary of knowledge gaps and discusses potential pathways for accelerating our understanding of the Arctic climate system.

Patrick C. Taylor↗
NASA NTRSDate not supplied

Development of the Thermal Interface Between the Dragonfly Mass Spectrometer and the DrACO Sample Delivery Carousel

Icy celestial bodies are an exciting new frontier for surface exploration and in-situ sampling and analysis. These destinations are inherently cryogenic in nature, and each body presents unique challenges related to thermal design. The Dragonfly mission to Titan is one such example. One of the most important requirements of a sampling system is to preserve the integrity of the surface material. The interface between the Dragonfly Mass Spectrometer (DraMS) and the Drill for Acquisition of Complex Organics (DrACO) is complicated by several competing requirements. Development of this interface has required the use of new enabling technologies such as 3D printing to achieve a successful design. This overview of the DraMS Cryogenic subsystem will show how the design meets all the requirements of the interface and preserves integrity of Titan surface samples.

Peter W. Barfknecht↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), is a platform built upon a database of radiation data relevant to space biology. RadLab provides visual and programmatic interfaces for interrogation of its database, as well as a submission process for inclusion of data from investigators. The RadLab application programming interface (API) implements a request syntax enabling users to retrieve data filtered by various combinations of parameters (detector type, location, direction, timespan, etc), which are delivered in machine-readable text formats, ready to be ingested by downstream analysis pipelines; while the graphical user interface (GUI) provides easy means to iteratively modify query parameters and incorporates a number of standard analyses and visualizations (time series plots, geospatial visualizations, detector comparison). Investigators from many countries, including US, Russia, Japan, Canada, the Czech Republic, Germany, Hungary, and Italy, have committed to provide data from their instruments located on the ISS; RadLab will also include data from other spacecraft in LEO (e.g., the Space Shuttle, the Mir space station), BLEO (e. g. BioSentinel, Mars Orbiter, among others), and on other celestial bodies (e. g. Chang’e 4, Curiosity). The first release of RadLab has been made available to the public. Once fully operational, RadLab will provide a comprehensive and ever-growing compendium of space radiation data, facilitating straightforward access to multiple types of readings and enabling space biology researchers to perform intercomparisons of detectors and to determine the radiation environment of research missions, both via programmatic retrieval of these data and via the graphical analysis toolkit; as well as a user-friendly submission portal for ingesting data from space agencies and research institutions. Radiation scientists will be able to use RadLab to gain a deeper understanding of the space radiation environment for future human space exploration. The RadLab Working Group has been formed to foster close collaborations among data contributors and users, to identify data sources, to put in place standards for data normalization, to guide the development of features of the analysis toolkit, to establish the use of RadLab in space radiation biology research, and eventually to provide a forum for discussing relevant research issues that can take advantage of RadLab's capabilities.

radiation↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets of these data. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments, both via programmatic retrieval of these data and through the graphical analysis toolkit. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

radiation↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

database↗