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Bryan W. Welch

Publications and source records attributed to Bryan W. Welch.

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2025

Code Migration and Optimization for Calculating Atmospheric Attenuation in RF Link Budgets Within Glenn Research Center Communication Analysis Suite

This technical report encompasses development completed on the Glenn Research Center Communication Analysis Suite (GCAS) as it relates to converting code from the original MATLAB® (The MathWorks, Inc.) GCAS code base to C++. It focuses on a majority of the functions, structures, and intermediate code developed for radiofrequency (RF) links calculations. The report serves as a comprehensive record of the current progress and outlines the technical challenges overcome during this research. Throughout this project, numerous functions and structures were migrated end to end, with validation test cases conducted in accordance with NASA’s verification and validation efforts for standard models and simulations. This report also provides high-level documentation of the completed work; detailed low-level documentation has been compiled to provide a line-by-line explanation in alignment with NASA’s goals. This development has largely been focused on atmospheric effects on calculating RF link budgets for both terrestrial and space links. Some developments outside of atmospheric functions are also covered throughout this report; these are largely related to mathematical operations and MATLAB® structure conversions.

Brady M. Phelps↗
NASA NTRS2024

Improvements to GCAS Visualization Functionality

Analysis of communication systems is crucial to NASA objectives, whether located here on Earth or on a cosmic scale. The Glenn Research Center Communication Analysis Suite (GCAS) is software designed for analysis of communication systems throughout the solar system. This suite includes web-based visualization software that is used to simulate the data generated from the GCAS MATLAB® (The MathWorks, Inc.) capability. This report focuses on recent additions to the visualization portion of GCAS, including the motivation and methodology behind them. Notable additions include improved camera controls, such as novel first- and third-person settings, methods for displaying pertinent analysis information, finer control over timing mechanisms, and automated features designed to improve efficiency and memory usage.

Visualization↗
NASA NTRS2024

GCAS Visualization Codebase Augmentation Migration to Modern Standards and Feature Enhancements

The Glenn Research Center Communication Analysis Suite (GCAS) includes many analysis tools that can be used to support a wide range of scenarios. It includes a visualization tool that implements the three.js graphics library to display a three-dimensional (3D) representation of its results. This software will enable researchers, engineers, and mission planners to interact intuitively with and understand the results of their analyses, which might not be apparent from raw data. With NASA’s efforts to return humans to the Moon as a part of the Artemis missions, the GCAS has been used extensively for lunar terrain and landing system development analysis, which is vital to ensuring mission achievability and safety. This has created the need to add several significant features to the visualization tool, such as the ability to display the terrain of the lunar surface accurately and to provide information demonstrating how a given region might impact mission objectives. Many of the changes made to the visualization tool can be separated into one of three general advancements: code restructuring to adhere to modern coding standards and practices, new user camera controls for first-person and third-person perspective views, and a terrain generation feature to enable rendering highly accurate terrains based on any celestial body’s digital elevation model (DEM) in GeoTIFF format. These improvements notably elevate the visualization tool's functionality, accuracy, and user interaction while providing a robust foundation for future development.

Visualization↗
NASA NTRS2024

Lunar Terrain Mapping Using 3D Software and Modeling Techniques for the Glenn Research Center Communication Analysis Suite

As NASA prepares to return humans to the Moon as part of upcoming Artemis missions, engineers must examine the surface features and safety of lunar terrain at various locations. The Glenn Research Center Communication Analysis Suite (GCAS) includes visualization tools developed to aid scientists in this quest to comprehend lunar terrain data, as well as spatial communication information. Visual information and understanding will be highly useful to engineers as they use the GCAS to compare the topography of regions of interest for the Artemis III and future space travel missions. Not only can three-dimensional (3D) visualization display the intricacies of the lunar terrain, but it can also demonstrate relationships such as the presence or absence of communication links between Earth ground stations, lunar crew members, and rovers, and the presence of shadows on the lunar surface. In the future, the GCAS has the potential to support the planning of other space exploration missions as well. The emerging possibility of incorporating more planetary bodies becomes especially important as NASA plans not only to return to the Moon but to press onward to Mars.

Visualization↗
NASA NTRS2023

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗
NASA NTRS2023

Dynamically Rendering Rough Terrain with Minimal Memory Overhead

Rendering highly detailed terrain is a process with the potential to consume a great deal of a computer’s random access memory (RAM). In a browser-based application, this resource is limited even further, leading to the necessity to use alternative methods of rendering the large amount of data needed for high detail. This report describes one such method that places the onus of rendering on the speed of the graphics processing unit (GPU) rather than on the computer’s memory. By removing attribute buffers, which contribute greatly to memory costs, from the rendering pipeline and generating the requisite attributes on the fly using a heightmap texture instead, it is estimated that memory usage can be cut down to one-sixth that of the previous method.

Visualization↗
NASA NTRS2023

Spatial Link Coverage Projections for the Glenn Research Center Communication Analysis Suite (GCAS)

Space communications are a fundamental part of every NASA mission, and reliable space communications are essential. Precise planning, simulation, and analysis of communications abilities are needed to know exactly what data rates, visibility times, and signal strength can be expected during the real missions. The goal of this work was to take a 3D icosphere, where each face was a point to be evaluated, and display the link performance onto a 2D projection of celestial bodies for links to a node location that could be spatially located at any of the icosahedral faces. 2D projections were produced for a wide range of spatial link grid sizes and compressed into low-size MAT files for ease of access and rapid implementation. The final icosahedral projections can be displayed onto various celestial body maps, using ultra-high-resolution maps for stitching. The results have proven satisfactory and are planned to support various simulation efforts.

communication link analysis↗
NASA NTRS2022

Optimizing Lunar Map Partitioning for Multipath Fade Loss Analyses

A methodology is presented pertaining to the run-time optimization of quasi-optical ray-tracing simulations. These shooting-and-bouncing ray methods are used for assessing multipath fade loss in cislunar communication links. Our approach employs partitioning lunar terrain maps in shapes that approximate two-dimensional projections of Fresnel zone cross-sections. This technique drastically reduces computational run-time without causing significant loss of simulation accuracy.

Digital elevation models↗