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Grogan, Paul

Publications and source records attributed to Grogan, Paul.

5 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Demonstrating a New Flood Observing Strategy on the Nos Testbed

A new observing strategy for floods was demonstrated and evaluated in a testbed environment. The strategy coordinates several observing platforms, including in situ and space based, to observe a flood from multiple vantage points and to dynamically target predicted flood events with high- resolution observations. The coordinated observations were assimilated back into the model to improve forecasts and future observation selection. This demonstration shows the potential for coordinated, model-driven observing strategies and the feasibility of the NOS Testbed for demonstrating and evaluating new observing strategies.

Capra, Leigha↗
NASA NTRS2018

Trade-Space Analysis Tool for Designing Constellations (TAT-C)

While there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSMs), there are currently no tool to help in the design of DSMs. The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. Our Trade-space Analysis Tool for Constellations (TAT-C) allows to investigate questions such as: "Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best cost/risk value?" This paper provides a description of the TAT-C tool and its components.

Image Processing↗
NASA NTRS2016

Trade-Space Analysis Tool for Constellations (TAT-C)

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: How many spacecraft should be included in the constellation? Which design has the best costrisk value? The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time.This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance.TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

Science Data Processing↗
NASA NTRS2016

TAT-C: A Trade-Space Analysis Tool for Constellations

Under a changing technological and economic environment, there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best costrisk value? This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI and formulating Trade-space Search Requests for the Trade-space Search Iterator, which in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules generates multiple potential architectures and their associated characteristics. UI will include Graphical, Command Line and Application Programmer Interfaces to respond to the demands of various levels of users expertise. Science inputs are grouped into various mission concepts, satellite specifications, and payload specifications, while science outputs are grouped into several types of metrics - spatial, temporal, angular and radiometric. Orbit Coverage leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data that are passed to Reduction Metrics. Then, for each architecture design, Cost Risk will provide estimates of the cost and life cycle cost as well as technical and cost risk of the proposed mission. Additionally, the Knowledge Base module is a centralized store of structured data readable by humans and machines. It will support both TAT-C analysis when composing new mission concepts from existing model inputs, and TAT-C exploration when discovering new mission concepts by querying previous results.

Science Data Processing↗