Engineering topics

Megan E Macdonald

Publications and source records attributed to Megan E Macdonald.

3 records

NASA NTRS2021

Emission Spectroscopy Characterization of Electrodes Species in the Freestream Flow at the NASA Ames Miniature Arc Jet II Facility

The second generation miniature Arc Jet (mARC II) is a subscale arc jet at NASA Ames Research Center that is undergoing initial characterization. During its operation, the electrodes used to produce continuous plasma flows deteriorate and the flow purity decreases. The present work reports the use of optical emission spectroscopy as a characterization tool for impurities in the plasma flow. The discussion is focused on the interpretation of spectroscopic measurements and their evolution under different testing conditions. Special emphasis is given to copper and silver, the main atomic elements of the electrodes. The highest rate of anode deterioration is found to occur during the arc jet ignition, while cathode deterioration is constant throughout the entire run. Based on the experimental spectra, a preliminary numerical characterization of the plasma temperature, enthalpy and number density is conducted.

facility↗

NASA NTRSDate not supplied

Initial Characterization of the 30 kW Miniature Arc Jet (mARC II) at NASA Ames Research Center

The second-generation Miniature Arc jet Research Chamber (mARC II) at NASA Ames is undergoing integrated systems testing. Once fully operational, this facility will be added to the range of available test facilities operated by the NASA Ames Thermophysics Facilities Branch, with primary focus on applications such as new arc jet flow diagnostics and new arc column diagnostics. Initial characterization of the mARC II is reported here, specifically, measured arc current, arc voltage, column and chamber pressures, mass flow rates, and initial emission measurements carried out at a range of conditions.

arc jet↗

NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗