Thursday, November 14, 2024 09:00AM

Master's Thesis Defense

 

Snigdha Nellutla

(Advisor: Dr. Christopher E. Carr)


 

"Optimizing Data Analysis and Aerosol Collection for Venus Atmosphere Exploration Missions"

 

Thursday, November 14 

9:00 a.m.

Montgomery Knight Building 317

 

 

Abstract


The quest to find life beyond Earth has motivated researchers to explore the environmental conditions on other worlds and the limits of chemical complexity, including alternative solvents. Venusian cloud particles are thought to consist predominantly of liquid droplets consisting of concentrated sulfuric acid, H2SO4, but further insights are needed to fully understand the chemical composition of these clouds as well as the potential for organic chemistry. Bulk methods of analysis from early Venus missions, like Venera, Vega, and Pioneer, leave room for confirmation in the compositions and shapes of individual particles and may mask the presence of heterogeneous populations. 

To address this, the Rocket Lab Mission to Venus, scheduled for launch no earlier than January 2025, will deploy a ballistic entry probe equipped with the Autofluorescence Nephelometer (AFN). The AFN measures single-particle light scattering and fluorescence, providing insights into particle size, refractive index, and possible organic material in Venus’s cloud droplets. Due to the power and bandwidth limitations of the transmitter (1000 bps), effective strategies for summarizing the raw data must be developed. A Python-based simulation has been created to model the AFN's expected data, including the number of particles detected, their equivalent optical diameters, refractive indices, and scattering cross sections. The simulation produces both a particle-by-particle data stream that is identical to the AFN’s output as well as a detailed summary sheet for additional context. Comparing both data streams will be critical in testing various summary algorithms to ensure efficient transmission during the mission, and that the most relevant information is successfully conveyed back to Earth. Field tests, additional laboratory studies, and controlled test cases will further enhance the reliability of these algorithms, ensuring preparedness for the Rocket Lab Mission to Venus.

In a complementary project, the exploration of Venus’s atmospheric chemistry continues with efforts to develop an aerosol collection system for a potential sample return mission targeted for the mid 2040’s. While it has often been assumed that organic carbon compounds are unstable in sulfuric acid, recent work suggests this is not the case. Due to the limitations of in-situ analyses, a sample return mission is being contemplated to increase the chances of accurate chemical analysis of Venusian cloud samples. The long-term goal is to develop the best design for aerosol collection systems that could be deployed in the atmosphere of Venus under realistic resource constraints.

This long-term project focuses on a collector derived from Earth-based fog collectors, intended for passive collection during random wind variations experienced by a balloon platform in the Venus clouds. As a precursor to studies utilizing sulfuric acid aerosols, I evaluated aerosol collection using different materials and mesh designs to determine their corresponding collection efficiencies. In this study, different meshes – including fiber meshes, Raschel mesh, kirigami mesh, and steel mosquito meshes – were implemented to collect and condense water vapor emitted from various atomizers. Future work includes experimenting with similar mesh designs in an enclosed chamber but different materials and dimensions, feature sizes, etc., designing a chamber that enables recirculation of emitted aerosols, and testing aerosols other than water vapor that could more closely represent concentrated sulfuric acid, thereby allowing the current methods to be applied to aerosol sampling in the Venus atmosphere.

Together, these two projects – the Rocket Lab probe mission’s in-situ measurements and the sample return mission with aerosol collection – aim to deepen our understanding of Venus’s atmospheric composition. Through a combination of short-term work on refining data simulation methods and long-term work involving experimental development, these efforts will contribute to refining our knowledge of Venusian cloud chemistry, including its potential for organics and carbon cycle processes.

Committee

  • Dr. Christopher E. Carr – School of Aerospace Engineering (advisor)
  • Dr. Álvaro Romero-Calvo – School of Aerospace Engineering
  • Dr. Pengfei Liu – School of Earth and Atmospheric Sciences