Search NASASearch

Engineering topics

Madzunkov, Stojan

Publications and source records attributed to Madzunkov, Stojan.

Cupid's Arrow: An Innovative Nanosat to Sample Venus' Upper Atmosphere

In NASA's Discovery 2014 AO, the opportunity to propose a Technology Demonstration Opportunity (TDO) to enhance the primary mission was specified. For the Venus Emissivity, Radio Science, InSAR, Topography, and Spectroscopy (VERITAS) mission, we elected to include the Cupid's Arrow nanosat TDO to sample and measure the abundances of noble gases and their isotopic ratios in Venus's upper atmosphere below the homopause. This paper will provide a basic overview of the VERITAS mission, with a focus on the Cupid's Arrow concept including a description of the mission, spacecraft design, and JPL's quadrupole ion trap mass spectrometer (QITMS) instrument specifications and design. In previous planetary entry probe mission designs, particularly at Venus, engineers w ere focused on entry and descent. A landed probe was also proposed for the New Frontiers SAGE mission. For Cupid's Arrow, the nanosat is designed to skim through the upper atmosphere, just below the homopause, in order to sample the atmosphere, perform the analysis, and then exit the atmosphere to transmit its data to the orbiting VERITAS spacecraft. Cupid's Arrow is a compelling addition to the VERITAS geology mission. A key missing link in our understanding of Venus' evolution is the noble gas abundances and their isotopic ratios. Not since Pioneer Venus have these measurements been made in the Venus atmosphere and never in the upper atmosphere, just below the homopause, to the degree of accuracy that will be accomplished by VERITAS' Cupid's Arrow nanosat.Such measurements were ranked as the number 1 investigation of the number 1 objective of the goal "Atmospheric Formation, Evolution, and Climate History ".

Discovery

Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse

To satisfy the Major Constituents Analysis (MCA) requirements for the Vehicle Cabin Atmosphere Monitor (VCAM), this software analyzes the relative abundance ratios for N2, O2, Ar, and CO2 as a function of time and constructs their best-estimate mean. A histogram is first built of all abundance ratios for each of the species vs time. The abundance peaks corresponding to the intended measurement and any obfuscating background are then separated via standard peak-finding techniques in histogram space. A voting scheme is then used to include/exclude this particular time sample in the final average based on its membership to the intended measurement or the background population. This results in a robust and reasonable estimate of the abundance of trace components such as CO2 and Ar even in the presence of obfuscating backgrounds internal to the VCAM device. VCAM can provide a means for monitoring the air within the enclosed environments, such as the ISS (International Space Station), Crew Exploration Vehicle (CEV), a Lunar Habitat, or another vehicle traveling to Mars. Its miniature pre-concentrator, gas chromatograph (GC), and mass spectrometer can provide unbiased detection of a large number of organic species as well as MCA analysis. VCAM s software can identify the concentration of trace chemicals and whether the chemicals are on a targeted list of hazardous compounds. This innovation s performance and reliability on orbit, along with the ground team s assessment of its raw data and analysis results, will validate its technology for future use and development.

Mandrake, Lukas

Major Constituents Analysis for the Vehicle Cabin Atmosphere Monitor

Vehicle Cabin Atmosphere Monitor (VCAM) can provide a means for monitoring the air within enclosed environments such as the International Space Station, the Crew Exploration Vehicle (CEV), a Lunar habitat, or another vehicle traveling to Mars. The software processes a sum total spectra (counts vs. mass channel) with the intention of computing abundance ratios for N2, O2, CO2, Ar2, and H2O. A brute-force powerset expansion compares a library of expected mass lines with those found within the data. Least squares error is combined with a penalty term for using small peaks.

Mandrake, Lukas