Dwelling Beyond: Sustainable Design On Mars

In 1620, over the course of 66 days, 102 passengers called the Mayflower their home before arriving and settling in Plymouth, New England. In the years following the Louisiana Purchase of 1803 nearly 7 million people traversed extreme wilderness in covered wagons to found and settle the American West. This year, 2015, the first spaceport has opened in anticipation of sub orbital space flights in 2017 and manned settlement flights to mars by 2026. This thesis explores the questions: In this next phase of human exploration and settlement, what does it mean to dwell beyond earth? What are the current architectural limitations regarding structure and material sustainability? And, How can architecture elevate the traditionally sterile environments of survival shelters to that of permanent dwellings?

DEVELOPMENT OF AN OFF-LINE RAINFLOW COUNTING ALGORITHM WITH TEMPORAL PARAMETERS AND DATA REDUCTION

Rainflow counting methods convert a complex load time history into a set of load reversals for use in fatigue damage modeling. Rainflow counting methods were originally developed to assess fatigue damage associated with mechanical cycling where creep of the material under load was not considered to be a significant contributor to failure. However, creep is a significant factor in some cyclic loading cases such as solder interconnects under temperature cycling. In this case, fatigue life models require the dwell time to account for stress relaxation and creep. This study develops a new version of the multi-parameter rainflow counting algorithm that provides a range-based dwell time estimation for use with time-dependent fatigue damage models. To show the applicability, the method is used to calculate the life of solder joints under a complex thermal cycling regime and is verified by experimental testing. An additional algorithm is developed in this study to provide data reduction in the results of the rainflow counting. This algorithm uses a damage model and a statistical test to determine which of the resultant cycles are statistically insignificant to a given confidence level. This makes the resulting data file to be smaller, and for a simplified load history to be reconstructed.