2016 RID Awards

PROJECT: Decompaction Effect of Lunar Soil due to Thermal Cycles

PI: Il-Sang Ahn, Assistant Professor, UAF

The proposed research is to investigate the decompaction effect of compacted granular soil due to widerange temperature cycles. This phenomenon will provide a reasonable explanation of sudden changes in the relative density of lunar regolith soil layer observed since the Apollo mission. Furthermore, this phenomenon would be a major cause of significant settlement that can possibly occur to man-made structures on the moon as a result of surface temperature changes. In the proposed research, the bulk density and relative density of a lunar regolith simulant specimen is estimated from compressional wave velocity measurement as the specimen is exposed to a number of thermal cycles. The test results are used to build a temperature ratchet model for particle transfer so that decompaction effect in a long period of time can be quantified.

PROJECT: Motion Planning for Astronauts on Mars with Reduced Gravity and Joint Strength

PI: Yujiang Xiang, Assistant Professor, UAF

The predictive dynamics method developed by the PI and his colleagues is one of the more efficient optimization-based methods to simulate human motion. The major advantage of this method lies in its computational efficiency, because inverse dynamics is used to evaluate and subsequently constrain joint torques (strength) in an optimization iteration process, instead of using a forward numerical integration approach. In addition, this method does not need full motion or force profile histories for all joints as input, which makes it more suitable for use with human motion simulation. The predictive dynamics method has been used successfully to simulate walking, running, box lifting, jumping, stair climbing, and carrying motions and some biomechanical insights have been obtained from these simulations. The purpose of this research is twofold: (1) to study the adaptation of human motion to an environment with reduced gravity and (2) to study the adaptation of human motion to human physics with reduced joint strength, such as astronauts living on Mars. This is the first attempt to apply the predictive dynamics
approach to an environment with reduced gravity for astronauts. We are going to develop a novel model with perfect integration of computational efficiency and accurate environmental and physical information about reduced gravity and joint strength. The inherent robust predictive capability of the approach will be able to show causes and effects of reduced gravity and joint strength. In addition, dynamic ladder climbing will be simulated as an example because ladder climbing is a common task that astronauts perform in daily life. A great deal of useful biomechanics detail will be revealed for astronauts’ dynamic motion planning on Mars.

PROJECT: Use of satellite data to predict near-ground air quality in interior Alaska

PI: Srijan Aggarwal, Assistant Professor, UAF

There are significant air quality challenges in interior Alaska, especially during the cold winters and summer wildfires. This leads to human health impacts because of increased exposure to elevated levels of particulate matter and other pollutants in the air. Additionally, there is insufficient ground-level air quality monitoring to cover the entire state, especially interior rural communities. Several recent advances have been made in the last decade toward utilizing satellite data to estimate levels of near ground, daily mean particulate matter concentrations. Statistical regional models have been proposed for various geographical regions in the United States and internationally. However, no extant study has investigated the performance and ability of satellite monitoring data to estimate air quality in Alaska. This project will leverage existing ground-level air quality data and NASA satellite data from the last
ten years to explore the use of (a) an advanced statistical modeling approach, and (b) a chemical transport modeling approach, toward estimation of near-ground air quality in interior Alaska.

PROJECT: Mapping Sea Ice Features with Aircraft Observations and Undergraduate Student Measurements

PI: Jessica Cherry, Associate Professor, UAF

The proposed effort will add an airborne observational component to an existing undergraduate research program at Barrow, Alaska, expose students to the realm of airborne remote sensing research through lectures and participation, and provide preliminary data for a larger proposal to NASA with a collaborator who is affiliated with NASA through the University of Maryland and maintains an office at Goddard Space Flight Center. The UAF investigator plans to fly an optical camera, twin thermal infrared cameras, and an L-band synthetic aperture radar (SAR) onboard a Cessna 182 that has been modified and FAA-approved for these sensors. These datasets will provide maps of sea ice properties in the Barrow area including the visual landscape (orthomosaic), a digital elevation model of ice ridges, an orthomosaic of thermal properties, and the L-band SAR scene. These will be compared to microclimate measurements collected by the students, including thermal infrared transects using technologies developed at Radford University. The larger proposal developed during the pilot project will focus on scaling thermal anomalies in sea ice landscapes from in situ to satellite remote sensing, using high resolution airborne measurements as a bridge.