<p> Mountain Lake is one of only two natural lakes in the state of Virginia. The lake's origin has been attributed to either a natural solution-collapse basin, or to a landslide damming the valley of northwesterly flowing Pond Drain, or to a NW-SE trending fracture lineation. The lake is located within the breached northwest limb of a gently plunging anticline, a part of the larger Valley and Ridge physiographic province. In recent years, the lake drained almost completely, exposing the lake bottom and revealing the presence of four sinkhole-like depressions, containing piping holes at their sides and bottoms, at the northeastern and northwestern margins of the lake. This study focuses on the most likely origin of large sandstone blocks present at the northern end of the lake in an area locally referred to as "Rock City", including mapping of the block locations and analyzing the mode and extent of displacement that they have undergone. An additional objective is to investigate the piping potential of the lake-bottom sediment and its role in seepage out of the lake basin causing lake-level fluctuations. </p><p> Mapping of Rock City was conducted by taking GPS readings at the corners of the rock blocks and using ArcMap Software. Investigations of the displacement mode of the rock blocks was done by comparing the measured orientations of principal discontinuity sets, forming the rock-block boundaries, with discontinuity orientations of undisturbed outcrops within the headscarp, using stereonet analysis. Grain size analysis, Atterberg limits, and a compaction-mold permeameter test were used to evaluate lake sediment's susceptibility to piping. </p><p> Field observations and discontinuity data analysis indicate that Rock City is a landslide that dammed the valley of Pond Drain, consequently forming the lake. The primary mode of slope movement involves lateral spreading that is associated with extension occurring along discontinuities. The Tuscarora Sandstone rock blocks comprising Rock City were detached from the scarp face along a northwest-southeast trending joint set and were displaced laterally towards the west. A seismic event appears to be the most likely triggering mechanism for slope movement. </p><p> Laboratory testing reveals that lake-bottom sediment is susceptible to piping, which is the primary mechanism responsible for the formation of the lake-bed depressions and lake-levels fluctuations. Grain size analysis reveals that lake-bottom sediment consists predominantly of fine sand and silt, both of which are highly susceptible to piping. Results of the compaction-mold permeameter test show that the hydraulic gradient at which lake-bottom sediment starts to pipe, the critical hydraulic gradient, ranges between 1 and 10, depending on the density, grain size distribution and cohesive properties of the sediment.</p>

abstract: Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars. Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona’s Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2017