Laboratory Characterization of Unsteady Boundary Layers

The study of waves and their effects on mean flow and turbulence in natural water bodies is an important issue for applications in aquatic biology, coastal engineering, sediment transport and hydrodynamic of the lake. These waves result in the generation of an oscillatory (Stokes) boundary layer near the bottom of the water column. The goal of this study was to conduct various experiments that will be used to characterize the turbulence in unsteady boundary layers and help understand the relation between various flow variables (e.g. wave amplitude, frequency, water depth, turbulent kinetic energy, etc.). Using the research facilities provided, three different types of waves were generated. Turbulence characteristics of purely oscillatory waves from a large wave basin are analyzed for unsteadiness time scales. In a smaller water flume, data was obtained for mean currents alone as well as waves plus currents combined. For the latter scenario, the flow was decomposed into vectorial components and characterized for turbulent features. The results are compared to theoretical profiles derived by simplifying the Navier Stokes equation in each of the three experimental conditions and plotted using MATLAB. The obtained models have been applied to model turbulence enhancement for mussel clearance models in Great Lakes, with the potential for further modelling of natural environments. Moreover, there is vast scope of research in this area to understand how the surface roughness affects the effects of surface roughness on apparent roughness and boundary layer height in unsteady boundary layers

Why this Flip Wasn\u27t a Flop: What the Numbers Don\u27t Tell You About Flipped Classes

This paper details the conversion of a large, required Civil Engineering fluid mechanics course into a more student-centered, active learning-oriented course through the flipping of one lecture per week. In the flipped class, students collaboratively solve homework problems in groups while receiving “expert” feedback from instructors and TAs. To offset the lost lectures, some course material that has been delivered in traditional lectures has been placed online in the form of short videos and textbook readings, with low-stakes quizzes for assessment. Student learning gains were quantitatively assessed by comparing quiz and final exam scores for three semesters (1 pre-flip and 2 post-flip). To maintain some element of consistency across the course transformation, a comprehensive, multiple-choice final exam has served to provide quantitative metrics on which the course improvement can be gaged. In addition, quiz questions remained relatively similar across semesters. One-way ANOVAs revealed a statically significant difference on quiz performance, with post-flip students performing better than those in pre-flip semesters. In addition, students in the final iteration of the course transformation significantly outperformed previous students on final exams by about 7%. Taken together, the numbers suggest that the process of flipping a large fluid mechanics course is associated with small but positive improvements to quiz and final exam performance. However, it is best to rely on other indicators beyond course performance in order to more accurately depict the impact of a course transformation. To supplement the results of the quantitative analyses, student comments about the course and instructor observations of the transformation implementation were assessed. Students found the work sessions to be very effective, enjoyed collaborating with peers and the instructor, and thought the online videos were helpful. The instructor indicated that the benefits of the flipped class include the following: heightened student engagement during class periods; greatly increased instructor awareness of student perceptions, challenges, personal issues, and conceptual bottlenecks; eventual reduction in instructor preparation time; improved instructor-student relationships; and a better focus on more important course objectives

Deep-Water Near-Bottom Turbulence in Lake Michigan: An Underwater Investigation

Motivated by a need to characterize near-bottom deep-water turbulence for an understanding of the filtration capabilities of invasive quagga mussels, an instrument tripod was deployed in Lake Michigan for six months in 60m of water to measure current velocities, with specific interest being paid to near-bottom (0.10 to 0.95 meters above bottom) velocities during the deployment. The deployment period (September 2012-April 2013) was characterized by very little stratification and a median temperature of about throughout the water column. A mean horizontal velocity of 3.6 cm/s with a standard deviation of 2 cm/s was also measured at 1 meter above the lake bed. In spite of the 60m depth of the measurement site, surface waves were found to influence near-bottom velocities for a significant fraction of the time, with periods between 6.5 and 12.5 seconds. Fluctuations in velocity were used to quantify turbulence through the use of turbulent kinetic energy (tke) calculations, while simple spectral analysis was used to verify tke levels and identify possible wave contamination. At distances greater than 500 z+ from the bed, turbulent kinetic energy levels follow canonical scaling with values of approximately 5. However, very near-bottom tke levels are greatly elevated relative to the expected values, which we speculate may be due to mussel-induced currents. These conclusions coupled with further modeling will allow for the development of mussel-influence models that will prove important to understanding the impact of these invasive species

A Machine Learning Framework for Extending Wave Height Time Series Using Historical Wind Records

This study presents a novel machine learning-based framework that utilizes the ConvLSTM-1D model to extend the hindcast of wave height time series by leveraging historical wind records. This approach was applied to Lake Michigan by incorporating wind data from multiple Automatic Surface Observation Systems (ASOS) stations as input features. A wave height time series from the Wave Information System model (WIS) served as the training, validation, and testing dataset for the proposed model. Several models were developed, considering different numbers of wind stations, revealing the importance of incorporating stations with variable distances and orientations to enhance prediction accuracy. Notably, the improvement in the model performance plateaued after a certain number of stations, underscoring the importance of selecting an optimal number of wind stations. Additionally, an ensemble learning technique was employed to combine multiple models, resulting in further enhancements in prediction accuracy. The developed model added 30 years of wave height predictions to the existing time series, expanding it by 70% which allows insights into the long-term wave climatology of the Lake Michigan. This framework offers a promising avenue for utilizing historical wind records worldwide to extend wave height time series, in turn improving coastal resilience and coastal management plans

A Wind-Derived Upwelling Index for Lake Michigan

Coastal upwelling is a phenomenon that occurs along coastlines throughout the world, and has been shown to be strongly correlated with large fish populations in these areas. Coastal upwelling occurs when strong coastal winds drive water transport away from the coast, causing colder, often nutrient-rich water to upwell in its place. While coastal upwellings can be detected with satellite imagery or in situ temperature measurements, these datasets are neither continuous nor long-term. A wind-derived upwelling index was created for Lake Michigan to continuously quantify upwellings over multiple decades, and to allow for further understanding of the impact of upwelling in the Great Lakes region. Following work on oceanic upwelling, directional upwelling indices were calculated by taking wind velocity data from both buoys and land stations in Lake Michigan and estimating the off-shore transport of water as predicted by standard dynamical arguments (Ekman transport). Indices were calculated on episodic, daily, monthly, and seasonal timescales. The calculated indices were then validated with direct metrics of upwellings, including in situ water temperature and velocity data and satellite-derived sea surface temperatures (SST). The results of these validations show that there is a strong qualitative correlation between the upwelling index model and the other sources of data, suggesting that the wind-derived index is a robust metric of coastal upwelling, at least for Muskegon. Historical calculations of interannual variability in the derived upwelling index show that the Muskegon coast is downwelling favorable for the middle of the year, but can vary greatly from year to year in magnitude. Future work will include validation of additional locations in Lake Michigan in order to provide a more complete picture of upwelling in the lake

Full-Water Column Turbulence Parameterization of Stratified Waters in Southern Lake Michigan

Full water column mean flow and turbulence structure was characterized at two stratified locations in Lake Michigan (a. Muskegon, MI; b. Michigan City, IN) in order to better understand the filtration potential of invasive quagga mussels. Invasive quagga mussels in Lake Michigan are filter feeders and can dramatically alter clarity as well as the biological/chemical characteristics of the water column. This filtering capacity is highly contingent on turbulence characteristics throughout the water column, which is poorly understood in the Great Lakes. Using velocity, temperature, and turbulence data collected from these locations, the structure of the water column turbulence was modeled for site (a) using data from 2011 and measured for site (b) in 2017. The data from 2017 was collected as a test run of a new acoustic Doppler current profiler, the Nortek Signature500, that will be utilized in future experiments on Lake Michigan. This data was analyzed to better characterize the turbulence structure of Lake Michigan and how it is affected by wind events and wave trends. Using power spectra and turbulence structure function, the turbulent kinetic energy dissipation of the full water column was analyzed from these two locations. This analysis provides insight into the turbulence structure of the full-water column in a stratified lake and will be utilized to prepare for the execution of future sampling events in Lake Michigan

Velocity Profiling, Turbulence, and Chlorophyll Concentrations in the Bottom Boundary Layer of Lake Michigan near Muskegon, Michigan

The characterization of water flow and turbulence near lake beds is important for modelling environmental and ecological effects throughout a lake. In Lake Michigan, where invasive filter-feeding Quagga mussels dominate the lake bed, turbulence plays an important role in determining how much of chlorophyll is mixed down to the Quagga Mussels. Deep in Lake Michigan (44m) near Muskegon, MI, a large tripod was deployed, attached with an Acoustic Doppler Velocimeter, a fluorometer to measure chlorophyll concentrations, and a temperature sensor. Measurements were recorded from late May until early August by sampling velocities every hour in ten-minute bursts at 4 Hz, and sampling temperature and concentration approximately every minute, continuously. Several important turbulent parameters were calculated using the data collected. Chlorophyll data from the site showed that the water column here displayed a Concentration Boundary Layer (CBL), in which the chlorophyll concentration increases as distance from the lake floor increases. The median speed (U = 2.85cm/s) and Turbulent Kinetic Energy (TKE = 2.1 x 10-5 m2/s2) were also calculated. All of these results have previously had very little documentation in such deep waters. The observation of a CBL shows that the invasive Quagga Mussels are able to drastically alter chlorophyll concentrations near the lake floor, an important result for future modeling efforts. The quantification of turbulence parameters will be useful in further studies to find causation between various turbulence levels and concentrations

Lateral dispersion of dye and drifters in the center of a very large lake

To better understand lateral dispersion of buoyant and nonbuoyant pollutants within the surface waters of large lakes, two lateral dispersion experiments were carried out in Lake Michigan during the stratified period: (1) a dye tracking experiment lasting 1 d; and (2) a drifter tracking experiment lasting 24 d. Both the dye patch and drifters were surface‐released at the center of Lake Michigan’s southern basin. Near‐surface shear induced by near‐inertial Poincaré waves partially explains elevated dye dispersion rates (1.5–4.2 m2 s−1). During the largely windless first 5 d of the drifter release, the drifters exhibited nearly scale‐independent dispersion (K ∼ L0.2), with an average dispersion coefficient of 0.14 m2 s−1. Scale‐dependent drifter dispersion ensued after 5 d, with K ∼ L1.09 and corresponding dispersion coefficients of 0.3–2.0 m2 s−1 for length scales L = 1500–8000 m. The largest drifter dispersion rates were found to be associated with lateral shear‐induced spreading along a thermal front. Comparisons with other systems show a wide range of spreading rates for large lakes, and larger rates in both the ocean and the Gulf of Mexico, which may be caused by the relative absence of submesoscale processes in offshore Lake Michigan.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154278/1/lno11302_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154278/2/lno11302.pd

A year of internal Poincaré waves in southern Lake Michigan

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95363/1/jgrc12491.pd

Adventures in Paragraph Writing: The Development and Refinement of Scalable and Effective Writing Exercises for Large-enrollment Engineering Courses

Adventures in paragraph writing: the development and refinement of scalable and effective writing exercises for large enrollment engineering courses. The ability to communicate effectively is a highly desirable attribute for today’s graduating engineers. Additionally, the inclusion of communication components in technical courses has been shown to enhance learning of technical content and can be leveraged to satisfy non-technical learning outcomes. However, the incorporation of such components in undergraduate engineering curricula remains challenging due to resource limitations, credit hour crunches, and other issues. This paper presents the design considerations and preliminary results from our ongoing work to create an effective, transferrable, low-overhead approach to paragraph writing exercises suitable for inclusion in any large engineering course. Key considerations in the development of these exercises include: identification of the motivations and learning outcomes for each exercise; development and tailoring of writing prompts (questions) appropriate for these outcomes; and the development and implementation of an assessment and feedback strategy,including resource-efficient grading rubrics and techniques.Results are reported from the application of the paragraph writing exercise in a large civil engineering undergraduate fluid mechanics course (120 students; approximately 15 assignments). A primary focus of this first application centered on two key components that must be refined in order for the exercise to be effective and transferrable: (1) the selection of writing prompts, and (2) assessment and feedback. Analysis of student paragraphs highlights the importance of the writing prompts in the success of the exercise, indicating that specific word choice, question focus, and supplemental instruction greatly affected the level of writing students submitted. Some writing prompts were selected to address and enhance technical content in the course, while other writing prompts were developed to broaden student awareness of engineering in societal, environmental, and global contexts. In addition to developing productive writing prompts, the assessment and feedback strategies were evaluated using student surveys and feedback. While minimal marking and holistic rubric assessment methods proved effective from a grading resource standpoint, students were frustrated by the lack of feedback associated with these techniques and uncomfortable with the holistic grading rubric. Data from student surveys point to the importance of giving meaningful feedback to students, and providing them with opportunities to revise their written submissions. Student surveys also highlighted an unforeseen obstacle to the exercise: student resistance to writing in technical courses. We provide several suggestions for overcoming student resistance, as well as improved assessment and feedback strategies that better meet student needs while still not over-burdening instructors and teaching assistants