RESEARCH
COMPUTATIONAL FLUID DYNAMIC (CFD) MODELS
Eddy resolving three-dimensional simulations combined with field and laboratory observations allow elucidation of key elements of fluid dynamics and sediment transport in fluvial environments. In this research, I develop a state-of-the-art Computational Fluid Dynamics (CFD) model for the study of sediment transport and morphodynamic processes in fluvial systems. My primary goal is to achieve a deeper understanding of fluid and sediment motion in river systems, and how these motions are represented at different spatial scales. Thus, the developed multi-physics model is capable of predicting sediment transport and bed evolution change, while resolving the energetically important eddies in the flow. The model has been validated in a large-scale canyon-bound river and can be used for a range of applications in water resources over a wide range of scales, from laboratory scales to large rivers. This physically-based model is also used as a prediction tool to understand and forecast the fundamental physics of erosion and deposition processes in river networks including different scenarios that will affect the river morphodynamics. Advances in our understanding of the role played by macro-turbulence events in sediment dynamics provide deeper insights into what determines the geomorphologic change in rivers. The results of this research lead to the development of more efficient models that can be used in lower-order models commonly employed to predict bed evolution in loose bed channels and river reaches (e.g., 3-D Reynolds averaged Navier-Stokes or 2-D depth-averaged models).
Video 1. Detached Eddy Simulation of a 1.4-km transect of the Colorado River along Grand Canyon, Arizona. It is shown instantaneous contours of Q-criterion displayed by the velocity magnitude taken during 1000 seconds of simulation. This three-dimensional eddy-resolving model was developed in OpenFOAM environment.
Video 2. This video is simulated using an eddy-resolving model developed in OpenFOAM. The non-hydrostatic component of the pressure is also shown. The length of mean surface velocity vectors ranges from 0 to 4.5 m/s, and the length of the near-bed velocity vectors is scaled five times
AUTONOMOUS SYSTEMS FOR SCIENCE AND ENGINEERING
Dr. Alvarez has been working on adapting algorithms of path planning for reconnaissance by applying machine learning in the development of autonomous robots, such as autonomous boats, Unmanned Aerial Systems (UAS), and Unmanned Surface Vehicles (USV) to deeply understand water-mediated environments, including bathymetry, flow features, object recognition, and material classifications. This technology can potentially be transferable to other platforms and robots.
Her research has been driven by her own curiosity about how machines can learn to obtain rapid data, infer earth system patterns, and represent complex processes in nature. She aims to innovate the state of the art in contextual modeling to create new methodological frameworks that move the science forward through numerical models and intelligent systems that learn from limited data sets under limited time. Previous AI algorithms, based mainly on statistical representations, are limited in reasoning capability, rely on large data sets for prediction, and sometimes, training data creates maladaptation. She works on novel scientific frameworks where physics-based models are merged with machine learning algorithms to provide solutions to earth science problems. Her goal is to achieve a deep understanding of processes through context adaptation models capable of perceiving, learning, abstracting, and reasoning. These AI models over time can build underlying self-explanations and make decisions that allow them to characterize real-world phenomena and understand why they are making those decisions.
BANK SLOPE STABILITY AND EROSION OF FLUVIAL DEPOSITS USING FULL-SCALED LABORATORY EXPERIMENTS
I study erosion of river sandbars that examines the impact of dam operation criteria on the bank slope stability leading to mass failure through seepage. This research work is developed by means of full-scale laboratory experiments to simulate the sandbar beaches of the Lower Colorado River Basin in Marble and Grand Canyons. Findings reveal that there is no significant correlation between diurnal stage fluctuation caused by the Glen Dam operation criteria and slope stability. The erosion of sandbars with a slope greater than the equilibrium slope is inevitable and after the bars reach the equilibrium slope, mass failure and seepage erosion cease. These findings are essential for decision-makers and scientists to restrict up the ramp and down ramp river stage rates caused by the Glen Canyon Dam operation rule.