Optimal interpretation of scalar and velocity observations in stratified turbulence
Abstract
The intriguing dynamics of stratified turbulent flows have motivated numerous experiments and simulations. Experiments, in particular field tests, provide valuable data but measurements can be limited in spatio-temporal resolution. As for simulations, while they can directly probe quantities of interest, they often invoke idealizations that can compromise the accuracy of their predictions. Nomatter the approach, once we step beyond canonical configurations, the scarcity of available observations frustrates both experimental and computational researchers alike. These challenges motivate the development of techniques whereby observations are directly infused in simulations of stratified turbulent flows in order to enhance the fidelity of the simulations and augment the spatiotemporal resolution of observations. These techniques start from the available measurements and solve an inverse problem where uncertain parameters in the simulations are optimized to reproduce the available data. The nonlinear optimization is challenging, requires accurate and scalable computational techniques, may admit multiple solutions, and the accuracy of predicting the unknown parameters depends on the type of available measurements and their resolution. Once solved, however, the inverse problem not only provides the optimal interpretation of the sensor data, but the measurement-infused simulations provide access to the full flow beyond the original sensor resolution. In this effort, we apply these measurement-infused simulations techniques to the scalar and velocity fields in stratified turbulence. Surrogate measurements are generated from independent simulations in order to be able to control the data resolution and systematically introduce and evaluate the impact of observation errors. From limited measurements, we will attempt to identify the sources of the scalar release. For passive scalars which do not alter the velocity fields, we will examine the effect of Schmidt number on the accuracy of predicting the source distribution, and will relate the results to the dynamics of the flow. We will also attempt to reconstruct the sources of active scalars, and evaluate the impact of the coupling to the velocity field on the accuracy of the source estimation. When the flow field is the wake of a bluff body in a stratified environment, internal gravity waves are radiated away from the wake. We will reconstruct the flow field using limited observations at progressively larger distances fromthe body and lower resolutions. The minimum spatio-temporal resolution of the measurements that is required in order to predict thefull state will be evaluated and compared to the criterion for isothermal conditions. The same tools that are adopted to solve the inverse problem enable us to address fundamental questions regarding the domain of dependence of an isolated measurement. The proposed effort views sensor data not as a mere record of the measured quantity at a point in space and instant in time, but as an encoding of the antecedent flow events that we decode using the governing equations. The notion of the optimal sensing thus focuses on the ability to most accurately solve the inverse problem.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 09, 2021
- Source ID
- N000142112375
Entities
People
- Tamer A. Zaki
Organizations
- Johns Hopkins University
- Office of Naval Research
- United States Navy