Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
Search by expertise, name or affiliation
Data-driven Sensor Placement for Fluid Flows
Palash Sashittal,
Daniel J. Bodony
Grainger College of Engineering
Aerospace Engineering
Mechanical Science and Engineering
National Center for Supercomputing Applications (NCSA)
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Data-driven Sensor Placement for Fluid Flows'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Fluid Flow
100%
Sensor Placement
100%
Proposed Methodology
50%
Modeling Techniques
50%
Computationally Efficient
50%
Challenging Problems
50%
Fluid Dynamics
50%
Noise Measurement
50%
Reduced Order Modeling
50%
Linear Approximation
50%
Gradient Descent
50%
Sensor Location
50%
Unstable Regime
50%
Observer-based Controller
50%
Optimal Sensor Placement
50%
System Noise
50%
Control-oriented
50%
Error Covariance Matrix
50%
Estimation Error Covariance
50%
Ginzburg-Landau Equation
50%
Inclined Flat Plate
50%
Wake Vortex Shedding
50%
Engineering
Fluid Flow
100%
Objective Function
100%
Fluid Dynamics
50%
Illustrates
50%
Estimation Error
50%
Measurement Noise
50%
Feedback Controller
50%
Location Sensor
50%
Flat Plate
50%
Oriented Control
50%
Vortex Shedding
50%
Dimensional Observer
50%
Gradient Descent
50%
Error Covariance Matrix
50%
Mathematics
Objective Function
100%
Minimizes
50%
Covariance Matrix
50%
Linear Approximation
50%
Error Covariance
50%
Adjoints
50%
Flat Plate
50%
Chemical Engineering
Fluid Flow
100%