Award Abstract # 2407176
Collaborative Research: Generalizing Drag Estimation for Rigid and Flexible Vegetation Canopies to Quantify Environmental Processes

NSF Org: EAR
Division Of Earth Sciences
Recipient: UNIVERSITY OF ILLINOIS
Initial Amendment Date: August 13, 2024
Latest Amendment Date: August 13, 2024
Award Number: 2407176
Award Instrument: Standard Grant
Program Manager: Laura Lautz
llautz@nsf.gov
 (703)292-7775
EAR
 Division Of Earth Sciences
GEO
 Directorate for Geosciences
Start Date: August 15, 2024
End Date: July 31, 2027 (Estimated)
Total Intended Award Amount: $281,419.00
Total Awarded Amount to Date: $281,419.00
Funds Obligated to Date: FY 2024 = $281,419.00
History of Investigator:
  • Leonardo Chamorro (Principal Investigator)
    lpchamo@illinois.edu
Recipient Sponsored Research Office: University of Illinois at Urbana-Champaign
506 S WRIGHT ST
URBANA
IL  US  61801-3620
(217)333-2187
Sponsor Congressional District: 13
Primary Place of Performance: University of Illinois at Urbana-Champaign
506 S WRIGHT ST
URBANA
IL  US  61801-3620
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): Y8CWNJRCNN91
Parent UEI: V2PHZ2CSCH63
NSF Program(s): Hydrologic Sciences
Primary Program Source: 01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 157900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

Understanding how aquatic plant canopies interact with flowing water is crucial for many aspects of environmental science, including river habitat restoration, flood management, and sustainable energy solutions. This project focuses on studying the forces that influence the movement and stability of these underwater and emergent canopies. By examining flexible and rigid plant structures in river environments, the researchers aim to uncover the complex interactions between water flow and plant life. The findings will enhance our ability to predict and manage water flow in natural and engineered environments, leading to more effective conservation strategies and improved designs for renewable energy systems. The project also promotes community engagement and education, with efforts to involve students from under-represented communities in STEM through university programs and public outreach activities, including interactive exhibits and public lectures.

The research involves a combination of experiments and numerical simulations to investigate how different types of plant canopies affect water flow and drag forces. Experiments will measure the overall resistance of plant canopies and analyze the flow patterns around them. Advanced flow and object-tracking techniques will be used to capture detailed data on canopy movements and water currents. Numerical simulations will complement these experiments by better understanding local drag forces and drag distribution within canopies. Artificial neural networks will be developed to predict the drag of canopies in various configurations. This project will generate comprehensive datasets to train machine learning models, ultimately leading to a generalized formulation for predicting canopy drag in different environments. The results will be shared through publications, presentations, and a publicly accessible digital repository, contributing to the broader scientific knowledge and practical applications in the field.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Please report errors in award information by writing to: awardsearch@nsf.gov.

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