Aly Mousaad Aly

Associate Professor Louisiana State University

  • Baton Rouge LA

Dr. Aly is revolutionizing resilient infrastructure via pioneering AI-enhanced large-scale wind engineering and control for extreme weather.

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Louisiana State University

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Biography

Dr. Aly Mousaad Aly is an Associate Professor at Louisiana State University, where he serves as the founding director of the Windstorm Impact, Science, and Engineering (WISE) research and education program. His research endeavors focus on advancing wind engineering, structural dynamics, and control systems to develop more resilient, economically sustainable, and recoverable infrastructure, thereby enhancing safety and mitigating the substantial costs associated with rebuilding after windstorms and earthquakes. Dr. Aly’s expertise includes pioneering advanced wind testing methodologies, utilizing the LSU WISE Open-Jet Testing facility to simulate full-scale wind loads, and making seminal contributions to the implementation of smart dampers in super-tall structures and the development of a novel probabilistic theory for semi-active damping systems. His academic achievements include a publication record of 71 peer-reviewed journal articles, two edited books, one patent, four book chapters, and numerous conference proceedings and presentations, underscoring his commitment to fostering safer, more sustainable urban environments through innovative engineering solutions.

Areas of Expertise

Wind Engineering
Structural Dynamics
Resilient Infrastructure
Computational Fluid Dynamics
Machine Learning
Fluid-Structure Interaction
Smart Structures
Disaster Mitigation

Research Focus

Wind Engineering & Structural Dynamics

Dr. Aly’s research focuses on wind engineering and structural dynamics, assessing how extreme winds affect buildings, bridges, solar arrays, and other coastal infrastructure. He integrates wind-tunnel and open-jet experiments, CFD simulations, and smart structural-control strategies to quantify loads and design cost-effective, wind-resilient systems.

Accomplishments

LSU Alumni Association Rising Faculty Research Award

2017

AISC Advancing Structural Steel Education Award, American Institute of Steel Construction

2023

ASCE Outstanding Civil Engineering Educator Award, American Society of Civil Engineers (Baton Rouge Branch)

2017

Education

Florida International University & Western University

Postdoctoral Research Fellow

Civil Engineering

2013

Focus: Wind Engineering

Politecnico di Milano

Ph.D.

Mechanical Engineering

2009

Specialization: Applied Mechanics, Wind Engineering, Structural Dynamics

Alexandria University

M.Sc.

Mechanical Engineering

2005

Focus: Structural Dynamics, Seismic Response Reduction

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Media Appearances

Hold that Tiger! Inside LSU’s Category 4 Hurricane Wind Machine

MSN  online

2024-05-31

WGNO Good Morning New Orleans features reporter Bill Wood wants you to meet Aly Mousaad Aly.

He got his PhD studying how high rise buildings hold up in a storm.

With help from four jet engine-sized super fans, the professor actually created a Category 4 hurricane. That’s up to 156 miles an hour.

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LSU professor studying ways to protect infrastructure from natural disasters

Greater Baton Rouge Business Report  online

2021-10-18

When Hurricane Ida swept through Louisiana in early fall, hundreds of thousands were left without power while others were left without homes as the storm took out power lines and vulnerable structures…

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Articles

Open-jet testing: Investigating turbulence and geometric scale effects on surface pressures in the atmospheric boundary layer

Physics of Fluids

2024

Bluff body aerodynamics is essential for the design and safety of structures exposed to wind forces. Traditional atmospheric boundary layer wind testing often fails to replicate the complex turbulence characteristics of real-world flows, necessitating innovative testing methodologies. We developed an open-jet testing approach and conducted experiments on scaled models (1: 7.6 and 1: 10) at Reynolds numbers ranging from 0.5× 10 6 to 1× 10 6, significantly higher than those typically achieved in conventional testing. This methodology produced integral length scales approximately ten times larger than those observed in traditional methods, resulting in 25%–300% higher peak pressures than those from small-scale tests, closely aligning with full-scale field data.

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Deep learning-based eddy viscosity modeling for improved RANS simulations of wind pressures on bluff bodies

Journal of Applied Fluid Mechanics

2024

Accurate prediction of wind pressures on buildings is crucial for designing safe and efficient structures. Existing computational methods, like Reynolds-averaged Navier-Stokes (RANS) simulations, often fail to predict pressures accurately in separation zones. This study proposes a novel deep-learning methodology to enhance the accuracy and performance of eddy viscosity modeling within RANS turbulence closures, particularly improving predictions for bluff body aerodynamics. A deep learning model, trained on large eddy simulation (LES) data for various bluff body geometries, including a flat-roof building and forward/backward facing steps, was used to adjust eddy viscosity in RANS equations. The results show that incorporating the machine learning-predicted eddy viscosity significantly improves agreement with LES results and experimental data, particularly in the separation bubble and shear layer. The deep learning model employed a neural network architecture with four hidden layers, 32 neurons, and tanh activation functions, trained using the Adam optimizer with a learning rate of 0.001.

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A review of agrivoltaic systems: addressing challenges and enhancing sustainability

Sustainability

2024

Agrivoltaics is a relatively new term used originally for integrating photovoltaic (PV) systems into the agricultural landscape and expanded to applications such as animal farms, greenhouses, and recreational parks. The dual use of land offers multiple solutions for the renewable energy sector worldwide, provided it can be implemented without negatively impacting agricultural production. However, agrivoltaics represent a relatively new technology, facing challenges including economic viability, vulnerability to wind loads, and interference with growing crops. This paper reviews the recent research on integrating agrivoltaics with farming applications, focusing on challenges, wind impact on agrivoltaics, and economic solutions. The effect of agrivoltaics on temperature control of the lands is a critical factor in managing (1) water and the soil of the land, (2) animal comfort, and (3) greenhouse productivity, positively or negatively.

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Event Appearances

Enhancing Structural Resilience: A Breakthrough in Wind Engineering through Open-Jet Testing

2025 | 15th Americas Conference on Wind Engineering  St Charles, MO

Enhancing Wind Resilience in Photovoltaic Systems: Experimental/Computational Efforts

2024 | ASCE Engineering Mechanics Institute (EMI) Conference  Chicago, IL

Resilient Coastal Infrastructure: Mitigating Windstorm Impacts and Empowering Vulnerable Communities

2024 | 28th Joint Engineering Societies Conference  Lafayette, LA

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Patents

Overheight vehicles impact avoidance and incident detection system

US12049233B2

A system and method are disclosed for overheight vehicle impact avoidance and incident detection. A detection subsystem of the system determines whether an incoming vehicle is clear to pass, depending at least on its height. The detection subsystem relies on distance sensors located along the freeway to detect the highest point of the vehicle and outputs an indication of whether the vehicle can pass. A warning subsystem receives the indication that a vehicle is overheight and provides a warning indication to the driver about the vehicle's inability to pass an upcoming structure. The warning subsystem may also perform a variety of other tasks, such as, for example, logging a variety of information about the vehicle and the incident, sending data about the incident locally to a central command, and generating reports.

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