Research Projects Archives - Professor Hamzeh Hajiloo Research /hajiloo/category/research-projects/ ÐÓ°ÉÔ­´´ University Sat, 28 Dec 2024 22:18:24 +0000 en-US hourly 1 https://wordpress.org/?v=6.3.1 GUI for capturing the full load-deflection response of FRCM-strengthened beams /hajiloo/2024/gui-for-capturing-the-full-load-deflection-response-of-frcm-strengthened-beams/?utm_source=rss&utm_medium=rss&utm_campaign=gui-for-capturing-the-full-load-deflection-response-of-frcm-strengthened-beams&utm_source=rss&utm_medium=rss&utm_campaign=gui-for-capturing-the-full-load-deflection-response-of-frcm-strengthened-beams Sat, 28 Dec 2024 22:05:57 +0000 /hajiloo/?p=219 A graphical user interface (GUI) was used in the MATLAB environment. However, the application needs MATLAB Runtime which is a standalone set of shared libraries that enables the execution of compiled MATLAB codes. This can be considered as the limitation of the developed user-friendly application. The main user interface is shown below. The application is able to capture the full load-deflection curve of the strengthened beam using the mechanical and geometrical properties of RC beam and FRCM. Additionally, it calculates stiffness and absorbed energy.

Download the application .

]]> Structural Damage Level of Road Bridges In Fire /hajiloo/2023/structural-damage-level-of-road-bridges-in-fire/?utm_source=rss&utm_medium=rss&utm_campaign=structural-damage-level-of-road-bridges-in-fire&utm_source=rss&utm_medium=rss&utm_campaign=structural-damage-level-of-road-bridges-in-fire Mon, 17 Apr 2023 03:03:37 +0000 /hajiloo/?p=41 Creating software that is easy for users to navigate and incorporates the findings of an artificial neural network is a viable approach for applying the benefits of machine learning in practical situations. Machine learning-based software can provide a more user-friendly interface, allowing users without extensive knowledge of machine learning to leverage its power. Moreover, ML-based software can facilitate the deployment of machine learning models in real-world scenarios, making it easier to integrate with other systems and technologies. The approach of practical implementation of ML in real problems enables engineers to obtain precise results from ANN without having to conduct numerous experiments or perform complicated mathematical calculations. The proposed ML-based software in this study was developed based on C# which is a general-purpose, high-level programming language supporting multiple paradigms. Users can obtain the estimated damage level in a bridge based on the location, material, structural system of a bridge, AADT, ignition source, combustible type, and face of a bridge to which fire is exposed.

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