03 May 2024

New Sustainable Solutions for Retrofitting: Evaluating the Performance of Jute Fiber Nets and Composite Mortar in Natural Fiber Textile Reinforced Mortars

We're thrilled to share the findings of our recent work on evaluating the performance of jute fiber nets and composite mortar in natural fiber textile reinforced mortars. This study not only provides an innovative perspective on integrated retrofitting but also a promising solution for constructing safer and more sustainable buildings.

25 April 2024

Structural Identification from Operational Modal Analysis: The Case of Steel Structures

Exciting News! Our paper titled "Structural Identification from Operational Modal Analysis: The Case of Steel Structures" is now available! We're thrilled to introduce our innovative methodology for structural identification using OMA, featured in this paper. By minimizing the disparity between experimental and theoretical eigenfrequencies, through simulated annealing, we've unlocked a powerful tool for enhancing structural knowledge while minimizing any potential impact on the structure itself and its operations.

19 April 2024

Jute fiber-reinforced mortars: mechanical response and thermal performance

Enhancing energy efficiency and structural capacity are the main objectives of masonry retrofitting. Find out how we achieved a dual positive effect by improving both thermal insulation properties and structural behavior of composite building materials using #jute #fibers. #sustainability always in mind. Learn more about our study and the results achieved:

16 April 2024

Enhancing Industrial Safety Against Explosions

About This Paper: Leveraging the deterministic Single-Degree-of-Freedom (SDOF) model founded on Donnell shallow-shell theory, our study advances this model by integrating a novel correction term. This term significantly refines the model's accuracy by compensating for the oversimplifications inherent in the SDOF model. Utilizing Bayesian inference, we meticulously estimate unknown parameters within the correction term and model error. This synthesis not only incorporates predictions from the SDOF model but also aligns them with experimental data and prior information.

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