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I'm thrilled to share our research: "Physics-based probabilistic demand model and reliability analysis for reinforced concrete beams under blast loads," published in Engineering Structures.

What’s this about?
Our study introduces a physics-based probabilistic demand model tailored for analyzing the reliability of reinforced concrete (RC) beams under blast loading. The model incorporates governing physical laws from structural dynamics, enhanced by a correction term and a model error, to ensure accurate and unbiased predictions.

Key Contributions:

Combines the generalized single-degree-of-freedom (SDOF) representation with Bayesian inference for robust parameter estimation.

Avoids over-reliance on calibration data by embedding fundamental physical principles.

Evaluates the reliability of RC beams under blast loads, identifying dominant sources of uncertainty for improved risk assessment.

Why is this important?
With growing challenges in designing safe and resilient infrastructure, our work provides a vital tool for engineers and researchers addressing extreme load scenarios.

Explore the full paper here: https://www.sciencedirect.com/science/article/pii/S0141029621010804?via%3Dihub

Your insights and citations would be greatly appreciated to further the dialogue and development in this critical area of structural engineering.

#StructuralEngineering #BlastLoads #ReinforcedConcrete #PhysicsBasedModels #ReliabilityAnalysis #EngineeringResearch #BayesianInference #ExtremeLoads #ResilientDesign