How can you predict the dynamic behavior of bridges more accurately?

2 Experimental testing

Another method for predicting the dynamic behavior of bridges is experimental testing. Experimental testing involves applying controlled loads to a physical model or a prototype of the bridge and measuring its response using sensors and instruments. Experimental testing can validate the results of FEA, identify the sources of uncertainty, and calibrate the parameters of the numerical model. Experimental testing can also reveal the effects of environmental conditions, human factors, and unexpected events that are difficult to simulate in FEA. However, experimental testing can be costly, time-consuming, and limited by the availability and scalability of the test facilities and equipment.

4 Hybrid simulation

A hybrid simulation is a method that combines the advantages of FEA, experimental testing, and AI to achieve more accurate and realistic predictions. A hybrid simulation integrates a numerical model with a physical model or a prototype of the bridge, and uses a feedback loop to synchronize their responses. The numerical model can represent the parts of the bridge that are difficult or impractical to test physically, such as the foundation, the soil, and the adjacent structures. The physical model or the prototype can represent the parts of the bridge that are critical or sensitive to the dynamic loads, such as the deck, the columns, and the bearings. The feedback loop can adjust the loads and displacements applied to both models to ensure their compatibility and equilibrium. AI can assist the hybrid simulation by providing data processing, optimization, and control functions.

5 Sensitivity analysis

A sensitivity analysis is a method that evaluates how the variation of the input parameters affects the output results of the prediction model. A sensitivity analysis can help structural engineers to identify the most influential parameters, quantify the uncertainty and variability, and optimize the design and performance of the bridge. A sensitivity analysis can be performed using different techniques, such as perturbation, regression, correlation, variance decomposition, and Monte Carlo simulation. A sensitivity analysis can also be coupled with other methods, such as FEA, experimental testing, AI, and hybrid simulation, to enhance their robustness and reliability.

6 Verification and validation

The final and essential method for predicting the dynamic behavior of bridges is verification and validation. Verification and validation are processes that ensure the accuracy and credibility of the prediction model and its results. Verification is the process of checking whether the prediction model is implemented correctly and consistently, and whether it satisfies the assumptions and requirements of the problem. Validation is the process of comparing the prediction results with the available experimental or field data, and assessing whether they agree within an acceptable range of error. Verification and validation can be conducted using different criteria, such as consistency, convergence, stability, sensitivity, uncertainty, and error analysis.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?