Computational Science Investigation of Material Mechanics

A forensic engineer investigates the cause for unacceptable performance (e.g. collapse) of a structure.

Key tasks are:

• collect evidence
• analyze evidence
• establish failure hypothesis
• validate/reject failure hypothesis
• conclude and report

1. Define the failure

2. Collect the evidence

3. Analyze the evidence

4. Establish possible root causes for the failure

5. Validate the hypothesis through structural analysis

6. Arrive at a conclusion regarding the cause(s)

7. Prepare the final report

Objective:

• Forensic: determine root cause for structural failure (Inverse problem)
• Design: make plans to build a structure (Forward problem)

Assumptions vs Evidence:

• Forensic: uses evidence to test various failure hypotheses
• Design: needs assumptions to design

Based on evidence --> tries to guess what happened
Based on assumptions --> tries to guess what is going to happen

(45-55%)   Design errors

(20-30%)   Construction defects

(5-10%)     Material deterioration / maintenance

Catastrophic events or overload

Human Factors for Failures:

• Negligence: Disregard of codes
• Incompetence: Failure to understand fundamental principles
• Ignorance: Failure to follow design and construction doc
• Greed: Intentional disregard of requirements and safe practice
• Disorganization: Failure to establish clear responsibilities
• Miscommunication: Failure to communicate between parties
• Group thinking: based on a common desire not to upset the balance of a group of people
• Misuse, abuse, neglect: Use and operation beyond its intent; lack of maintenance

Genua brücke

Use actual values for geometry, material, and load instead of design values.

For design, you aim to remain below a critical value --> which results in mostly linear behavior

For failure, you need to determine what happens beyond this critical value --> highly non-linear

1. Physical problem statement: describe the physical properties to model

2. Mathematical problem statement: translate the physics into mathematics to solve it

3. (Numerical) Solution of problem: find the exact or approximate solution to the problem

Then evaluate the model (e.g. compare it to actual data) and refine it if required.

Analytical or numerical (approximate) solutions.