Composite Laminate Design & Failure Analysis
Design composite laminates and predict failure modes
What You Can Do
You can design multi-ply composite laminates from material specifications and load requirements, automatically calculating effective properties (stiffness, strength, compliance). The skill predicts failure modes using industry-standard criteria (Tsai-Wu, Max Stress, Max Strain, Hashin) and verifies designs against structural requirements, helping you optimize ply orientations to meet performance targets while minimizing weight and cost.
Features
specify plies, orientation angles, and material types to create tailored composite structures
compute equivalent stiffness matrix (Q-bar), compliance, and in-plane/flexural properties for any laminate
apply Tsai-Wu, Max Stress, Max Strain, and Hashin criteria to identify critical failure modes under combined loads
calculate stress components in each ply and layer to diagnose failure initiation and stress concentration
check margins of safety against target stiffness, strength, and thermal stability requirements
suggest ply orientation and count changes to meet structural goals without over-designing
organize and compare multiple loading scenarios (tension, compression, shear, bending, combined)
Example Output
Laminate Design Output
Stacking Sequence: [0/±45/90]s (8 plies)
Material: Carbon/Epoxy (IM7/8552)
Thickness: 1.2 mm | Fiber vol. fraction: 60%
Effective Properties:
Ex = 68.5 GPa | Ey = 12.3 GPa | Gxy = 5.8 GPa
νxy = 0.32 | α11 = -0.1 ppm/°C | α22 = 28 ppm/°C
Failure Prediction (Tsai-Wu Criterion)
Load Case: 500 MPa tension in 0° direction
Critical Ply: Ply 3 (90° fiber)
Reserve Factor: 1.2 ✓ Safe
Failure Mode: Matrix cracking with fiber-matrix debond
Risk: Monitor delamination under fatigue
Optimization Recommendation
Current: [0/±45/90]s → RF = 1.2, Mass = 2.4 kg/m²
Suggested: [0/0/±45/90]s → RF = 1.6 (63% improvement)
Impact: +3% mass, +5% cost, better damage tolerance
What's Included
- SKILL.md: Full composite laminate design assistant with failure prediction and optimization logic
- Material database template: Pre-filled common fiber/resin systems (Carbon/Epoxy, Glass/Epoxy, Aramid/Epoxy) with mechanical and thermal properties
- Laminate design worksheet: Guided prompts for ply selection, orientation specification, and thickness calculation
- Load case catalog: Standard aerospace/automotive scenarios (wing bending, fuselage pressure, torsion, impact)
- Failure analysis checklist: Step-by-step verification using Tsai-Wu, Max Stress, Hashin, and Puck criteria
- Design review template: Structural requirement validation against stiffness, strength, thermal, and manufacturing constraints
- Case studies: Four worked examples (wing skin, pressure vessel, automotive bracket, sandwich panel)
Who It's For
- Composite & Aerospace Engineers — Design and optimize carbon/glass/aramid laminates for aircraft, spacecraft, and structural components
- Automotive Engineers — Develop composite body panels, suspension arms, battery enclosures, and crash structures
- Materials Engineers — Evaluate composite performance and degradation under multi-axial loads and environmental exposure
- Structural Designers — Verify composite designs against certification standards (FAA, EASA, OEM requirements) and load envelopes
- Manufacturing Engineers — Understand ply-level stress for process optimization, quality control, and design-for-manufacturability
Best For
- Laminate design from scratch — Choose fiber orientation, ply count, and material to meet stiffness and strength targets
- Failure mode prediction — Identify which plies and layers fail first under tension, compression, or combined multi-axial loads
- Design optimization — Compare competing stacking sequences and recommend changes to improve reserve factor or reduce mass
- Structural requirement verification — Confirm a laminate meets target properties (modulus, strength, thermal stability, damage tolerance)
- Load case analysis — Organize and rank multiple failure scenarios (wing bending, fuselage pressurization, impact, fatigue) by risk
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