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International Journal of Scientific and Research Publications

IJSRP, Volume 16, Issue 10, October 2026 Edition [ISSN 2250-3153]

Advanced Weld Failure Prediction in Crashworthiness CAE
     Tushar Phule, Sunil Waghmare
Abstract: Weld separation can redirect load paths, accelerate structural collapse, and create large discrepancies between physical crash tests and finite-element predictions. The difficulty is not limited to assigning a single rupture force. Automotive joints experience mixed-mode normal, shear, bending, and torsional loading; sheet tearing may compete with nugget pull-out or interfacial fracture; local heat-affected-zone softening and geometric eccentricity alter the effective resistance; and mesh size, connector formulation, strain rate, manufacturing scatter, and model assembly quality all influence the numerical response. This paper presents a comprehensive methodology for advanced weld failure prediction in crashworthiness computer-aided engineering (CAE), with emphasis on resistance spot welds, gas metal arc and metal inert gas seam welds, laser welds, projection welds, and mixed-material joints represented in explicit finite-element solvers such as LS-DYNA. The framework separates joint behavior into elastic stiffness, plastic deformation, damage initiation, mixed-mode interaction, progressive degradation, final separation, and post-failure contact. It defines a hierarchical test pyramid, parameter-identification workflow, verification matrix, full-vehicle validation strategy, uncertainty treatment, and governance process. Particular attention is given to solid nugget, beam/connector, tied-contact, cohesive, and detailed heat-affected-zone approaches; force-based versus stress/strain-based criteria; mesh-objective regularization; and model transfer across gauges, grades, stack-ups, and loading rates. A staged implementation is proposed in which screening-level connectors are retained for non-critical joints while high-fidelity representations are deployed along dominant crash load paths. The resulting process improves physical realism without imposing uncontrolled model size or calibration complexity. The paper concludes that predictive weld modeling is best treated as
Reference this Research Paper (Copy):
Tushar Phule, Sunil Waghmare (2026); Advanced Weld Failure Prediction in Crashworthiness CAE; International Journal of Scientific and Research Publications (IJSRP) 16(10) (ISSN: 2250-3153), DOI: http://dx.doi.org/ 10.29322/IJSRP.16.10.2026.p17817
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| ISSN: 2250-3153 | DOI: 10.29322/IJSRP