Publications

Link Publications

  1. Kapusuzoglu, B., Mahadevan, S., Matsumoto, S., Miyagi, Y., Taba, S., Watanabe, D. (2022). Adaptive Surrogate Modeling for High-Dimensional Spatio-Temporal Output. Structural and Multidisciplinary Optimization 65.10 (2022): 300. doi: 10.1007/s00158-022-03402-x
  2. Kapusuzoglu, B., Mahadevan, S., Matsumoto, S., Miyagi, Y., Taba, S., Watanabe, D. (2022). Multi-Level Bayesian Calibration of a Multi-Component Dynamic System Model. ASME JCISE, 1-15. doi: 10.1115/1.4055315
  3. Kapusuzoglu, B., Nath, P., Sato, M., Mahadevan, S., Witherell, P., (2022). Multi-Objective Optimization Under Uncertainty of Part Quality in Fused Filament Fabrication. ASME J. Risk Uncertainty Part B; 8(1): 011112. doi: 10.1115/1.4053181
  4. Kapusuzoglu, B., Mahadevan, S., (2020). Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data. Reliability Engineering and System Safety, Special Issue: Sensitivity Analysis of Model Outputs. doi: 10.1016/j.ress.2021.107712
  5. Kapusuzoglu, B., Mahadevan, S. (2020). Physics-Informed and Hybrid Machine Learning in Additive Manufacturing: Application to Fused Filament Fabrication. JOM, 1-11. doi: 10.1007/s11837-020-04438-4
  6. Kapusuzoglu, B., Sato, M., Mahadevan, S., Witherell, P., (2020). Process optimization under uncertainty for improving the bond quality of polymer filaments in Fused Filament Fabrication. Journal of Manufacturing Science and Engineering, 1-46. doi: 10.1115/1.4048073
  7. Karve, P. M., Guo, Y., Kapusuzoglu, B., Mahadevan, S., Haile, M. A. (2020). Digital twin approach for damage-tolerant mission planning under uncertainty. Engineering Fracture Mechanics, 106766
  8. Oskay, C., Su, Z., Kapusuzoglu, B. (2019). Discrete eigenseparation-based reduced order homogenization method for failure modeling of composite materials. Computer Methods in Applied Mechanics and Engineering, 112656
  1. Kapusuzoglu, B., Guo, Y., Mahadevan, S., Matsumoto, S., Miyagi, Y., Taba, S., Watanabe, D. (2022). Dimension Reduction for Efficient Surrogate Modeling in High-Dimensional Applications. AIAA SCITECH 2022 Forum (p. 1440). doi: 10.2514/6.2022-1440
  2. Karve, P. M., Guo, Y., Kapusuzoglu, B., Mahadevan, S., Haile, M. A. (2020). Fatigue Crack Growth Diagnosis and Prognosis for Damage-Adaptive Operation of Mechanical Systems. Model Validation and Uncertainty Quantification, Volume 3 (pp. 233-236). Springer, Cham.
  3. Karve, P. M., Guo, Y., Kapusuzoglu, B., Mahadevan, S., Haile, M. A. (2020). Resilience-enhancing operations of aerostructural systems under uncertainty: a digital twin approach. AIAA SCITECH 2020 Forum.