Daniele Mortari

Selected Publications

• Mortari, D., Garrappa, R., and Nicolo’, L. “Theory of Functional Connections Extended to Fractional Operators,” Functional Interpolation (Mathematics), 2023, , Vol. 11, No. 7.
• Mortari, D. “Theory of Functional Connections Subject to Shear-type and Mixed Derivatives,” Functional Interpolation (Mathematics), 2022, 10(24):4692.
• Yassopoulos, C., Reddy, J.N., and Mortari, D. “Analysis of Nonlinear Timoshenko–Ehrenfest Beam Problems with von Kármán Nonlinearity using the Theory of Functional Connections,” Mathematics and Computers in Simulation, 2022, In print.
• Mortari, D. “Using the Theory of Functional Connections to solve Boundary Value Geodesic Problems,” Mathematical and Computational Applications, 2022; 27(4):64. https://doi.org/10.3390/mca27040064
• Mai, T. and Mortari, D. “Theory of Functional Connections Applied to Quadratic and Nonlinear Programming under Equality Constraints,” Journal of Computational and Applied Mathematics, 2022,Vol. 406, 113912.
• Yassopoulos, C., Leake, C., Reddy, J.N., and Mortari, D. “Analysis of Timoshenko-Ehrenfest Beam Problems using the Theory of Functional Connections,” Special Issue “Computational Approaches to Mechanical Response Analysis of Structures at Diverse Scales,”‘ Journal Engineering Analysis with Boundary Elements, 2021, Vol. 132, pp. 271-280.
• Johnston, H. and Mortari, D. “Least-squares Solutions of Boundary-Value Problems in Hybrid Systems,” Journal of Computational and Applied Mathematics, 393, (2021) 113524.
• Mortari, D. and Arnas, D. “Bijective Mapping Analysis to Extend the Theory of Functional Connections to Non-rectangular 2-dimensional Domains,” Mathematics 2020, 8(9), 1593; https://doi.org/10.3390/math8091593.
• Leake, C., Johnston, H., and Mortari, D. “The Multivariate Theory of Functional Connections: Theory, Proofs, and Application in Partial Differential Equations,” Mathematics, 2020, 8(8), 1303.
• Leake, C. and Mortari, D. “Deep Theory of Functional Connections: A New Method for Estimating the Solutions of Partial Differential Equations“, Machine Learning and Knowledge Extraction, 2020, Vol. 2, No. 1, pp. 37-55.