Computational Methods in Structural Engineering: Current Advances and Future Perspectives

This brief editorial introduces the Special Issue “Computational Methods in Structural Engineering”. This Special Issue brings together recent advances in computational approaches—including finite element modeling, machine learning applications, stochastic analysis, and high-precision numerical methods— highlighting their increasing influence on the analysis, design, and assessment of modern structural systems. The published contributions cover topics such as the nonlinear finite element method (FEM) for structural response under extreme loading, advanced plate and composite modeling, explainable AI for material characterization, machine learning for predictive performance modeling, data-driven signal processing for structural health monitoring, and stochastic analysis of dynamic inputs. Through this collection of studies, this Special Issue underscores both the opportunities and the challenges of applying advanced computational methods to enhance the resilience, efficiency, and understanding of structural engineering systems.

Authors

Institutions

Publication Details

Journal
Computation
Published
2025-09-16
DOI
https://doi.org/10.3390/computation13090224
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational Methods in Structural Engineering: Current Advances and Future Perspectives

Manolis Georgioudakis, Vagelis Plevris, Mahdi Kioumarsi
Computation
Topology Optimization in Engineering
article

Computational Methods in Structural Engineering: Current Advances and Future Perspectives

Manolis Georgioudakis, Vagelis Plevris, Mahdi Kioumarsi
article en

Abstract

This brief editorial introduces the Special Issue “Computational Methods in Structural Engineering”. This Special Issue brings together recent advances in computational approaches—including finite element modeling, machine learning applications, stochastic analysis, and high-precision numerical methods— highlighting their increasing influence on the analysis, design, and assessment of modern structural systems. The published contributions cover topics such as the nonlinear finite element method (FEM) for structural response under extreme loading, advanced plate and composite modeling, explainable AI for material characterization, machine learning for predictive performance modeling, data-driven signal processing for structural health monitoring, and stochastic analysis of dynamic inputs. Through this collection of studies, this Special Issue underscores both the opportunities and the challenges of applying advanced computational methods to enhance the resilience, efficiency, and understanding of structural engineering systems.

ComputationVol. 13(9)
National Technical University of Athens (GR), OsloMet – Oslo Metropolitan University (NO), Qatar University (QA)
Openalex Percentile: Top 74%
Topology Optimization in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.