H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 53 Citations 7,810 197 World Ranking 1224 National Ranking 6

Research.com Recognitions

Awards & Achievements

2002 - Fellow of the International Association for Computational Mechanics (IACM)

Overview

What is he best known for?

The fields of study he is best known for:

  • Finite element method
  • Structural engineering
  • Mathematical optimization

His primary areas of study are Mathematical optimization, Algorithm, Finite element method, Optimization problem and Applied mathematics. His research in Mathematical optimization tackles topics such as Robustness which are related to areas like Data mining. He combines subjects such as Artificial neural network and Domain decomposition methods with his study of Algorithm.

His Finite element method research integrates issues from Numerical analysis, Mathematical analysis and Shell. His study focuses on the intersection of Optimization problem and fields such as Reliability engineering with connections in the field of Incremental Dynamic Analysis, Reinforced concrete and Structure. His study in Applied mathematics is interdisciplinary in nature, drawing from both Airfoil, Lagrange multiplier, Polygon mesh and Conjugate gradient method.

His most cited work include:

  • Reliability-based structural optimization using neural networks and Monte Carlo simulation (358 citations)
  • Structural reliability analyis of elastic-plastic structures using neural networks and Monte Carlo simulation (192 citations)
  • Structural optimization using evolution strategies and neural networks (155 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Structural engineering, Mathematical optimization, Finite element method, Optimization problem and Algorithm. His research is interdisciplinary, bridging the disciplines of Nonlinear system and Structural engineering. His Mathematical optimization research incorporates themes from Domain decomposition methods, Robustness and Applied mathematics.

The various areas that Manolis Papadrakakis examines in his Finite element method study include Shell and Mathematical analysis. His study on Multi-swarm optimization, Meta-optimization and Continuous optimization is often connected to Context as part of broader study in Optimization problem. His work carried out in the field of Algorithm brings together such families of science as Artificial neural network and Numerical analysis.

He most often published in these fields:

  • Structural engineering (27.36%)
  • Mathematical optimization (26.01%)
  • Finite element method (22.30%)

What were the highlights of his more recent work (between 2014-2021)?

  • Structural engineering (27.36%)
  • Nonlinear system (13.51%)
  • Finite element method (22.30%)

In recent papers he was focusing on the following fields of study:

Manolis Papadrakakis mostly deals with Structural engineering, Nonlinear system, Finite element method, Applied mathematics and Mathematical optimization. His Nonlinear system study combines topics from a wide range of disciplines, such as Dynamic loading and Soil structure interaction. His work on Extended finite element method as part of his general Finite element method study is frequently connected to Random field and Initialization, thereby bridging the divide between different branches of science.

His studies deal with areas such as Block matrix, Linear system, Domain decomposition methods, Galerkin method and Coefficient matrix as well as Applied mathematics. In his study, which falls under the umbrella issue of Domain decomposition methods, Algorithm and Robustness is strongly linked to Isogeometric analysis. The Mathematical optimization study combines topics in areas such as Stochastic partial differential equation, Acceleration, Flowchart and Benchmark.

Between 2014 and 2021, his most popular works were:

  • Determination of RVE size for random composites with local volume fraction variation (50 citations)
  • Stochastic finite element analysis of composite structures based on material microstructure (45 citations)
  • Stochastic finite element analysis of composite structures based on mesoscale random fields of material properties (37 citations)

In his most recent research, the most cited papers focused on:

  • Structural engineering
  • Finite element method
  • Mathematical analysis

His primary scientific interests are in Structural engineering, Finite element method, Extended finite element method, Nonlinear system and Random field. His research in Structural engineering intersects with topics in Classical mechanics, Probabilistic logic and Robustness. His studies in Probabilistic logic integrate themes in fields like Shape optimization, Optimization problem, Service life and Seismic assessment.

His work is dedicated to discovering how Finite element method, Material properties are connected with Waviness and other disciplines. Manolis Papadrakakis performs multidisciplinary study on Poisson's ratio and Mathematical optimization in his works. His studies examine the connections between Mathematical optimization and genetics, as well as such issues in Stiffness, with regards to Applied mathematics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Reliability-based structural optimization using neural networks and Monte Carlo simulation

Manolis Papadrakakis;Nikos D Lagaros.
Computer Methods in Applied Mechanics and Engineering (2002)

555 Citations

Structural reliability analyis of elastic-plastic structures using neural networks and Monte Carlo simulation

Manolis Papadrakakis;Vissarion Papadopoulos;Nikos D. Lagaros.
Computer Methods in Applied Mechanics and Engineering (1996)

305 Citations

Structural optimization using evolution strategies and neural networks

Manolis Papadrakakis;Nikos D. Lagaros;Yiannis Tsompanakis.
Computer Methods in Applied Mechanics and Engineering (1998)

251 Citations

Structural optimization using evolutionary algorithms

Nikolaos D. Lagaros;Manolis Papadrakakis;George Kokossalakis.
Computers & Structures (2002)

246 Citations

A method for the automatic evaluation of the dynamic relaxation parameters

M. Papadrakakis.
Computer Methods in Applied Mechanics and Engineering (1981)

228 Citations

Stochastic finite element analysis of shells with combined random material and geometric properties

G. Stefanou;M. Papadrakakis.
Computer Methods in Applied Mechanics and Engineering (2004)

193 Citations

Robust and efficient methods for stochastic finite element analysis using Monte Carlo simulation

Manolis Papadrakakis;Vissarion Papadopoulos.
Computer Methods in Applied Mechanics and Engineering (1996)

185 Citations

Post-buckling analysis of spatial structures by vector iteration methods

M. Papadrakakis.
Computers & Structures (1981)

180 Citations

A Hybrid Particle Swarm—Gradient Algorithm for Global Structural Optimization

Vagelis Plevris;Manolis Papadrakakis.
Computer-aided Civil and Infrastructure Engineering (2010)

166 Citations

Performance-based multiobjective optimum design of steel structures considering life-cycle cost

Michalis Fragiadakis;Nikos D. Lagaros;Manolis Papadrakakis.
Structural and Multidisciplinary Optimization (2006)

150 Citations

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