Blar i Publikasjoner fra Cristin på forfatter "Plevris, Vagelis"

Viser treff 1-20 av 20

    • 3D simulation models for developing digital twins of heritage structures: challenges and strategies 

      Shabani, Amirhosein; Skamantzari, Margarita; Tapinaki, Sevasti; Georgopoulos, Andreas; Plevris, Vagelis; Kioumarsi, Mahdi (Procedia Structural Integrity;Volume 37, 2022, Peer reviewed; Journal article, 2022-02-22)
      Structural vulnerability assessment of heritage structures is a pivotal part of a risk mitigation strategy for preserving these valuable assets for the nations. For this purpose, developing digital twins has gained much ...

    • ANN-based surrogate model for predicting the lateral load capacity of RC shear walls 

      Solorzano, German; Plevris, Vagelis (ECCOMAS Congress;8th European Congress on Computational Methods in Applied Sciences and Engineering, Conference object, 2022)
      Reinforced concrete (RC) shear walls are often used as the main lateral-resisting component in the seismic design of buildings. They provide a large percentage of the lateral stiffness of the structure, and therefore, they ...

    • Bridge management through digital twin-based anomaly detection systems: A systematic review 

      Jiménez Rios, Alejandro; Plevris, Vagelis; Nogal, Maria (Peer reviewed; Journal article, 2023)
      Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently evidenced by the collapse of several bridges ...

    • Chatbots Put to the Test in Math and Logic Problems: A Comparison and Assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard 

      Plevris, Vagelis; Papazafeiropoulos, George; Jiménez Rios, Alejandro (Peer reviewed; Journal article, 2023)
      In an age where artificial intelligence is reshaping the landscape of education and problem solving, our study unveils the secrets behind three digital wizards, ChatGPT-3.5, ChatGPT-4, and Google Bard, as they engage in a ...

    • A Collection of 30 Multidimensional Functions for Global Optimization Benchmarking 

      Plevris, Vagelis; Ramirez, German Solorzano (Data;, Peer reviewed; Journal article, 2022)
      A collection of thirty mathematical functions that can be used for optimization purposes is presented and investigated in detail. The functions are defined in multiple dimensions, for any number of dimensions, and can be ...

    • Computational intelligence methods in simulation and modeling of structures: A state-of-the-art review using bibliometric maps 

      Ramirez, German Solorzano; Plevris, Vagelis (Peer reviewed; Journal article, 2022)
      The modeling and simulation of structural systems is a task that requires high precision and reliable results to ensure the stability and safety of construction projects of all kinds. For many years now, structural engineers ...

    • Computational Methods Applied to Earthen Historical Structures 

      Jiménez Rios, Alejandro; Ruiz-Capel, Samuel; Plevris, Vagelis; Nogal, Maria (Peer reviewed; Journal article, 2023)
      Earthen structures have an important representation among the UNESCO World Heritage List sites as well as among the built environment in general. Unfortunately, earthen heritage structures are also numerous within the ...

    • Design of Reinforced Concrete Isolated Footings Under Axial Loading with Artificial Neural Networks 

      Ramirez, German Solorzano; Plevris, Vagelis (EUROGEN;Proceedings of the 14th International Conference on Evolutionary and Deterministic Methods For Design, Optimization and Control, Conference object, 2021)
      In engineering practice, the design of structural elements is a repetitive task that has proven to be difficult to fully automate. This is mainly because of the complex relations of the design variables and the multiple ...

    • DNN-MLVEM: A Data-Driven Macromodel for RC Shear Walls Based on Deep Neural Networks 

      Solorzano, German; Plevris, Vagelis (Peer reviewed; Journal article, 2023)
      This study proposes the DNN-MVLEM, a novel macromodel for the non-linear analysis of RC shear walls based on deep neural networks (DNN); while most RC shear wall macromodeling techniques follow a deterministic approach to ...

    • Investigation of performance metrics in regression analysis and machine learning-based prediction models 

      Plevris, Vagelis; Solorzano, German; Bakas, Nikolaos P.; Ben Seghier, Mohamed El Amine (ECCOMAS Congress;8th European Congress on Computational Methods in Applied Sciences and Engineering, Conference object, 2022-11-24)
      Performance metrics (Evaluation metrics or error metrics) are crucial components of regression analysis and machine learning-based prediction models. A performance metric can be defined as a logical and mathematical construct ...

    • On the performance of differential evolution variants in constrained structural optimization 

      Georgioudakis, Manolis; Plevris, Vagelis (Procedia Manufacturing;volume 44, Peer reviewed; Journal article, 2020-05-04)
      Constrained optimization is a highly important field of engineering as most real-world optimization problems are associated with one or several constraints. Such problems are often challenging to solve due to their complexity ...

    • An Open-Source Framework for Modeling RC Shear Walls Using Deep Neural Networks 

      Solorzano, German; Plevris, Vagelis (Peer reviewed; Journal article, 2023)
      Reinforced concrete (RC) shear walls macroscopic models are simplified strategies able to simulate the complex nonlinear behavior of RC shear walls to some extent, but their efficacy and robustness are limited. In contrast, ...

    • Performance-based seismic assessment of a historical masonry arch bridge: Effect of pulse-like excitations 

      Shabani, Amirhosein; Kioumarsi, Mahdi; Plevris, Vagelis (Peer reviewed; Journal article, 2023)
      Seismic analysis of historical masonry bridges is important for authorities in all countries hosting such cultural heritage assets. The masonry arch bridge investigated in this study was built during the Roman period and ...

    • Prediction of seismic damage spectra using computational intelligence methods 

      Gharehbaghi, Sadjad; Gandomi, Mostafa; Plevris, Vagelis; Gandomi, Amir H. (Computers & structures;, Peer reviewed; Journal article, 2021)
      Predicting seismic damage spectra, capturing both structural and earthquake features, is useful in performance-based seismic design and quantifying the potential seismic damage of structures. The objective of this paper ...

    • Prediction of the Eigenperiods of MDOF Shear Buildings Using Neural Networks 

      Plevris, Vagelis; Ramirez, German Solorzano (International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering;8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, Conference object, 2021)
      The study of multi-degree of freedom (MDOF) systems is essential to evaluate and understand the seismic response of buildings. Through a MDOF idealization, the dynamic properties of the building such as its natural frequencies ...

    • A Preliminary Structural Survey of Heritage Timber Log Houses in Tønsberg, Norway 

      Shabani, Amirhosein; Hosamo, Haidar; Plevris, Vagelis; Kioumarsi, Mahdi (Conference object, 2021-11-29)
      The formulation of a multi-hazard loss model for a given structure is not only of interest for predicting the economic impact of future damage but it can also be of importance for risk mitigation. A methodology that can ...

    • Pure Random Orthogonal Search (PROS): A Plain and Elegant Parameterless Algorithm for Global Optimization 

      Plevris, Vagelis; Ramirez, German Solorzano (Applied Sciences;Volume 11 / Issue 11, Peer reviewed; Journal article, 2021-05-29)
      A new, fast, elegant, and simple stochastic optimization search method is proposed, which exhibits surprisingly good performance and robustness considering its simplicity. We name the algorithm pure random orthogonal search ...

    • Synthetic data generation for the creation of bridge digital twins what-if scenarios 

      Jiménez Rios, Alejandro; Plevris, Vagelis; Nogal, Maria (Chapter; Peer reviewed; Conference object, 2023)
      The Digital Twin (DT) concept, as understood nowadays, appeared in the early 2000s as an attempt to create virtual replicas of physical assets, such as bridges, that can be used to examine, monitor and manage their ...

    • Uncertainties in the synthetic data generation for the creation of bridge digital twins 

      Jiménez Rios, Alejandro; Plevris, Vagelis; Nogal, Maria (Chapter; Peer reviewed; Conference object, 2023)
      Digital twins (DTs) are virtual replicas of physical assets that can be used to monitor and manage their performance. To date, the DT concept has been effectively implemented in various industries, including aeronautics, ...

    • Vulnerability assessment of cultural heritage structures 

      Kioumarsi, Mahdi; Plevris, Vagelis; Shabani, Amirhosein (ECCOMAS Congress;8th European Congress on Computational Methods in Applied Sciences and Engineering, Conference object, 2022)
      Cultural heritage (CH) assets are the legacy of a society that are inherited from the past generations and can give us lessons for contemporary construction. Not only the formally recognized CH assets but also the non-CH ...