0000000000117147
AUTHOR
Panagiotis G. Asteris
showing 26 related works from this author
Prediction of concrete materials compressive strength using surrogate models
2022
Using soft computing methods could be of great interest in predicting the compressive strength of Ultra-High-Performance Fibre Reinforced Concrete (UHPFRC). Therefore, this study developed four soft computing techniques. The models are the Linear- relationship (LR), pure quadratic, M5P-tree (M5P), and artificial neural network (ANN). The models were trained and developed using 306 datasets comprising 11 input parameters, including the curing temperature (T), the water-to-cement ratio (w/c), silica fume (SF), cement content (C), fiber content (Fb), water (W), sand content (S), superplasticizer (SP), fiber aspect ratio (AR) and curing time (t). Experimental results were used and compared to t…
Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks
2015
The fundamental period is one of the most critical parameters for the seismic design of structures. There are several literature approaches for its estimation which often conflict with each other, making their use questionable. Furthermore, the majority of these approaches do not take into account the presence of infill walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period. In the present paper, artificial neural networks (ANNs) are used to predict the fundamental period of infilled reinforced concrete (RC) structures. For the training and the validation of the ANN, a large data set i…
Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks
2019
The present paper discussed the development of a reliable and robust artificial neural network (ANN) capable of predicting the tribological performance of three highly alloyed tool steel grades. Experimental results were obtained by performing plane-contact sliding tests under non-lubrication conditions on a pin-on-disk tribometer. The specimens were tested both in untreated state with different hardening levels, and after surface treatment of nitrocarburizing. We concluded that wear maps via ANN modeling were a user-friendly approach for the presentation of wear-related information, since they easily permitted the determination of areas under steady-state wear that were appropriate for use…
Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete
2022
Reinforced concrete bond strength deterioration is one of the most serious problems in the construction industry. It is one of the most common factors impacting structural deterioration and the major cause of premature decadence of reinforced concrete structures. Therefore, developing an accurate model with the lowest variance and high reliability for the bond strength of corroded reinforced concrete is very important. The current work evaluates the efficiency of convolution-based ensemble learning algorithms. To address these issues, convolution-based ensemble learning models are developed using a database collected from the previous experimental studies of relative bond strength for corro…
Parameters affecting the fundamental period of infilled RC frame structures
2015
Despite the fact that the fundamental period appears to be one of the most critical parameters for the seismic design of structures according to the modal superposition method, the so far available in the literature proposals for its estimation are often conflicting with each other making their use uncertain. Furthermore, the majority of these proposals do not take into account the presence of infills walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period numerical value. Toward this end, this paper presents a detailed and in-depth analytical investigation on the parameters that affect…
Strategies of Identification of a Base-Isolated Hospital Building by Coupled Quasi-Static and Snap-Back Tests
2020
In this paper, the description of a series of quasi-static pushing tests and dynamic snap-back tests is proposed, involving the base-isolated emergency building of the Palermo university hospital. The base isolation system is characterized by a set of double-curved friction pendulum isolators placed on the top of the columns of the underground level, characteristics that cannot be found in the experimental studies available in the literature. The aim of the work was to investigate the static and dynamic properties of the building in question and comparing the in-situ results with the characteristics assigned during the design process and to assess the level of agreement. Static lateral push…
Definition of Seismic Vulnerability Maps for Civil Protection Systems: The Case of Lampedusa Island
2016
The opportunity to locate and quantify the major criticalities associated to natural catastrophic events on a territory allows to plan adequate strategies and interventions by civil protection bodies involved in local and international emergencies. Seismic risk depends, most of all, on the vulnerability of buildings belonging to the urban areas. For this reason, the definition, by a deep analysis of the territory, of instruments identifying and locating vulnerability, largely favours the activities of institutions appointed to safeguard the safety of citizens. This paper proposes a procedure for the definition of vulnerability maps in terms of vulnerability indexes and critical peak ground …
Equivalent Non-Linearization of Hysteretic Systems by Means of RPS
2018
BackgroundThe analysis of elastoplastic systems with hardening (Bouc-Wen systems) under stochastic (seismic) loads needs the evaluation of higher order statistics even in the simplest case of normal distributed input. ObjectiveIn this paper, a non-linearization technique is proposed in order to evaluate the moments of any order of the response. MethodThis technique is developed by means of a nonlinear class of systems whose statistics are a priori known. The parameters of such systems can be chosen in such a way that the two systems are equivalent in a wide sense. Result & ConclusionIn the paper, the strategy to obtain the equivalence and the reliability of the results are discussed.
Krill herd algorithm-based neural network in structural seismic reliability evaluation
2018
ABSTRACTIn this research work, the relative displacement of the stories has been determined by means of a feedforward Artificial Neural Network (ANN) model, which employs one of the novel methods for the optimization of the artificial neural network weights, namely the krill herd algorithm. For the purpose of this work, the area, elasticity, and load parameters were the input parameters and the relative displacement of the stories was the output parameter. To assess the precision of the feedforward (FF) model optimized using the Krill Herd Optimization (FF-KH) algorithm, comparison of results has been performed relative to the results obtained by the linear regression model, the Genetic Alg…
Genetic prediction of ICU hospitalization and mortality in COVID‐19 patients using artificial neural networks
2021
There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, …
Novel fuzzy-based optimization approaches for the prediction of ultimate axial load of circular concrete-filled steel tubes
2021
An accurate estimation of the axial compression capacity of the concrete-filled steel tubular (CFST) column is crucial for ensuring the safety of structures containing them and preventing related failures. In this article, two novel hybrid fuzzy systems (FS) were used to create a new framework for estimating the axial compression capacity of circular CCFST columns. In the hybrid models, differential evolution (DE) and firefly algorithm (FFA) techniques are employed in order to obtain the optimal membership functions of the base FS model. To train the models with the new hybrid techniques, i.e., FS-DE and FS-FFA, a substantial library of 410 experimental tests was compiled from openly availa…
A macro-modelling approach for the analysis of infilled frame structures considering the effects of openings and vertical loads
2015
During the last decades, several macro-models have been proposed for the modelling of the infill panels' contribution to the lateral strength of frames. Despite all this effort, a robust model, which takes into account the influence of the vertical load, is not yet available. Furthermore, the influence of the very common case of infill walls with openings, such as windows and doors, has been neglected in all the code provisions that have been published so far. In this paper, an updated macro-model, based on the equivalent pin-jointed diagonal compressive strut, is presented. The proposed macro-model is able to represent the stiffening effect of the infill panel with openings by taking into …
Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects
2019
A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approac…
Residual out-of-plane capacity of infills damaged by in-plane cyclic loads
2020
Abstract During earthquakes, infills are subjected to In-Plane (IP) and Out-Of-Plane (OOP) actions. In the case of strong earthquakes, infills may progressively change their mechanical behavior resulting in a reduction of IP and OOP stiffness and strength. Recent earthquakes have proved that the OOP collapse of infills is a diffused mechanism also for buildings designed to resist seismic events in agreement to the most modern codes. This is potentially a very dangerous event with risk for human health. The strong interaction between IP and OOP behavior of infills traduces in a progressive reduction of the OOP strength. The IP damaging loads may cause a loss of the OOP capacity not predicted…
Mapping and holistic design of natural hydraulic lime mortars
2020
Supplementary data to this article can be found online at https://doi.org/10.1016/j.cemconres.2020.106167.
Genetic justification of severe COVID-19 using a rigorous algorithm
2021
Recent studies suggest excessive complement activation in severe coronavirus disease-19 (COVID-19). The latter shares common characteristics with complement-mediated thrombotic microangiopathy (TMA). We hypothesized that genetic susceptibility would be evident in patients with severe COVID-19 (similar to TMA) and associated with disease severity. We analyzed genetic and clinical data from 97 patients hospitalized for COVID-19. Through targeted next-generation-sequencing we found an ADAMTS13 variant in 49 patients, along with two risk factor variants (C3, 21 patients; CFH,34 patients). 31 (32%) patients had a combination of these, which was independently associated with ICU hospitalization (…
Fundamental period of infilled reinforced concrete frame structures
2016
AbstractThe fundamental period of vibration appears to be one of the most critical parameters for the seismic design and assessment of structures. In the present paper, the results of a large-scale analytical investigation on the parameters that affect the fundamental period of reinforced concrete structures are presented. The influence of the number of storeys, the number of spans, the span length, the infill wall panel stiffness and the percentage of openings within the infill panel on the fundamental period of infilled RC frames was investigated. Based on these results, a regression analysis is applied in order to propose a new empirical equation for the estimation of the fundamental per…
A novel heuristic algorithm for the modeling and risk assessment of the COVID-19 pandemic phenomenon
2020
This article belongs to the special issue: Soft computing techniques in materials science and engineering Summarization: The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of dai…
Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniques
2022
In this study, a model for the estimation of the compressive strength of concretes incorporating metakaolin is developed and parametrically evaluated, using soft computing techniques. Metakaolin is a component extensively employed in recent decades as a means to reduce the requirement for cement in concrete. For the proposed models, six parameters are accounted for as input data. These are the age at testing, the metakaolin percentage in relation to the total binder, the water-to-binder ratio, the percentage of superplasticizer, the binder to sand ratio and the coarse to fine aggregate ratio. For training and verification of the developed models a database of 867 experimental specimens has …
Strategies for waste recycling : the mechanical performance of concrete based on limestone and plastic waste
2022
Recycling is among the best management strategies to avoid dispersion of several types of wastes in the environment. Research in recycling strategies is gaining increased importance in view of Circular Economy principles. The exploitation of waste, or byproducts, as alternative aggregate in concrete, results in a reduction in the exploitation of scarce natural resources. On the other hand, a productive use of waste leads to a reduction in the landfilling of waste material through the transformation of waste into a resource. In this frame of reference, the paper discusses how to use concrete as a container of waste focusing on the waste produced in limestone quarries and taking the challenge…
Masonry Compressive Strength Prediction Using Artificial Neural Networks
2019
The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of m…
Numerical modelling of out-of-plane response of infilled frames: State of the art and future challenges for the equivalent strut macromodels
2017
Abstract Infill-frame interaction constitutes a still open question both in research and in practicing engineering. Computational models used to predict this interaction are, in most cases, addressing the estimation of the response of the infilled frames when subjected to actions parallel to their plane. However, the observation of the post-earthquake damage has demonstrated that infills, weakened by the in-plane actions, may fail out-of-plane increasing the risks associated to the earthquake scenarios. In spite of this, different studies have shown that infills, if properly designed and supported by the frame, exhibit a significant strength and displacement capacity when called to resist t…
A Novel Heuristic Global Algorithm to Predict the COVID-19 Pandemic Trend
2020
SummaryMathematical models are useful tools to predict the course of an epidemic. A heuristic global Gaussian-function-based algorithm for predicting the COVID-19 pandemic trend is proposed for estimating how the temporal evolution of the pandemic develops by predicting daily COVID-19 deaths, for up to 10 days, starting with the day the prediction is made. The validity of the proposed heuristic global algorithm was tested in the case of China (at different temporal stages of the pandemic). The algorithm was used to obtain predictions in six different locations: California, New York, Iran, Sweden, the United Kingdom, and the entire United States, and in all cases the prediction was confirmed…
Surrogate models for the compressive strength mapping of cement mortar materials
2021
Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method available in the literature, which can reliably predict their strength based on the mix components. This limitation is attributed to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques for predicting the compressive strength of mortars is investigated. Specifically, Levenberg–Marquardt, biogeography-based optimization, and invasive weed optimization algorithms are used for this purpose (based on experimental data available in the literature). The c…
Influence of column shear failure on pushover based assessment of masonry infilled reinforced concrete framed structures: A case study
2017
Structural frames, constructed either of steel or reinforced concrete (RC), are often infilled with masonry panels. However, during the analysis of the structural frames, it has become common practice to disregard the existence of infills because of the complexity in modeling. This omission should not be allowed because the two contributions (of infills and of frames) complement each other in providing a so different structural system. The use of different modeling assumptions significantly affects the capacity as well as the inelastic demand and safety assessment. In specific, the adoption of equivalent diagonal pin-jointed struts leaves open the problem of the evaluation of the additional…
Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
2022
We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphoc…