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Panagiotis G. Asteris

School of Pedagogical and Technological Education

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Danial Jahed Armaghani

University of Technology Sydney

Liborio Cavaleri

University of Palermo

Ahmed Salih Mohammed

University of Sulaimani

Athanasia D. Skentou

School of Pedagogical and Technological Education

Abidhan Bardhan

National Institute of Technology Patna

Anna Mamou

School of Pedagogical and Technological Education

Markos Z. Tsoukalas

School of Pedagogical and Technological Education

Minas E. Lemonis

School of Pedagogical and Technological Education

Maria G. Douvika

School of Pedagogical and Technological Education

Mohammadreza Koopialipoor

Amirkabir University of Technology

Cooperative Institutions

National Technical University of Athens

School of Pedagogical and Technological Education

National and Kapodistrian University of Athens

G. Papanikolaou General Hospital

Aristotle University of Thessaloniki

University of Technology Malaysia

Central South University

National Institute of Technology Patna

Duy Tan University

University of West Attica

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MASONRY INFILLED REINFORCED CONCRETE FRAMES WITH OPENINGS

Panagiotis G. Asteris Christis Ζ. Chrysostomou Ioannis Giannopoulos

This work presents an assessment of the behavior of infilled frames. The feasibility of possible immediate implementation of some recent developments both in analysis and de- sign of infilled frames for practical design is investigated. It is now widely recognised that masonry infill panels, used in reinforced concrete (R/C) frame structures, significantly en- hance both the stiffness and the strength of the surrounding frame. However, their contribu- tion is often not taken into account because of the lack of knowledge of the composite behaviour of the surrounding frame and the infill panel. Currently, Seismic Design Guidelines (EC8 - Part 3, FEMA - 440, ASCE 41-06) contain provisions for the calculation of the stiffness of solid infilled frames mainly by modeling infill walls as struts. However, such provisions are not provided for infilled frames with openings. The present study, based on available finite element results, proposes analyti- cal equations for obtaining the reduction factor, which is the ratio of the effective width of a diagonal strut representing a wall with an opening over that of the solid RC infilled frame. That will allow the calculation of the initial lateral stiffness of infills when an opening is present. The validity of the proposed equations is demonstrated by comparing our results, against work done by various researchers.

Infill

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Identifying Universal Characteristics in Local Strain Field Evolution for Creep Failure Prediction

Bakhtiyar Mammadli Tero Mäkinen Karol Frydrych Panagiotis G. Asteris Stefanos Papanikolaou

Strain (injury)

10.2139/ssrn.5025938

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Citations (0)

Closure to “Lateral Stiffness of Brick Masonry Infilled Plane Frames” by P. G. Asteris

Journal of Structural Engineering (2005)

Panagiotis G. Asteris

Closure (psychology)

10.1061/(asce)0733-9445(2005)131:3(523.2)

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Citations (13)

Genetic justification of severe COVID-19 using a rigorous algorithm

Clinical Immunology (2021)

Eleni Gavriilaki Panagiotis G. Asteris Tasoula Touloumenidou Evaggelia-Evdoxia Koravou Maria Koutra

ADAMTS13

Thrombotic microangiopathy

Thrombomodulin

Eculizumab

Complement

10.1016/j.clim.2021.108726

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Citations (57)

Parameters affecting the fundamental period of infilled RC frame structures

Earthquakes and Structures (2015)

Panagiotis G. Asteris Constantinos C. Repapis Athanasios K. Tsaris Fabio Di Trapani Liborio Cavaleri

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 indepth analytical investigation on the parameters that affect the fundamental period of reinforce concrete structure. The calculated values of the fundamental period are compared against those obtained from the seismic code and equations proposed by various researchers in the literature. From the analysis of the results it has been found that the number of storeys, the span length, the stiffness of the infill wall panels, the location of the soft storeys and the soil type are crucial parameters that influence the fundamental period of RC buildings.

Infill

Fundamental frequency

10.12989/eas.2015.9.5.999

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Citations (63)

Genetic prediction of ICU hospitalization and mortality in COVID‐19 patients using artificial neural networks

Journal of Cellular and Molecular Medicine (2022)

Panagiotis G. Asteris Eleni Gavriilaki Tasoula Touloumenidou Evaggelia‐Evdoxia Koravou Maria Koutra

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, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.

2019-20 coronavirus outbreak

10.1111/jcmm.17098

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Citations (60)

Numerical Investigation of the Effect of Infill Walls on the Structural Response of RC Frames

The Open Construction and Building Technology Journal (2012)

Panagiotis G. Asteris

The work presented herein sets out to investigate numerically, by means of nonlinear finite element analysis, the effect of un-reinforced concrete or masonry infill walls on the overall structural response of reinforced concrete frames under static monotonic and seismic loading. For this purpose, a nonlinear finite element package purpose built for the analysis of concrete structures is employed in order to predict the nonlinear behaviour of both the infill walls as well as the surrounding frame. Specifically, the dynamic response of a bare two-storey, one-bay frame, whose behaviour has been experimentally established in the past through shake-table testing, is first investigated via nonlinear finite element analysis. Subsequently, concrete and masonry walls are introduced into the selected frame in order to investigate numerically how important aspects of structural response such as stiffness, load-carrying capacity, deformation profile, cracking, ductility and mode of failure of the frame are affected.

Infill

Earthquake shaking table

Response analysis

10.2174/1874836801206010164

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Citations (31)

Anisotropic masonry failure criterion using artificial neural networks

Neural Computing and Applications (2016)

Panagiotis G. Asteris Vagelis Plevris

Brittleness

10.1007/s00521-016-2181-3

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Citations (89)

Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients

International Journal of Thermal Sciences (2021)

Navid Kardani Abidhan Bardhan Pijush Samui Majidreza Nazem Panagiotis G. Asteris

10.1016/j.ijthermalsci.2021.107427

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Citations (76)

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

Panagiotis G. Asteris Panayiotis C. Roussis Maria G. Douvika

This work presents a soft-sensor approach for estimating critical mechanical properties of sandcrete materials. Feed-forward (FF) artificial neural network (ANN) models are employed for building soft-sensors able to predict the 28-day compressive strength and the modulus of elasticity of sandcrete materials. To this end, a new normalization technique for the pre-processing of data is proposed. The comparison of the derived results with the available experimental data demonstrates the capability of FF ANNs to predict with pinpoint accuracy the mechanical properties of sandcrete materials. Furthermore, the proposed normalization technique has been proven effective and robust compared to other normalization techniques available in the literature.

Normalization

10.3390/s17061344

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Citations (158)

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