Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2019

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

0 Datasets

0 Files

en
2019
Vol 9 (2)
Vol. 9
DOI: 10.3390/app9020243

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Panagiotis Asteris
Panagiotis Asteris

Institution not specified

Verified
Panagiotis Asteris
Αντωνία Μοροπούλου
Athanasia D. Skentou
+5 more

Abstract

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 approach for assessing the seismic vulnerability of masonry historical and monumental structures is presented, taking into account the probabilistic nature of the input parameters by means of analytically determining fragility curves. The emerged methodology is presented in detail through application on theoretical and built cultural heritage real masonry structures.

How to cite this publication

Panagiotis Asteris, Αντωνία Μοροπούλου, Athanasia D. Skentou, Maria Apostolopoulou, Amin Mohebkhah, Liborio Cavaleri, Hugo Rodrigues, Humberto Varum (2019). Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects. , 9(2), DOI: https://doi.org/10.3390/app9020243.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2019

Authors

8

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.3390/app9020243

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access