Data-Interpretation methodologies for Non-Linear Earthquake Response Predictions of Damaged Structures

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Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

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Fibre-reinforced polymers (FRP) strengthening can be applied to decrease the seismic vulnerability of existing masonry buildings, both with regard to in-plane and out-of-plane failure mechanisms. Experimentally, the impact of strengthening solutions has be ...

This paper presents quantitative information on the effectiveness of seismic retrofit solutions using bilinear oil dampers for seismically deficient existing tall steel buildings. For this purpose, a benchmark 40-story steel space moment-resisting frame bu ...

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability impr ...

Recent seismic events have showcased the vulnerability of non-structural components to even low- or moderate-intensity earthquakes that occur far more frequently than design-basis ones. Thus, community-critical buildings, such as hospitals, telecommunicati ...

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Masonry buildings form building aggregates around the world in historical centers, which developed as the layout of the city or village densified. In these aggregates, adjacent buildings can share structural walls, connected at the interfaces by interlocki ...

Sustainable development has emerged as a paramount consideration in various fields of industry, including construction, to preserve the environment and its finite resources. Lightweight structures, such as fiber-polymer composite structures, address both s ...

With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...

Data-Interpretation methodologies for Non-Linear Earthquake Response Predictions of Damaged Structures

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Reliable data-driven decision-making through optimal transport

Data and scripts for the RaFSIP scheme

Development and characterization of thin iron-based shape memory alloy prestressing wire

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

Precision luminosity measurement at hadron colliders

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

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Seismic Assessment and Retrofit of Pre-Northridge High Rise Steel Moment Resisting Frame Buildings with Bilinear Oil Dampers

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

The use of ductile steel fuses for the seismic protection of acceleration sensitive non- structural components: Numerical and Experimental verification

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

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Seismic Testing of Adjacent Interacting Masonry Structures

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Surrogate modelling for seismic collapse risk assessment of steel moment resisting frames