Post-seismic response and repair of earthquake-damaged reinforced concrete bridges

“In bridge structures, column members are typically designed to be the primary source of energy dissipation during an earthquake. Therefore, reinforced concrete (RC) bridges that are damaged in an earthquake tend to have damage to the column members. While many studies have been conducted on seismic strengthening of RC bridge columns, most are focused on retrofit instead of repair. In addition, the limited research on seismic repair of RC bridges has focused on evaluating the response of individual columns (member level), not the bridge structure (system level), due to limitations in modeling and especially testing of full bridge structures. Local modifications (interventions) from the repair of a member can change its performance, and changes in column member performance can influence the bridge structure performance, especially under seismic loading. This study evaluated the impact of RC bridge column seismic repair on the member level, system level, and community level responses. Numerical simulation was used to model the response of repaired RC bridge columns (member level) and study the post-repair response of a prototype bridge with repaired columns (system level). The model was also extended to develop a methodology to minimize the level of pre-earthquake retrofit such that the RC bridge can withstand an earthquake without collapse, suffering minor or moderate damage that can be rapidly repaired later. Finally, a discrete-event-based simulation model was developed to estimate the time needed to bring the situation under control for a given volume of resources under a variety of scenarios after an earthquake occurs in a case-study community (community response), and to study the sensitivity of the restoration times to different variables”--Abstract, page iii

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The Sex-Specific Detrimental Effect of Diabetes and Gender-Related Factors on Pre-admission Medication Adherence Among Patients Hospitalized for Ischemic Heart Disease: Insights From EVA Study

Background: Sex and gender-related factors have been under-investigated as relevant determinants of health outcomes across non-communicable chronic diseases. Poor medication adherence results in adverse clinical outcomes and sex differences have been reported among patients at high cardiovascular risk, such as diabetics. The effect of diabetes and gender-related factors on medication adherence among women and men at high risk for ischemic heart disease (IHD) has not yet been fully investigated.Aim: To explore the role of sex, gender-related factors, and diabetes in pre-admission medication adherence among patients hospitalized for IHD.Materials and Methods: Data were obtained from the Endocrine Vascular disease Approach (EVA) (ClinicalTrials.gov Identifier: NCT02737982), a prospective cohort of patients admitted for IHD. We selected patients with baseline information regarding the presence of diabetes, cardiovascular risk factors, and gender-related variables (i.e., gender identity, gender role, gender relations, institutionalized gender). Our primary outcome was the proportion of pre-admission medication adherence defined through a self-reported questionnaire. We performed a sex-stratified analysis of clinical and gender-related factors associated with pre-admission medication adherence.Results: Two-hundred eighty patients admitted for IHD (35% women, mean age 70), were included. Around one-fourth of the patients were low-adherent to therapy before hospitalization, regardless of sex. Low-adherent patients were more likely diabetic (40%) and employed (40%). Sex-stratified analysis showed that low-adherent men were more likely to be employed (58 vs. 33%) and not primary earners (73 vs. 54%), with more masculine traits of personality, as compared with medium-high adherent men. Interestingly, women reporting medication low-adherence were similar for clinical and gender-related factors to those with medium-high adherence, except for diabetes (42 vs. 20%, p = 0.004). In a multivariate adjusted model only employed status was associated with poor medication adherence (OR 0.55, 95%CI 0.31–0.97). However, in the sex-stratified analysis, diabetes was independently associated with medication adherence only in women (OR 0.36; 95%CI 0.13–0.96), whereas a higher masculine BSRI was the only factor associated with medication adherence in men (OR 0.59, 95%CI 0.35–0.99).Conclusion: Pre-admission medication adherence is common in patients hospitalized for IHD, regardless of sex. However, patient-related factors such as diabetes, employment, and personality traits are associated with adherence in a sex-specific manner

Experimental study of the compressive behavior of masonry columns confined with SRG composites

La letteratura scientifica del secolo passato ha dimostrato come il confinamento sia un metodo di rinforzo efficace per elementi compressi in c.a. e muratura. In particolare, l’utilizzo di materiali compositi ha dato nuovo impulso alle applicazioni ed ha permesso di superare i limiti dei metodi tradizionali. Questo scritto tratta della possibile applicazione di una nuova tecnologia di materiali compositi detti SRG (steel reinforced grout) nel settore della conservazione degli edifici storici. Vengono mostrati i risultati di una sperimentazione di tale tecnica applicata a colonne in muratura a sezione quadrata sottoposte a compressione assiale monotona. L’efficacia del confinamento viene studiata in termini incremento di capacità portante, di deformazione massima e di energia assorbita rispetto a dei provini non confinati. Le variabili analizzate sono la densità delle fibre d’acciaio e il raggio di arrotondamento degli spigoli

Strategic Implications for Civil Infrastructure and Logistical Support Systems in Post-Earthquake Disaster Management: The Case of St. Louis

An important role of post-earthquake emergency management is to minimize the restoration time, which is the sum of the travel time and the response time. The travel time is the time needed to reach the affected area from the dispatch location, while the response time is the time required to bring the situation under control after reaching the affected area. A number of built environment variables, e.g., building collapse probability, and natural variables, e.g., flooding probability, are known to affect the restoration time. Data from St. Louis, Missouri, USA are used in conjunction with a discrete-event-based simulation model to identify the statistically significant variables via an analysis of variance. The experimental results show that in order to reduce the loss of life, the volume of resources and the building collapse and flooding probabilities are significant factors that should be accounted for in the emergency-response planning for an earthquake

Discrete-Event-Based Simulation Model for Performance Evaluation of Post-Earthquake Restoration in a Smart City

Emergency responders are typically notified immediately after a major earthquake strikes. However, a time delay, called the travel time, is usually experienced between the notification and the arrival of the responders on the scene. The reparative work necessary after the responders arrive takes an additional amount of time, called the response time, depending on the nature of the damage and the volume of resources available. In a smart city, the restoration time, which is the sum of the travel and response times, should be minimized. A new discrete-event-based simulation (DEBS) model is presented in this paper to estimate the restoration time needed to bring the situation under control after notifying the response center. The DEBS model not only relaxes restrictive assumptions on travel time made by the Markov chain models from the existing literature, but it can also quantify the impact of resource volumes on restoration times. Additionally, the DEBS model is very useful for training purposes. The DEBS model was employed on a case study from the state of Missouri (U.S.). The experiments demonstrate that numerical results with the model take a short amount of computational time and that it can be implemented on a real-time basis in a smart-city infrastructure

Confinement of Clay Masonry Columns with SRG

In this study, the behavior of clay masonry columns confined by steel reinforced grout (SRG) composite with a natural hydraulic lime mortar is investigated. An experimental study was carried out to understand the behavior of masonry prisms with a square cross-section confined by SRG composite jackets subjected to a monotonic concentric compressive load. Test parameters considered in this study are the density of steel fibers and column corner radius. The effectiveness of the confinement is studied in terms of load-bearing capacity with respect to unconfined columns

Compressive Behavior of Brick Masonry Columns Confined with Steel-Reinforced Grout Jackets

In this study, a new type of composite comprised of steel cords embedded in a mortar matrix - referred to as steel-reinforced grout (SRG) - is explored for use in the confinement of masonry columns. This paper presents the results of an experimental study carried out to understand the behavior of solid clay brick masonry columns confined by single-layer SRG jackets. Thirty-one confined and three unconfined columns with a square cross-section were tested to failure under a monotonic concentric compressive load. Test parameters considered were the SRG matrix type, column corner condition, and steel cord sheet density (i.e., steel cord spacing) in the SRG jacket. SRG confinement improved the compressive strength, ultimate strain, and energy absorption of masonry columns relative to the unconfined condition. Models from the literature for FRP-confined masonry were examined for their applicability to predict the strength increase from the SRG jacket, with certain models predicting the confined compressive strength within 9% of the test values

Confinement of Brick Masonry Columns with SRG Jackets

This paper presents the results of an experimental program carried out to study the behavior of brick masonry columns confined by steel reinforced grout (SRG) comprised of continuous steel fiber cords embedded in a cementitious matrix. Short brick masonry columns with a square cross-section confined by SRG jackets were subjected to a monotonic concentric compressive load. Parameters investigated in this study were the area weight of steel fibers and the masonry column corner radius. Results show that the SRG jackets increased the compressive strength of the masonry columns by 26-42% relative to the unconfined masonry columns. The compressive strength of the confined columns increased slightly with increasing corner radius ratio and with increasing fiber area weight

System-Level Performance of Earthquake-Damaged Concrete Bridges with Repaired Columns

Reinforced concrete (rc) bridge columns are typically designated as the primary source of energy dissipation for a bridge structure during an earthquake. Therefore, seismic repair of rc bridge columns has been studied extensively during the past several decades. On the other hand, few studies have been conducted to evaluate how repaired column members influence the system-level response of an rc bridge structure in subsequent earthquakes. In this study, a numerical model was established to simulate the response of two large-scale rc columns, repaired using different techniques, reported in the literature. The columns were implemented into a prototype bridge model that was subjected to earthquake loading. Incremental dynamic analysis (ida) and fragility analysis were conducted on numerical bridge models to evaluate the efficacy of the repairs and the post-repair seismic performance of the prototype bridge that included one or more repaired columns in various locations. For the prototype bridge herein modeled, the results showed that a confinement-enhanced oriented repair would not affect the seismic behavior of the prototype bridge. Increasing the strength of the longitudinal reinforcement could effectively reduce the drift of the prototype bridge in subsequent earthquakes. A full repair configuration for the columns was the most effective method for enhancing the seismic performance of the prototype bridge. To obtain a positive effect on seismic performance, a minimum of two repaired columns was required