A dual-chamber, thick-walled cardiac phantom for use in cardiac motion and deformation imaging by ultrasound

Determination of the mechanical properties of the myocardium is crucial for cardiac diagnosis. Cardiac strain and strain rate imaging may enable such quantification. To further develop these methodologies, an experimental setup allowing the recording of ultrasonic deformation data in a reproducible manner is necessary. Such setup with biventricular polyvinyl alcohol heart phantoms has been built. To test this setup, segmental longitudinal, radial and circumferential displacement, velocity, strain and strain rate in the phantoms were measured using a clinical ultrasound scanner and commercially available deformation imaging algorithms (based on both tissue velocity imaging and speckle tracking). The model deformation was close to that observed in the human left ventricular wall and was highly reproducible (e.g., the average peak longitudinal strain for the mid- and apical phantom segments equals -15.32 +/- 0.53% and -19 +/- 6% for the ventricle wall). The experimental setup is a valuable source of data for the development of algorithms for deformation estimation.status: publishe

Seismic resilience of interdependent built environment for integrating structural health monitoring and emerging technologies in decision-making

The functionality of interdependent infrastructure and resilience to seismic hazards have become a topic of importance across the world. The ability to optimize an engineered solution and support informed decisionmaking is highly dependent on the availability of comprehensive datasets and requires substantial effort to ingest into community-scale models. In this paper, a comprehensive seismic resilience modeling methodology is developed, with detailed multi-disciplinary datasets, and is explored using the state-of-the-science algorithms within the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). The methodology includes a six-step chained/linked process consists of 1) community data and information, 2) spatial seismic hazard analysis using next-generation attenuation, 3) interdependent community model development, 4) physical damage and functionality analysis, 5) socio-economic impact analysis and 6) structural health monitoring (SHM) and emerging technologies (ET). An illustrative case study is presented to demonstrate the seismic functionality and resilience assessment of Shelby County in Memphis, Tennessee, in the United States. From the results discussion, it is then concluded that data from structural health monitoring and emerging technologies is a viable approach to enhance characterising the seismic hazard resilience of infrastructure, enabling rapid and in-depth understanding of structural behaviour in emergency situations. Moreover, considering the momentum of the digitalization era, setting a holistic framework on resilience, which includes SHM and ET, will allow reducing uncertainties that still a challenge to quantify and propagate, supported by sequential updating techniques from Bayesian statistics

Seismic Resilience of Interdependent Built Environment for Integrating Structural Health Monitoring and Emerging Technologies in Decision-Making

This article results from the joint work of the members of IABSE TG.8 “Design Requirements for Infrastructure Resilience” of Working Commission C1.Data Availability Statement: The data that support the findings of this study are available upon reasonable request. Contact the corresponding author for assistance.The functionality of interdependent infrastructure and resilience to seismic hazards has become a topic of importance across the world. The ability to optimize an engineered solution and support informed decision-making is highly dependent on the availability of comprehensive datasets and requires substantial effort to ingest into community-scale models. In this article, a comprehensive seismic resilience modeling methodology is developed, with detailed multi-disciplinary datasets, and is explored using the state-of-the-science algorithms within the interdependent networked community resilience modeling environment (IN-CORE). The methodology includes a six-step chained/linked process consists of: (a) community data and information, (b) spatial seismic hazard analysis using next-generation attenuation, (c) interdependent community model development, (d) physical damage and functionality analysis, (e) socio-economic impact analysis and (f) structural health monitoring (SHM) and emerging technologies (ET). An illustrative case study is presented to demonstrate the seismic functionality and resilience assessment of Shelby County in Memphis, Tennessee, in the United States. From the discussion of results, it is then concluded that data from structural health monitoring and emerging technologies is a viable approach to enhance characterising the seismic hazard resilience of infrastructure, enabling rapid and in-depth understanding of structural behaviour in emergency situations. Moreover, considering the momentum of the digitalization era, setting an holistic framework on resilience that includes SHM and ET will allow reducing uncertainties that are still a challenge to quantify and propagate, supported by sequential updating techniques from Bayesian statistics