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Many design codes, such as ACI 318−19, ACI 352.1R-11 and ASCE 41−17, offer deterministic inter-storey drift limit functions of the gravity shear ratios for flat slab floor systems acting as the primary lateral load-resisting system. However, such deterministic limits are not capable of capturing the inherent aleatory uncertainty in the damage capacities of slab-column connections, inducing unknown failure risks during seismic events. To address this, seismic fragility analysis is conducted to generate fragility curves relating the probability of a connection exceeding a performance level or damage state to the inter-story drift ratio and gravity shear ratio. The developed fragility curves are based on an updated experimental database of 221 interior reinforced concrete and post-tensioned slab-column connections without and with shear reinforcement under combined gravity and lateral loadings. Two damage states are introduced, yielding and failure due to punching shear or flexure. The developed fragility curves are used as basis for generating reliability-based formulations and charts to aid designers in determining the drift limits as a function of the design gravity shear ratio as well as a chosen reliability index. The analysis showed that connections with continuous bottom reinforcement, shear reinforcement, or prestressing have enhanced drift capacities and reliability. Also, higher gravity shear ratios significantly lower the limit drift ratio of both reinforced concrete and post-tensioned slab-column connections without shear reinforcement at a given reliability index value. Comparing the proposed reliability-based drift limits to the deterministic limits in ACI 318−19, ACI 352.1R-11 and ASCE 41−17 revealed that the code limits tend to correspond to a reliability index ranging from about 0 to 2.5 for connections without shear reinforcement; and 3 to 8 for connections with shear reinforcement. The existing design limits for slab-column connections without shear reinforcement are least reliable at high gravity shear ratios with reliability index generally below 1.25. These results signify that the proposed reliability-based limits can prompt more informed risk-based designs, especially for connections without shear reinforcement. [ABSTRACT FROM AUTHOR]

Evaluating the dynamic behavior of corroded pipelines conveying fluids is essential to guard against resonance and fatigue failures. However, existing solutions for obtaining the dynamic characteristics, such as natural frequencies, lack an updating methodology based on new corrosion inspection data, hindering effective planning for preventing corrosion damages. Thus, this article introduces a novel framework for characterizing the natural frequency of corroded pipelines conveying fluids. The framework simulates fluid-structure parameters using Gaussian random fields, modified using fuzzy membership functions to account for corrosion effects as identified from field inspection. Based on these fuzzy-random fields, piecewise fuzzy-probabilistic formulations are developed for the natural frequency of pipeline systems function of (1) dimensionless fluid-structure parameters to facilitate adaptation for various pipeline systems; (2) a pipeline condition index (PCI) to enable updates with new corrosion inspection data; and (3) a user-defined safety margin to accommodate different safety requirements. Numerical examples are presented, showcasing the ability of the proposed piecewise formulations to estimate the natural frequencies with R2 ranging from 90.8% to 99.8%. • Fuzzy-probabilistic assessment of corroded pipes conveying fluids. • Simulate the uncertainty in corrosion quantification using the fuzzy logic theory. • Model the uncertainty in FSI parameters using the random field theory. • Formulate a pipe condition index via field inspection to estimate corrosion level. • Parametric formulas for natural frequencies of pipes given condition and properties. [ABSTRACT FROM AUTHOR]

Seismic evaluations of bridges are critical to ensure the post-earthquake integrity of transportation networks; however, systematic evaluations are costly. Hence, bridge management systems have developed screening policies to identify the most seismically vulnerable bridges. Nevertheless, such policies are typically qualitative and may not easily capture the impact of bridge aging or the uncertainty in material and structural parameters, leading to potentially underrated vulnerability estimates. Thus, a new quantitative-yet-practical framework is proposed to screen bridges given the fragilities of deteriorating critical components, namely bearings and columns. The framework uses fuzzy-logic to integrate deterioration data from routine visual inspections into fragility analysis. Then, parameterized fuzzy-fragility models are developed for columns and bearings given their deterioration level, bridge design parameters, and seismic intensity. These models are utilized to develop a seismic vulnerability ranking system to set bridge priorities for detailed seismic investigation. The analysis revealed that bridge vulnerability ranking could significantly increase with deterioration. • Proposes a practical framework to estimate seismic fragility of deteriorating bridges. • Formulates fuzzy condition indices based on visual inspection to update fragility estimates. • Develops fuzzy-fragility models function of condition and design parameters. • Demonstrates how fuzzy-fragility models can be used to rank the seismic vulnerability of bridges. [ABSTRACT FROM AUTHOR]

• Identifies bridge bearing lifetime demands for a range of typical highway bridge designs. • Develops prediction models for number of cycles and cycles displacements. • Explores trends in demands for various loading and bridge design parameters. • Demonstrates how prediction models can be used to derive customized bridge bearing loading protocols. A good replacement and maintenance policy for bridge bearings is essential for bridge integrity and functionality. This requires proper estimation of the bearing life expectancy which in turn is dependent on the working condition demands. The lifetime travel and peak displacement demands are highly sensitive to the loading, bridge geometry, and bearing properties. Hence, predicting when bearings should be replaced is difficult. To facilitate the decision making process, this study proposes prediction models for the annual demands of elastomeric bridge bearings. First, random bridge configurations (e.g. elements geometry, deck type, and number of spans) and random loading conditions (e.g. temperature profiles, earthquake records, and traffic loading scenarios) are generated using Monte Carlo simulation combined with Latin hypercube sampling, and the bearing demands are computed. Bearing demand prediction models are then developed via regression analysis and used to create a general fatigue loading protocol. This protocol can be used for testing and rating sample bearings. This would aid in predicting the bearing life expectancy, allowing for better replacement scheduling, and budget estimation. The application of the proposed demand prediction models for generating fatigue loading protocols is demonstrated through a case study. [ABSTRACT FROM AUTHOR]

Background: Breast imaging reporting and data system (BIRADS) III and IV lesions are considered indeterminate breast lesions and an imaging dilemma. Contrast enhanced MRI shows high sensitivity in detecting these lesions but with low specificity leading to unnecessary biopsy in some of them and high false positive rate. So there was a need for new imaging techniques to raise the specificity of MRI. One of these new imaging techniques is MRS which can improve breast cancer diagnosis especially in indeterminate breast lesions. IT is a noninvasive method that can be added to the DCE-MRI of the breast increasing only the time of examination but allow better characterization of lesions depending on their chemical composition. Objective: To assess the diagnostic value of recent MR imaging modalities in diagnosis of problematic breast lesions categorized by mammography or sonomammography as (BIRADS III and IV) and correlation of these findings with available histopathological findings, clinical data or follow up. Patients and Methods: Study was carried out in the Radiology Department of Al-Azhar University Hospitals. The work took place during the period between May 2017 and June 2018. A total of 35 patients, presented with breast lesions for characterization, were included in the study. Results: We found that MRS measurement increased the specificity of the breast MRI in characterizing different breast lesions especially when it is combined with conventional dynamic MRI. Conclusion: MRS is a noninvasive scan that can be added easily to standard breast MRI protocols as an adjuvant tool. Detection of choline peak using choline SNR can accurately differentiate benign from malignant breast lesions especially indeterminate breast lesions with high sensitivity and specificity especially by adding its results with the results of the standard DCE- MRI scan. [ABSTRACT FROM AUTHOR]