Collapse Vulnerability and Fragility Analysis of Substandard RC Bridges Rehabilitated with Different Repair Jackets under Post-Mainshock Cascading Events

Past earthquakes have signaled the increased collapse vulnerability of mainshock-damaged bridge piers and urgent need of repair interventions prior to subsequent cascading hazard events, such as aftershocks, triggered by the mainshock (MS). The overarching goal of this study is to quantify the collapse vulnerability of mainshock-damaged substandard RC bridge piers rehabilitated with different repair jackets (FRP, conventional thick steel and hybrid jacket) under aftershock (AS) attacks of various intensities. The efficacy of repair jackets on post-MS resilience of repaired bridges is quantified for a prototype two-span single-column bridge bent with lap-splice deficiency at column-footing interface. Extensive number of incremental dynamic time history analyses on numerical finite element bridge models with deteriorating properties under back-to-back MS-AS sequences were utilized to evaluate the efficacy of different repair jackets on the post-repair behavior of RC bridges subjected to AS attacks. Results indicate the dramatic impact of repair jacket application on post-MS resilience of damaged bridge piers—up to 45.5 % increase of structural collapse capacity—subjected to aftershocks of multiple intensities. Besides, the efficacy of repair jackets is found to be proportionate to the intensity of AS attacks. Moreover, the steel jacket exhibited to be the most vulnerable repair intervention compared to CFRP, irrespective of the seismic sequence (severe MS-severe or moderate AS) or earthquake type (near-fault or far-fault)

Rolling up the pieces of a puzzle: A systematic review and meta-analysis of the prevalence of toxoplasmosis in Iran

Toxoplasmosis is a neglected parasitic disease with global distribution in warm-blooded vertebrates and high prevalence among different human societies. We contrived a systematic review and meta-analysis on the prevalence of toxoplasmosis in Iran. Following the general methodology recommended for systematic reviews and meta-analysis, four English and three Persian electronic databases were explored up to April 2016. Out of 105,139 examined samples of different hosts, the weighted overall prevalence was 37% (95% CI = 31–43). Due to the significant heterogeneity (I2 = 81.9%) the random-effects model was used. The pool estimated prevalence of toxoplasmosis in human intermediate hosts, animal intermediate hosts, and definitive hosts was 43% (95% CI = 38–47), 26 (95% CI = 17–35) and, 34% (95% CI = 22–46), respectively. Our results represent that regular inspection in food industries, improved screening programs using standard diagnostic assay as well as distinguishing toxoplasmosis condition in other zoonotic hosts are extremely recommended for better disease management in Iran.Keywords: Toxoplasma gondii, Prevalence, Iran, Systematic review, Meta-analysi

Synthesis, characterization and application of novel MnO and CuO impregnated biochar composites to sequester arsenic (As) from water: Modeling, thermodynamics and reusability

© 2020 Elsevier B.V. The present study aimed at enhancing the adsorption potential of novel nanocomposites of Sesbania bispinosa biochar (SBC) with copper oxide (SBC/CuO) and manganese oxide nanoparticles (SBC/MnO) for the efficient and inexpensive removal of environmentally concerned contaminant arsenic (As) from contaminated water at batch scale. The scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, energy dispersive X-ray (EDX), X-ray diffraction (XRD) and point of zero charge (PZC) analyses proved successful impregnation of the metallic nanoparticles on SBC surface. The results revealed the maximum As removal (96 %) and adsorption (12.47 mg/g) by SBC/CuO composite at 10 mg As/L, optimum pH-4, dose 1.0 g/L and ambient temperature (25 ± 1.5 °C) as compared with SBC (7.33 mg/g) and SBC/MnO (7.34 mg/g). Among four types of adsorption isotherms, Freundlich isotherm demonstrated best fit with R2 \u3e 0.997. While pseudo second-order kinetic model revealed better agreement with kinetic experimental data as matched with other kinetic models. The thermodynamic results depicted that As adsorption on the as-synthesized adsorbents was endothermic and spontaneous in nature with increased randomness. The SBC/CuO displayed excellent reusability and stability over four adsorption/desorption cycles and proved that the as-synthesized SBC/CuO composite may be the efficient adsorbent for practical removal of As from contaminated water

A Network-Based Importance Measurement Index for Bridge Security Risk Assessment and Prioritisation

In the related literature, conventional approaches to assessing security risk and prioritising bridges have focused on unique characteristics. Although the unique characteristics appropriately reflect the economic and social consequences of failure, they neglect the consequences of a bridge failure at the network level. If network owners and operators prioritise bridges solely based on their unique characteristics, bridges with low object-level importance and high network-level importance have very low chances to get priority. In this paper, a bridge importance measurement index α(e) has been presented, prioritising bridges based on their unique characteristics, location and network topology. To describe how to use this index α(e), three numerical examples were provided. While the first example was related to a simple hypothetical network, the second and third examples were real networks related to the bridges of Wroclaw city. Using these examples, the results of bridge prioritisation obtained in the unique-characteristics-only state were compared to the state in which α(e) had been used. Results showed that considering the location of the bridge and the topological characteristics of the network change the bridges prioritisation. For instance, in the second example, it was observed that the use of the α(e), made bridge Bolesława Krzywoustego the essential bridge, while bridge Grunwaldzki was the essential bridge under the previous prioritisation made by researchers. However, the results of the third example showed that bridge Milenijny, which was considered the essential network bridge as stated in the previous prioritisation made by researchers, was again selected as the most critical bridge based on the α(e)

New empirical approach for determining nominal shear capacity of steel fiber reinforced concrete beams

The main objective of this paper is to develop new design formulations for determining shear stress of steel fiber-reinforced concrete (SFRC) beams without stirrups using Gene Expression Programming (GEP) and Artificial Neural Networks (ANNs) based on a large number of test results. The proposed formulations relate the average shear stress to geometrical, and material properties of common reinforced concrete beam (effec- tive depth, ratio of shear span to effective depth, compressive strength of concrete, and longitudinal steel reinforcement) and fiber properties (diameter, length, and volume percentage). In order to verify the validity and reliability of the proposed formulations, a comparative assessment was conducted between measured and calculated average shear stress of beams. The comparative assessment is carried out in terms of common and modified coefficient of determination (R and Rm ), root- mean-square error (RMSE), mean absolute per- centage error (MAPE), and gradients of regression lines (k and k’). The results obtained for the considered sta- tistical measures and performance criteria reveal that all of the proposed formulations have acceptable ability to calculate average shear stress for a wide range of shear span to effective depth ratios

New empirical approach for determining nominal shear capacity of steel fiber reinforced concrete beams

The main objective of this paper is to develop new design formulations for determining shear stress of steel fiber-reinforced concrete (SFRC) beams without stirrups using Gene Expression Programming (GEP) and Artificial Neural Networks (ANNs) based on a large number of test results. The proposed formulations relate the average shear stress to geometrical, and material properties of common reinforced concrete beam (effective depth, ratio of shear span to effective depth, compressive strength of concrete, and longitudinal steel reinforcement) and fiber properties (diameter, length, and volume percentage). In order to verify the validity and reliability of the proposed formulations, a comparative assessment was conducted between measured and calculated average shear stress of beams. The comparative assessment is carried out in terms of common and modified coefficient of determination (R and Rm), root- mean-square error (RMSE), mean absolute percentage error (MAPE), and gradients of regression lines (k and k’). The results obtained for the considered statistical measures and performance criteria reveal that all of the proposed formulations have acceptable ability to calculate average shear stress for a wide range of shear span to effective depth ratios

Flexural Strength of Concrete Beams Made of Recycled Aggregates: An Experimental and Soft Computing-Based Study

The implementation of recycled concrete aggregates (RCAs) in the construction industry has been highlighted in the literature recently. This study aimed to propose an intelligent model for predicting the ultimate flexural strength of recycled reinforced concrete (RRC) beams. For this reason, a database comprising experimental tests on concrete beams was compiled from the literature. Additionally, two experimental tests were performed in the laboratory to enhance the aforementioned database. The flexural test results showed a 10% reduction in flexural strength when the RRC beam was tested instead of a conventional beam (constructed with natural aggregates). Nevertheless, an artificial neural network (ANN) improved by particle swarm optimization (PSO), as well as an imperialist competitive algorithm (ICA), were utilized for developing the predictive model. The inputs of the hybrid predictive models of flexural strength were the beam geometrical properties, reinforcement ratio, RCA percentage, compressive strength of concrete, and the yield strength of steel. The overall findings (e.g., correlation coefficient values of 0.997 and 0.994 for the testing data) showed the feasibility of the PSO-based ANN predictive model, as well as the ICA-based ANN predictive model in the flexural assessment of RRC beams. Furthermore, comparing the prediction performances of PSO-based ANN with ICA-based ANN and the conventional ANN showed that the PSO-based ANN model outperformed the predictive model built with the conventional ANN and the ICA-ANN

Innovative Hybrid Reinforcement Constituting Conventional Longitudinal Steel and FRP Stirrups for Improved Seismic Strength and Ductility of RC Structures

The use of fiber reinforced polymer (FRP) reinforcement is becoming increasingly attractive in construction of new structures. However, the inherent linear elastic behavior of FRP materials up to rupture is considered as a major drawback under seismic attacks when significant material inelasticity is required to dissipate the input energy through hysteretic cycles. Besides, cost considerations, including FRP material and construction of pre-fabricated FRP configurations, especially for stirrups, and probable damage to epoxy coated fibers when transported to the field are noticeable issues. The current research has proposed a novel economical hybrid reinforcement scheme for the next generation of infrastructures implementing on-site fabricated FRP stirrups comprised of FRP sheets. The hybrid reinforcement consists of conventional longitudinal steel reinforcement and FRP stirrups. The key feature of the proposed hybrid reinforcement is the enhanced strength and ductility owing to the considerable confining pressure provided by the FRP stirrups to the longitudinal steel reinforcement and core concrete. Reinforced concrete beam specimens and beamcolumn joint specimens were tested implementing the proposed hybrid reinforcement. The proposed hybrid reinforcement, when compared with conventional steel stirrups, is found to have higher strength, stiffness, and energy dissipation. Design methods, structural behavior, and applicability of the proposed hybrid reinforcement are discussed in detail in this paper

Rapid Repair of Earthquake-Damaged RC Columns with Prestressed Steel Jackets

In this study, a lightweight prestressed steel jacket (PSJ) was proposed and developed for rapid and cost-effective repair of a severely damaged circular reinforced concrete column. The PSJ is composed of several prestressed strands, and a thin steel sheet is restrained by these strands, which can be manually wrapped around and jointed to form a jacket on the column as part of a 12-h repair job by two workers. The prestressed strands restrain the thin sheet from buckling, while the steel sheet in turn prevents the strands from cutting into cracked concrete and thus preserves the prestressing forces. The PSJ was validated with cyclic (reversed) testing of two large-scale columns with lap-splice deficiency under incrementally increased displacements every three cycles. The ultimate strength and displacement ductility of the damaged column were restored to 115% and 140%, respectively, of those of the as-built column. The initial stiffness of the damaged column, however, was restored to only 84% of that of the as-built column because the PSJ was designed to restore the strength and ductility only. By connecting the damaged column to its footing through anchored dowel bars, the levels of restoration in ultimate strength, initial stiffness, and displacement ductility were all increased by at least 20%

Mechanical Properties of High Performance Fiber Reinforced Cementitious Composites

Extensive experimental studies on High Performance Fiber Reinforced Cement Composites (HPFRCC) owing to their remarkable properties have been carried out. Statistical studies have been mainly focused on Fiber Reinforced Concrete (FRC). An extensive study, including an experimental/statistical approach addressing key mechanical properties (compressive and flexural strength) and impact resistance of such high performance composites with inclusion of different volume of fibers has been carried out on two-hundred and forty specimens in this research.Results from this study revealed that compressive and flexural strength as well as impact resistance of HPFRCC follow the normal distribution. Furthermore, statistical data analyses (both parametric and nonparametric) showed higher percentage of fibers led in greater values for mechanical properties and impact resistance of HPFRCC. Moreover, based on acquired test results, equations were developed between mechanical properties and impact resistance of HPFRCC materials