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The purpose of this study is to examine the influence of additives on estimating the useful service life of self-compacting concrete (SCC). For that, durability tests were performed on 43 SCC mix designs to estimating the service life of SCC based on the FIB model. The investigated supplementary materials included xanthan gum at concentrations of 0.2% and 0.25% by weight of cement, microsilica at concentrations of 5%, 7% and 10% by weight of cement, and nanosilica at concentrations of 2%, 3% and 4% by weight of cement. All 43 designs met the reliability index of the model, thereby obtaining the estimated service life for each design. The findings revealed that in chloride-rich environments, the control sample exhibited greater penetration depth compared to the concretes incorporating xanthan gum, microsilica and nanosilica additives. This observation suggests that the inclusion of xanthan gum extends the service life of SCC due to the formation of a denser and more cohesive structure in the hydration products of xanthan gum-modified concrete. Additionally, the investigations conducted indicate that the presence of nano and micro additives effectively reduces voids, while xanthan gum plays a significant role in minimising cracking and enhancing the thickening properties of the concrete. [ABSTRACT FROM AUTHOR]

The nation's transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a model for predicting the corrosion process in concrete. This model is defined based on the simultaneous infiltration of chloride ions and the phenomenon of carbonation of concrete under certain environmental conditions. For this purpose, the simultaneous effect of chloride ion diffusion and carbonation phenomenon was studied using experiments on the fabricated samples. For this reason, in the first case, the samples are exposed to carbon dioxide once and then to chloride ions. In the latter case, only samples under the influence of chloride infiltration are examined. To make the samples, which include 9 mixing designs, three water-to-cement ratios of 0.35, 0.4 and 0.5 and three percent of 0%, 7% and 10% silica fume have been used. In this study, accelerated chloride ion (RCPT) penetration, capillary adsorption, pressurized water penetration and compressive strength tests of concrete were performed on the samples. Also in control and carbonate samples, the results of long-term experiments including chloride ion penetration and determination of chloride ion profile and determination of chloride ion diffusion coefficient have been investigated. The results of permeability tests show that carbonation has a direct effect on reducing the flow rate in the chloride ion permeation test and also reducing the capillary adsorption coefficient in the water capillary adsorption test. While increasing the ratio of water to cementations materials, the effect of carbonation on reducing the flow rate and also the capillary absorption coefficient of water increases, it should be noted that increasing the percentage of soot silica reduces this effect. Using linear fitting models on the results of long-term experiments, the amount of changes in chloride ion diffusion coefficient due to carbonation of concrete and determination of chloride ion concentration in concrete is presented. [ABSTRACT FROM AUTHOR]

As a matter of fact, structural drift is a random variable that is associated with several bases of the uncertainties related to the loading excitation and structural resistance. Hence, it seems essential to utilize the probabilistic philosophy to provide a design criterion of control the structural drift. The current study was conducted to propose a probabilistic approach to control the structural drift subjected to seismic loading. The main contribution of this manuscript is to propose a new sophisticated design criterion to control the structural drift using the reliability analysis. As-a-state-of-the-art, a new limit state function is established to be utilized for reliability analysis of the considered extreme event. To do so, several different steel frames are analyzed and investigated using the existing design criterion of the ASCE07 code. Also, the analysis of the critical excitations is conducted to deliberate the required target reliability indices for the considered limit state function. Accordingly, the reliability index spectrum is illustrated which revealed that the drift of the structures is related to the fundamental structural period. Eventually, based on the consistency of the reliability index consideration a stylish formula is proposed to control the drift reliability index corresponding to the target reliability indices constraints in the range of 2 to 4 (2 ≤ β ≤ 4). In addition to the main advantage of the proposed design criterion which is to provide a consistent range of the reliability level for different structures. Indeed, the analysis of the critical excitation shows that the reliability index spectrum varies by the fundamental frequency of the structure. Hence, in this research, a new structural drift criterion was proposed to sophisticatedly present the design criterion based on the fundamental structural period. Also, the proposed design criterion contains the deflection amplification factor to conclude the comprehensive inter-story drift control. [ABSTRACT FROM AUTHOR]

Design and evaluation of highway bridges requires the assessment of live loads, which can involve a considerable degree of uncertainties. These uncertainties typically refer to the number of vehicles, weight of vehicles, headway distance, type of vehicles, axle spacing, axle load, speed of vehicles and other factors. Therefore, in order to perform a reliability analysis, it is necessary to consider live load as a random variable. Multiple truck presence (MTP) and headway distance also are two random variables that should be deliberated for the assessment of live load. The basic goal of this study is to update the statistical parameters of in-a-lane MTP, using the recent available weigh-in-motion (WIM) data, and then delineate the relationship between the bridge lengths and the influence of MTP events. However, since MTP is a time-dependent variable, the statistical parameters of MTP influences should be determined for the considered lifetime of the bridge. Therefore, the main contribution of this study is to propose a new methodology to calculate the statistical parameters of MTP for different time periods. The dataset for this study includes WIM data from 19 stations throughout the United States, which were collected by the Federal Highway Administration over 5 years, with timestamp accuracy of one-hundredth of a second. [ABSTRACT FROM AUTHOR]