Derya Deniz

Evaluation of Expansive Characteristics of Reclaimed Asphalt Pavement and Virgin Aggregate Used as Base Materials

Reclaimed asphalt pavement (RAP) is reprocessed hot-mix asphalt pavement material that contains asphalt and aggregates. A viable solution for disposing of large quantities of RAP is to incorporate it into base and subbase applications for highway construction. This paper compares the expansive properties of RAP materials, especially the ones including recycled steel slag aggregates, with those of the virgin aggregates to evaluate their potential use as pavement base materials. Seventeen RAP materials and virgin aggregates collected in Illinois were tested for their expansive characteristics in the laboratory, following the ASTM D4792 test method. The specimens in California bearing ratio test molds were submerged into a high-alkali cement–water solution and kept soaked at 70°C to accelerate hydration reactions. Some steel slag aggregates showed considerably high expansion potential, up to 6.2% swell, when compared with other virgin aggregates, such as siliceous gravel and crushed dolomite, which had minor or almost no expansion. The RAP materials, which often had lower densities, exhibited more of an initial settlement or contraction before any expansion with time. Two RAP materials—surface RAP, with 92% steel slag aggregates, and steel slag RAP—gave the maximum expansion amounts of 1.69% and 1.46%, respectively. Although the RAP materials had much lower tendencies to expand than did the virgin steel slag aggregates, the use of RAP materials containing high percentages of steel slag aggregates may have to be avoided in the pavement substructure layers, depending on the level of expansion.

Information Deficits and Community Disaster Resilience

AbstractInformation infrastructures facilitate communication between community stakeholders through a combination of organizational, technological, and human systems and processes. These systems an...

Flood loss models for residential buildings, based on the 2013 Colorado floods

Flooding is the most costly natural hazard event worldwide and can severely impact communities, both through economic losses and social disruption. To predict and reduce the flood risk facing a community, a reliable model is needed to estimate the cost of repairing flood-damaged buildings. In this paper, we describe the development and assessment of two models for predicting direct economic losses for single-family residential buildings, based on the experience of the 2013 Boulder, Colorado riverine floods. The first model is based on regression analyses on empirical data from over 3000 residential building damage inspections conducted by the Federal Emergency Management Agency (FEMA). This model enables a probabilistic assessment of loss (in terms of FEMA grants paid to homeowners for post-flood repairs) as a function of key building and flood hazard parameters, considering uncertainties in structural properties, building contents, and damage characteristics at a given flood depth. The second model is an assembly-based prediction of loss considering unit prices for damaged building components to predict mean repair costs borne by the homeowner, which is based on typical Boulder construction practices and local construction and material costs. Comparison of the two proposed models illustrates benefits that arise from each of the two approaches, while also serving to validate both models. These models can be used as predictive tools in the future, in Boulder and other US communities, due to adaptability of the model for other context, and similarities in home characteristics across the country. The assembly-based model quantifies the difference between the FEMA grants and true losses, providing a quantification of out-of-pocket homeowner expenses.

Energy-based seismic collapse risk assessment of structures

Structural collapse is traditionally associated with the exceedance of a target value of inter-story drift or plastic hinge rotation at structural components. However, such an approach may not accurately estimate the structural collapse potential due to load redistribution and variation of structural damage within the structure. Moreover, collapse prediction may be sensitive to such assumed threshold values. Therefore, in this study, energy balance of a structural system is utilized to represent the severe structural damage history that eventually leads to structural collapse. Performing energy-based collapse analyses, a new dynamic-instability based collapse criterion is developed and key collapse measures are identified. Using the results, a new collapse fragility model is then established for estimating and improving structural reliability against collapse. Moreover, extensive parametric studies are performed to investigate sensitivity of collapse fragilities to variability in structural and earthquake parameters.

Validation of a Finite Element Approach to Modeling of Structural Collapse of Steel Structures

The prediction of collapse of structures has gained growing attention recently, as it is important to be able to predict and model structural collapse due to extreme loads. A lack of accurate and validated structural collapse models significantly limits the structural engineering community to predict possible extreme loads that precipitate collapse. This paper proposes an integrated platform for validated prediction of collapse of steel structures that accounts for material softening followed by elimination of finite elements to enable simulation of fracture. The proposed approach employs a void growth model (VGM) to simulate the initiation of softening and the Hillerborg model for modeling the softening itself, followed by an element deletion strategy that is developed in this framework. The parameters of these models were calibrated to a comprehensive set of experimental test results of circumferentially notched tensile (CNT) coupon specimens. These calibrated models were then validated through comparison with a broad array of experimental test results of steel structures, ranging in complexity from tensile coupons to moment-resisting beam-to-column connections. The proposed approach is shown to be accurate. Through element deletion, the formulation can account for complete structural component separation, thus precipitating modeling of the collapse of structures. This approach thus enables high-fidelity parametric simulation capabilities of interest to researchers, practitioners, and code developers who address collapse of structures.