Rip currents near coastal structures in Lake Michigan: Characterization and assessment for warnings

Rip currents near coastal structures commonly occur in Lake Michigan in the Great Lakes region of the United States. Lack of timely warning due to undocumented characteristics of rip currents and no assessment tool can contribute to tragic drownings incidents. In this paper, we characterized rip current occurrences near breakwater structures and developed an assessment tool for providing timely rip current warnings to beachgoers at the study site, City of Port Washington, WI. Characteristics of rip currents near the structure were observed from field measurements or visual images. Deflection rip currents had speeds of ～ 0.2 m/s and lasted for several hours. The rip current occurrences were associated with environmental proxies. It was found that rip currents can occur even when the water appears calm near the structure. A Structure Rip Checklist and Assessment Matrix (SRiCAM) with a four-tiered risk was developed and validated using observations. Furthermore, the SRiCAM was integrated into cyberinfrastructure with a data contingency plan to provide real-time warnings to the public. The applicability of the SRiCAM to other locations across Lake Michigan was further tested and results are promising. Overall, the SRiCAM has the potential to be widely extended to foster recreational water safety and resilience to rip current hazards in the Great Lakes.     

Flexural behaviour of RC slabs strengthened with prestressed CFRP strips using different anchorage systems

The Externally Bonded Reinforcement (EBR) technique using Carbon Fiber-Reinforced Polymers (CFRP) has been commonly used to strengthen concrete structures in flexure. The use of prestressed CFRP material offers several advantages well-reported in the literature. Regardless of such as benefits, several studies on different topics are missing. The present work intends to contribute to the knowledge of two commercially available systems that differ on the type of anchorage: (i) the Mechanical Anchorage (MA), and (ii) the Gradient Anchorage (GA). For that purpose, an experimental program was carried out with twelve slabs monotonically tested under displacement control up to failure by using a four-point bending test configuration. The effect of type of anchorage system (MA and GA), prestrain level (0 and 0.4%), width (50 mm and 80 mm) and thickness (1.2 mm and 1.4 mm) of the CFRP laminate, and the surface preparation (grinded and sandblasted) on the flexural response were the main studied parameters. Better performance was observed for the slabs: (i) with prestressed laminates, (ii) for the MA system, and (iii) with sandblasted surface preparation.     

Model Validation for Bridge-Road-Vehicle Dynamic Interaction System

The dynamic response of highway bridges subjected to moving truckloads has been observed to be dependent on (1) dynamic characteristics of the bridge; (2) truck configuration, speed, and lane position on the bridge; and (3) road surface roughness profile of the bridge and its approach. Historically, truckloads were measured to determine the load spectra for girder bridges. However, truckload measurements are either made for a short period of time [for example, weigh-in-motion (WIM) data] or are statistically biased (for example, weigh stations) and cost prohibitive. The objective of this paper is to present results of a 3D computer-based model for the simulation of multiple trucks on girder bridges. The model is based on the grillage approach and is applied to four steel girder bridges tested under normal truck traffic. Actual truckload data collected using a discrete bridge WIM system are used in the model. The data include axle loads, truck gross weight, axle configuration, and statistical data on multiple presence (side by side or following). The results are presented as a function of the static and dynamic stresses in each girder and compared with code provisions for dynamic load factor. The study provides an alternate method for the development of live-load models for bridge design and evaluation.     

History of Construction, Engineering, and Management in the Department of Civil and Environmental Engineering at Penn State

At Penn State, the credit for broadening the Civil Engineering Department’s longstanding academic focus on analysis and design to include the construction phase must go to Dr. Harmer A. Weeden and his longtime associate Dr. Thomas D. Larson. Jack H. Willenbrock joined the Department as an Instructor in June 1968 and grew the construction program so that today about a fourth to a third of the civil undergraduates obtain employment in the construction industry. The program has awarded about 250 postbaccalaureate degrees.     

GPR inspection of concrete bridges

Ground-penetrating-radar (GPR) has become an important method for the non-destructive testing of concrete bridges. Although there are standards and guidelines available today, the quality of results does not only depend on the object inspected but also on the qualification and experience of the team carrying out the radar survey. This situation is unsatisfactory for engineers that have to decide whether a radar survey is suitable to solve their problem.EMPA has been active in the field of non-destructive testing of concrete structures for more than ten years. During this time, procedures for efficient data acquisition, processing interpretation and reporting have been developed. In addition, a large number of concrete structures has been inspected for research and services.In a research project completed in 2005, radar inspections using the EMPA approach were carried out on bridges designated for demolition. Results were laid open before the bridges were taken down. After the demolition radar results were verified with the help of the bridge parts. Thus, the accuracy and reliability of radar surveys was quantified under realistic circumstances.     

Modeling of Moisture Behavior of Wood Planks in Nonvented Flat Roofs

A computer model was extended and adapted to simulate the hygrothermal behavior of building envelope-wood components. The model was used to predict moisture movement in wood planks forming the decks of nonvented flat roofs insulated with cellulose. The gradient of water potential was considered as the driving force for moisture movement in wood. The model required the determination of convective heat- and mass-transfer coefficients, the sorption curves, the effective water conductivity for different wood species, and the hygrothermal conditions within the assembly to characterize the mass-conservation equation. Once these parameters were integrated in the computer model, this approach was then validated by carrying a simulation of the drying process of wood planks using experimental data from a large-scale test.     

Simulation and optimization of SOFC-BCHP system

As the prime motor of dispersed energy system, the high-temperature solid oxide fuel cells (SOFC) are high efficient with large heat recovery. This study presents a simulation of SOFC building-based cooling, heat and power (BCHP) system, which can meet basic requirements in power and heating (cooling) of the designated customers. The peak power load can be met by power grid, while the peak heating (cooling) load requirement can be met by backup equipments. In order to solve the economic dispatch problem of the energy system, a restricted nonlinear optimization model has been developed. The production costs can be minimized via both the equality constraints of customer’s heat and power demands, and other inequality constrains of equipments’ capacities. The sequential quadratic programming method has been used to search the solution. The study indicates that the model can be used to optimize the system’s capacities and run strategy. An office building case has been computed, and it is indicated that the model can be served in design and optimization of SOFC-BCHP system.     

Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications

Uncertainty estimates corresponding to measured hydrologic and water quality data can contribute to improved monitoring design, decision-making, model application, and regulatory formulation. With these benefits in mind, the Data Uncertainty Estimation Tool for Hydrology and Water Quality (DUET-H/WQ) was developed from an existing uncertainty estimation framework for small watershed discharge, sediment, and N and P data. Both the software and its framework-basis utilize the root mean square error propagation methodology to provide uncertainty estimates instead of more rigorous approaches requiring detailed statistical information, which is rarely available. DUET-H/WQ lists published uncertainty information for data collection procedures to assist the user in assigning appropriate data-specific uncertainty estimates and then calculates the uncertainty for individual discharge, concentration, and load values. Results of DUET-H/WQ application in several studies indicated that substantial uncertainty can be contributed by each procedural category (discharge measurement, sample collection, sample preservation/storage, laboratory analysis, and data processing and management). For storm loads, the uncertainty was typically least for discharge (±7–23%), greater for sediment (±16–27%) and dissolved N and P (±14–31%) loads, and greater yet for total N and P (±18–36%). When these uncertainty estimates for individual values were aggregated within study periods (i.e. total discharge, average concentration, and total load), uncertainties followed the same pattern (Q < TSS < dissolved N and P < total N and P). This rigorous demonstration of uncertainty in discharge and water quality data illustrates the importance of uncertainty analysis and the need for appropriate tools. It is our hope that DUET-H/WQ contributes to making uncertainty estimation a routine data collection and reporting procedure and thus enhances environmental monitoring, modeling, and decision-making. Hydrologic and water quality data are too important for scientists to continue to ignore the inherent uncertainty.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.