Probabilistic Characterization of Live Load Using Visual Counts and In-Service Strain Monitoring

It has been argued that the AASHTO LRFD design code for maximum live loads on highway bridges is overly conservative. In an attempt to determine the level of conservativeness, if any, the writers developed a methodology incorporating real-time visual data collection from traffic cameras coupled with structural strain response of girder bridges. Average daily truck traffic along with frequency of multiple presences (same lane as well as adjacent lanes) and lane-wise truck traffic distribution were estimated for a steel-girder highway bridge on I-95 in Delaware. These data compared well with predictions from a Poisson process based model developed for this study. Statistical properties of girder moments in single and multiple presence conditions were determined as well. In this particular example, the girder design moment on the 24.6?foot approach span according to AASHTO specifications was found to be about 3.5 times higher than that estimated from the in-service data.     

Impact of Annual Average Daily Traffic on Highway Runoff Pollutant Concentrations

The objective of this study was to evaluate correlations between annual average daily traffic (AADT) and storm water runoff pollutant concentrations generated from California Department of Transportation (Caltrans) highway sites. Analyses of data collected from the Caltrans four-year (1997–2001) highway runoff characterization program revealed that, in general, pollutant concentrations from urban highways were higher than those found from nonurban highways. For a limited number of pollutants, however, the concentrations from nonurban highways were found to be higher than the concentrations from urban highways. No direct linear correlation was found between highway runoff pollutant event mean concentrations and AADT. However, through multiple regression analyses, it was shown that AADT has an influence on most highway runoff constituent concentrations, in conjunction with factors associated with watershed characteristics and pollutant build-up and wash off. The other noticeable factors shown to influence the accumulation of pollutants on highways were antecedent dry period, drainage area, maximum rain intensity, and land use.     

Simulating Sediment Transport in a Flume with Forced Pool-Riffle Morphology: Examinations of Two One-Dimensional Numerical Models

One-dimensional numerical sediment transport models (DREAM-1 and DREAM-2) are used to simulate seven experimental runs designed to examine sediment pulse dynamics in a physical model of forced pool-riffle morphology. Comparisons with measured data indicate that DREAM-1 and -2 closely reproduce the sediment transport flux and channel bed adjustments following the introduction of fine and coarse sediment pulses, respectively. The cumulative sediment transport at the flume exit in a DREAM-1 simulation is within 10% of the measured values, and cumulative sediment transport at flume exit in a DREAM-2 simulation is within a factor of 2 of the measured values. Comparison of simulated and measured reach-averaged aggradation and degradation indicates that 84% of DREAM-1 simulation results have errors less than 3.3?mm, which is approximately 77% of the bed material geometric mean grain size or 3.7% of the average water depth. A similar reach-averaged comparison indicates that 84% of DREAM-2 simulation results have errors less than 7.0?mm, which is approximately 1.7 times the bed material geometric mean grain size or 11% of the average water depth. Simulations using measured thalweg profiles as the input for the initial model profile produced results with larger errors and unrealistic aggradation and degradation patterns, demonstrating that one-dimensional numerical sediment transport models need to be applied on a reach-averaged basis.     

Long-Term Field Performance of Cold In-Place Recycled Roads in Iowa

Cold in-place recycling (CIR) is one of the most effective methods to rehabilitate asphalt pavements. In fact, most CIR roads have performed well at low cost in Iowa since the first CIR road was constructed in 1986. However, some CIR roads have reached failures earlier than their expected design lives because there is no design standard for designing CIR roads with a limited amount of past performance information. Some of the most prominent problems seemed to have come from selecting CIR in areas where there are poor subgrades. Therefore, it is critical to collect CIR performance data along with falling weight deflectometer (FWD) data in order to develop performance models. The main purpose of this paper is to document that effort. The performance models were developed on the basis of historical data collected from CIR roads in Iowa. First, an inventory of CIR roads was created which includes construction information, subgrade and base characteristics, and traffic levels. In consideration of pavement age, level of traffic, and subgrade condition, 26 test sections were selected from the inventory of CIR roads and pavement surface distress surveys were conducted on these roads using an automated image collection system. Distress data were then compiled to compute pavement condition index (PCI) for each test section. FWD data were collected from each test section to determine its relative soil support condition. Finally, to determine their long-term performance, the PCI values were plotted against the pavement age for each group of pavements categorized by their soil support conditions and traffic levels. Overall, it can be concluded that the CIR roads in Iowa, all under traffic level of annual average daily traffic of 2,000, have performed very well and predicted to last up to 25 years before reaching the poor condition (PCI = 40) when the pavements are to be rehabilitated. The CIR roads with a good subgrade support, however, are predicted to last up to 35 years.     

Subtractive Clustering-Based K-means Technique for Determining Optimum Time-of-Day Breakpoints

In many countries, the most widely used method for timing plan selection and implementation is the time-of-day (TOD) method. In TOD mode, a few traffic patterns that exist in the historical volume data are recognized and used to find the signal timing plans needed to achieve optimum performance of the intersections during the day. Traffic engineers usually determine TOD breakpoints by analyzing 1 or 2?days worth of traffic data and relying on their engineering judgment. The current statistical methods, such as hierarchical and K-means clustering methods, determine TOD breakpoints but introduce a large number of transitions. This paper proposes adopting the Z-score of the traffic flow and time variable in the K-means clustering to reduce the number of transitions. The numbers of optimum breakpoints are chosen based on a microscopic simulation model considering a set of performance measures. By using simulation and the K-means algorithm, it was found that five clusters are the optimum for a major arterial in Al-Khobar, Saudi Arabia. As an alternative to the simulation-based approach, a subtractive algorithm-based K-means technique is introduced to determine the optimum number of TODs. Through simulation, it was found that both approaches results in almost the same values of measure of effectiveness (MOE). The proposed two approaches seem promising for similar studies in other regions, and both of them can be extended for different types of roads. The paper also suggests a procedure for considering the cyclic nature of the daily traffic in the clustering effort.     

Developing a Traffic Closure Integrated Linear Schedule for Highway Rehabilitation Projects

In recent years, the state departments of transportation have implemented a number of highway rehabilitation projects across the country. These projects differ fundamentally from new highway projects in that they require an uninterrupted flow of traffic throughout both the duration and geometric length of the project. Synchronization of traffic closure with the construction activities is crucial in such projects to avoid the traffic conflicts and prevent idle time for equipment and labor. Although most highway rehabilitation projects involve predominantly linear activities, the techniques of linear scheduling are not readily applicable to highway rehabilitation projects due to the conflict between the workzone and traffic flow. This paper documents the development of a traffic closure integrated linear schedule (TCILS) that addresses both traffic closure and work progress issues. The TCILS generates a single schedule for both the construction activities and the associated traffic closures. Visual and graphical features are also applied in the system, which makes it particularly applicable for highway rehabilitation projects. An actual concrete pavement rehabilitation project using the TCILS is presented as a sample of application. The findings from the sample project, although they are limited, show that the TCILS can be applied to an actual project. With recommended future development, the system is believed to be beneficial for both construction practitioners and academics.     

Automated GIS-Based System for Speed Estimation and Highway Safety Evaluation

Although geographic information systems (GISs) have been applied in different areas of transportation, full use of their potential in speed profile analysis and highway design consistency studies has yet to be made. The possibilities that GISs offer for analysis and the increasing number of highway inventories supported by such systems, including traffic data and crash rates, suggest that the implementation of a highway design consistency analysis module within a GIS will facilitate and improve road safety studies. It is with this aim that a GIS-based computer system that builds vehicle speed profiles and analyzes highway design consistency has been developed, in which an operating speed prediction model, acceleration/deceleration rates, and other features can be configured by the engineering user in order to obtain an analysis that is more representative of drivers and local conditions. Application of this system to the study of the design consistency of highways is described, using three examples.     

Grouping in Short-Term Memory: Do Oscillators Code the Positions of Items?

According to several current models of short-term memory, items are retained in order by associating them with positional codes. The models differ as to whether temporal oscillators provide those codes. The authors examined errors in recall of sequences comprising 2 groups of 4 consonants. A critical manipulation was the precise timing of items within the groups, whereby temporal position (time from group onset) and ordinal position (number of items from group onset) were partially unconfounded. Errors that involve items migrating across groups should preserve within-group temporal position according to oscillator models, but should preserve within-group ordinal position according to nonoscillator models. Results from the intergroup errors strongly favored preservation of ordinal rather than temporal position. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling Controlled Water Systems

The particular challenges of modeling controlled water systems are discussed. The high degree of freedom due to the control structures increases the risk of producing the right output for the wrong reasons. On the other hand, many controlled water systems are (partly) manually operated or at least supervised by an operational water manager. The decisions of these managers are not as rigid as a computer simulated control strategy. Therefore, getting a very close fit with a water-system control model is mostly not possible. A modeling framework is proposed that takes advantage of the vast availability of measurement data in controlled water systems. The water level and flow data at control structures allow for intensive validation and subsystem calibration to reduce the degree of modeling freedom and to model separately the natural rainfall-runoff and hydrodynamic processes. The framework is successfully applied to improve a simulation model of the controlled water system of Rijnland, The Netherlands. The yearly volume error was reduced from 11% to less than 1% and as a consequence, the short-term peak events were modeled more accurately as well. The resulting water-system control model is more reliable for both design studies and operational decision support. The framework will contribute to prepare more reliable simulation models of controlled water systems.     

Computer Simulation Model: Construction Analysis for Pavement Rehabilitation Strategies

Most state highways in the United States were built during the 1960s and 1970s with an infrastructure investment of more than $1 trillion. They now exceed their 20?year design lives and are seriously deteriorated. The consequences are high maintenance and road user costs because of degraded road surfaces and construction work zone delays. Efficient planning of highway rehabilitation closures is critical. This paper presents a simulation model, Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS), which estimates the maximum amount of highway rehabilitation/reconstruction during various closure timeframes. The model balances project constraints such as scheduling interfaces, pavement materials and design, contractor logistics and resources, and traffic operations. It has been successfully used on several urban freeway rehabilitation projects with high traffic volume, including projects on I-10 and I-710. The CA4PRS helps agencies and contractors plan highway rehabilitation strategies by taking into account long-life pavement performance, construction productivity, traffic delay, and total cost.     

Activity Calculation by Application of Sub-Regular Solution Model in Binary Oxide Systems

 To confirm sub-regular solution model valid for predicting the activity of component in binary oxide systems, seven systems in the whole concentration and twelve systems presenting saturation concentration have been studied. The total average relative errors of component 1 and 2 are 3.2% and 4.1% respectively by application of the sub-regular solution model into the systems within the whole concentration. However, the total average relative errors are 16% and 1088% in the systems presenting saturation concentration. The results show that sub-regular solution model is not good for predicting the systems presenting saturation concentration, especially for the systems containing acidic or neutral oxide. The reason may be that the influence of the two types of oxide on the configuration is greater in binary oxide systems. These oxides can be present in the form of complex anion partly, Si-O, Al-O, Ti-O and so on, for example (SiO4)4-. That is contrary to sub-regular solution model which is supposed that the oxide systems consist of cation and O2-. But compared with regular solution model and quasi-regular solution model, sub-regular solution model is closer to the characteristics of actual solution and the calculated results are superior.     

Testing and Evaluating Alternative Algorithms for Location Referencing System Route Generation

Modeling the transportation network of roads and highways for data and information system implementations presents unique challenges. The foremost challenge is selecting a modeling methodology that is compatible with the needs and culture of the organization using it. The second challenge is implementing the model in a viable enterprise information system via a database. Transportation information systems must efficiently store network topology and geometry, as well as attributes, and they must be compatible with geographic information systems (GIS). This paper deals with the topological aspects of the highway network. In particular, it describes computing methodologies for generating location referencing system routes. The paper describes the link node referencing system used to build the routes and mentions an alternative approach using GIS. Various algorithms are presented and described, test case results are presented, the algorithms are compared, and evaluation criteria are defined.     

Identification of Environmental Categories for Markovian Deterioration Models of Bridge Decks

In general, state-of-the-art bridge management systems have adopted Markov-chain models to predict the future condition of bridge elements and networks in different environments when various maintenance actions are implemented. However, the categories used to describe the various possible environments for a bridge element are neither accurately defined nor explicitly linked to the external factors affecting the element deterioration. In this paper, a new approach is proposed to provide transportation agencies with an effective decision support tool to identify the categories that best define the environmental and operational conditions specific to their bridge structures. This approach is based on genetic algorithms to determine the combinations of deterioration parameters that best fit each environmental category. The proposed approach is applied to develop Markovian deterioration models for concrete bridge decks using actual data obtained from the Ministére des Transports du Québec. This application illustrates the ability of the proposed approach to correlate the definition of environmental categories to parameters, such as highway class, region, average daily traffic, and percentage of truck traffic, in an accurate and efficient manner.     

Dissimilar items benefit from phonological similarity in serial recall.

In short-term serial recall, similar sounding items are remembered less well than items that do not sound alike. This phonological similarity effect has been observed with lists composed only of similar items, and also with lists that mix together similar and dissimilar items. An additional consistent finding has been what the authors call dissimilar immunity, the finding that ordered recall of dissimilar items is the same whether these items occur in pure dissimilar or mixed lists. The authors present 3 experiments that disconfirm these previous findings by showing that dissimilar items on mixed lists are recalled better than their counterparts on pure lists if order errors are considered separately from intrusion errors (Experiment 1), or if intrusion errors are experimentally controlled (Experiments 2 and 3). The memory benefit for dissimilar items on mixed lists poses a challenge for current models of short-term serial recall. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rethinking how family researchers model infrequent outcomes: A tutorial on count regression and zero-inflated models.

Marital and family researchers often study infrequent behaviors. These powerful psychological variables, such as abuse, criticism, and drug use, have important ramifications for families and society as well as for the statistical models used to study them. Most researchers continue to rely on ordinary least-squares (OLS) regression for these types of data, but estimates and inferences from OLS regression can be seriously biased for count data such as these. This article presents a tutorial on statistical methods for positively skewed event data, including Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. These statistical methods are introduced through a marital commitment example, and the data and computer code to run the example analyses in R, SAS, SPSS, and Mplus are included in the online supplemental material. Extensions and practical advice are given to assist researchers in using these tools with their data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Truck Loading and Fatigue Damage Analysis for Girder Bridges Based on Weigh-in-Motion Data

Based on data collected by weigh-in-motion (WIM) measurements, truck traffic is synthesized by type and loading condition. Three-dimensional nonlinear models for the trucks with significant counts are developed from the measured data. Six simply supported multigirder steel bridges with spans ranging from 10.67 m (35 ft) to 42.67 m (140 ft) are analyzed using the proposed method. Road surface roughness is generated as transversely correlated random processes using the autoregressive and moving average model. The dynamic impact factor is taken as the average of 20 simulations of good road roughness. Live-load spectra are obtained by combining static responses with the calculated impact factors. A case study of the normal traffic from a specific site on the interstate highway I-75 is illustrated. Static loading of the heaviest in each truck type is compared with that of the American Association of State Highway and Transportation Officials standard design truck HS20-44. Several important trucks causing fatigue damage are found.     

Development and internal validation of an in vitro-in vivo correlation for a hydrophilic metoprolol tartrate extended release tablet formulation

PURPOSE: To develop and validate internally an in vitro-in vivo correlation (IVIVC) for a hydrophilic matrix extended release metoprolol tablet. METHODS: In vitro dissolution of the metoprolol tablets was examined using the following methods: Apparatus II, pH 1.2 & 6.8 at 50 rpm and Apparatus I, pH 6.8, at 100 and 150 rpm. Seven healthy subjects received three metoprolol formulations (100 mg): slow, moderate, fast releasing and an oral solution (50 mg). Serial blood samples were collected over 48 hours and analyzed by a validated HPLC assay using fluorescence detection. The f2 metric (similarity factor) was used to analyze the dissolution data. Correlation models were developed using pooled fraction dissolved (FRD) and fraction absorbed (FRA) data from various combinations of the formulations. Predicted metoprolol concentrations were obtained by convolution of the in vivo dissolution rates. Prediction errors were estimated for Cmax and AUC to determine the validity of the correlation. RESULTS: Apparatus I operated at 150 rpm, and pH of 6.8 was found to be the most discriminating dissolution method. There was a significant linear relationship between FRD and FRA when using either two or three of the formulations. An average percent prediction error for Cmax and AUC for all formulations of less than 10% was found for all IVIVC models. CONCLUSIONS: The relatively low prediction errors for Cmax and AUC observed strongly suggest that the metoprolol IVIVC models are valid. The average percent prediction error of less than 10% indicates that the correlation is predictive and allows the associated dissolution data to be used as a surrogate for bioavailability studies.     

Calibration and Verification of a 2D Hydrodynamic Model for Simulating Flow around Emergent Bendway Weir Structures

The predictive capability of a two-dimensional (2D)-hydrodynamic model, the finite-element surface water modeling system (FESWMS), to describe adequately the flow characteristics around emergent bendway weir structures was evaluated. To examine FESWMS predictive capability, a sensitivity analysis was performed to identify the flow conditions and locations within the modeled reach, where FESWMS inputs for Manning’s n and eddy viscosity must be spatially distributed for to better represent the river bed flow roughness characteristics and regions where the flow is highly turbulent in nature. The sensitivity analysis showed that high flow conditions masked the impact of Manning’s n and eddy viscosity on the model outputs. Therefore, the model was calibrated under low flow conditions when the structures were emergent and had the largest impact on the flow pattern and model inputs. Detailed field measurements were performed under low flow conditions at the Raccoon River, Iowa for model calibration and verification. The model predictions were examined for both spatially averaged and distributed Manning’s n and eddy viscosity model input values within the study reach for an array of emergent structures. Spatially averaged model inputs for Manning’s n and eddy viscosity provided satisfactory flow depth predictions but poor velocity predictions. Estimated errors in the predicted values were less than 10% for flow depth and about 60% for flow velocity. Distributed Manning’s n and eddy viscosity model inputs, on the contrary, provided both satisfactory flow depth and velocity predictions. Further, distributed inputs were able to mimic closely the recirculation flow pattern in the wake region behind the bendway weir structures. Estimated errors in the predicted values were less than 10 and 25% for flow depth and velocity, respectively. Overall, in the case of distributed model inputs, FESWMS provided satisfactory results and allowed a closed depiction of the flow patterns around the emergent bendway weirs. These findings suggest that 2D models with spatially distributed values for Manning’s n and eddy viscosity can adequately replicate the velocity vector field around emergent structures and can be valuable tools to river managers, except in cases when detailed three-dimensional flow patterns are needed. The study was limited to the examined low flow conditions, and more field data, especially under high flow conditions, are necessary to generalize the findings of this study regarding the model prediction capabilities.     

Evaluation of Various Surface Irrigation Numerical Simulation Models

In this study, a zero-inertia model (ZIMOD) is presented to simulate all phases of border and furrow irrigation systems. The governing equations were discretized using a control volume of moving cells, by procedures reported in the literature for borders and for furrows. Later, the discretized equations were linearized by applying a Taylor series expansion according to the Newton-Raphson procedure, and then the algebraic linearized equations were iteratively solved using the Gaussian elimination technique. The ZIMOD was verified against several field experimental data and output of various numerical models in the SIRMOD package. Computational times, errors in predicting advance and recession trajectories, and estimated runoff and infiltrated volumes were compared. All models used in the comparative analysis predicted the advance and recession times and the infiltrated and runoff volumes satisfactory. However, models in the SIRMOD package were computationally faster than ZIMOD.     

Developing Regression Models for Predicting Pan Evaporation from Climatic Data—A Comparison of Multiple Least-Squares, Principal Components, and Partial Least-Squares Approaches

Regression models for predicting daily pan evaporation depths from climatic data were developed using three multivariate approaches: multiple least-squares regression (MLR), principal components regression (PCR), and partial least-squares (PLS) regression. The objective was to compare the prediction accuracies of regression models developed by these three approaches using historical climatic datasets of four Indian sites that are located in distinctly different climatic regimes. In all cases (three approaches applied to four climatic datasets), regression models were developed using a part of the data and subsequently validated with the remaining data. Results indicated that although performances of the regression models varied from one climate to another, more or less similar prediction accuracies were obtained by all three approaches, and it was difficult to identify the best approach based on performance statistics. However, the final forms of the regression models developed by the three approaches differed substantially from one another. In all cases, the models derived using PLS contained the smallest number of predictor variables; between two to three out of a possible maximum of six predictor variables. The MLR approach yielded models with three to six predictor variables, and PCR models included all six predictor variables. This implies that the PLS regression models are the most parsimonious in terms of input data required for estimating epan from climate variables, and yet yield predictions that are almost as accurate as the more data-intensive MLR and PCR models.