Considerações sobre os métodos de dimensionamento estrutural de pavimentos com camadas recicladas a frio com espuma de asfalto.

A reciclagem profunda com espuma de asfalto tem sido uma alternativa de sucesso para a restauração de pavimentos degradados. Em relação às soluções tradicionais de reabilitação, como os recapeamentos, tem a vantagem de proporcionar a correção de defeitos em camadas inferiores, com a manutenção ou pequena elevação do greide da pista, além de ganhos ambientais, como um menor consumo de materiais virgens da natureza e redução do volume de material descartado. Entretanto, no Brasil não há método para dimensionamento estrutural para esta tecnologia, o que dificulta seu emprego. Para o desenvolvimento de um procedimento de dimensionamento que contemple este tipo de solução, foram estudados métodos presentes na bibliografia internacional: guia da AASHTO de 1993 e Caltrans, dos EUA, TRL386 e TRL611, da Inglaterra, as duas versões do guia sul-africano TG2 e os métodos oriundos do Austroads, tanto o procedimento interino de 2011 como adaptações de órgãos da Austrália e Nova Zelândia. Observou-se divergência de opiniões quanto ao comportamento do material reciclado com espuma de asfalto. Alguns órgãos e autores consideram o comportamento do mesmo mais próximo às misturas asfálticas, sendo o mecanismo de falha o trincamento, e outros o definem como semelhante a um material granular modificado com alta coesão e ruptura devido às deformações permanentes. Correlaciona-se tal associação ao teor de espuma usualmente utilizado nas obras rodoviárias. Outros aspectos que se destacam para este tipo de base são o ganho de resistência ao longo do tempo devido à cura, mesmo com início da operação da rodovia e a importância da infraestrutura remanescente no dimensionamento. Tais fatos foram corroborados pelos estudos de caso e resultados do trecho experimental construído na Rodovia Ayrton Senna - SP 070, monitorado por meio de ensaios deflectométricos com FWD durante um ano. Como resultado do trabalho, foi proposto um procedimento para o dimensionamento estrutural de pavimentos com camadas recicladas a frio com espuma de asfalto utilizando dados deflectométricos que atende o método do Manual de Pavimentação do Departamento Nacional de Infraestrutura de Transportes (DNIT) e incorpora diferentes aspectos na análise mecanicista. Outras conclusões são a viabilidade técnica a longo prazo da solução mencionada e a importância do controle tecnológico, com ênfase para o monitoramento deflectométrico nos primeiros meses de operação do pavimento para averiguar a evolução da cura do material.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Accident prediction model for railway-highway interfaces

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes. Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.

Road crash proneness prediction using data mining

Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

Prediction of tread block forces for a free-rolling tyre in contact with a rough road

This paper describes a new approach to model the forces on a tread block for a free-rolling tyre in contact with a rough road. A theoretical analysis based on realistic tread mechanical properties and road roughness is presented, indicating partial contact between a tread block and a rough road. Hence an asperity-scale indentation model is developed using a semi-empirical formulation, taking into account both the rubber viscoelasticity and the tread block geometry. The model aims to capture the essential details of the contact at the simplest level, to make it suitable as part of a time-domain dynamic analysis of the coupled tyre-road system. The indentation model is found to have a good correlation with the finite element (FE) predictions and is validated against experimental results using a rolling contact rig. When coupled to a deformed tyre belt profile, the indentation model predicts normal and tangential force histories inside the tyre contact patch that show good agreement with FE predictions. © 2012 Elsevier B.V..

Prediction of outcome in patients with low-grade squamous intraepithelial lesions by fluorescence in situ hybridization analysis of human papillomavirus, TERC, and MYC

BACKGROUND Cytology is an excellent method with which to diagnose preinvasive lesions of the uterine cervix, but it suffers from limited specificity for clinically significant lesions. Supplementary methods might predict the natural course of the detected lesions. The objective of the current study was to test whether a multicolor fluorescence in situ hybridization (FISH) assay might help to stratify abnormal results of Papanicolaou tests. METHODS A total of 219 liquid-based cytology specimens of low-grade squamous intraepithelial lesions (LSIL), 49 atypical squamous cells of undetermined significance (ASCUS) specimens, 52 high-grade squamous intraepithelial lesion (HSIL) specimens, and 50 normal samples were assessed by FISH with probes for the human papillomavirus (HPV), MYC, and telomerase RNA component (TERC). Subtyping of HPV by polymerase chain reaction (PCR) was performed in a subset of cases (n=206). RESULTS There was a significant correlation found between HPV detection by FISH and PCR (P<.0001). In patients with LSILs, the presence of HPV detected by FISH was significantly associated with disease progression (P<.0001). An increased MYC and/or TERC gene copy number (>2 signals in>10% of cells) prevailed in 43% of ASCUS specimens and was more frequent in HSIL (85%) than in LSIL (33%) (HSIL vs LSIL: P<.0001). Increased TERC gene copy number was significantly correlated with progression of LSIL (P<.01; odds ratio, 7.44; area under the receiver operating characteristic curve, 0.73; positive predictive value, 0.30; negative predictive value, 0.94) CONCLUSIONS: The detection of HPV by FISH analysis is feasible in liquid-based cytology and is significantly correlated with HPV analysis by PCR. The analysis of TERC gene copy number may be useful for risk stratification in patients with LSIL.

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