Baris Salman

Modeling Failure of Wastewater Collection Lines Using Various Section-Level Regression Models

AbstractWastewater utilities are aiming to implement asset management strategies to minimize costly emergency repairs, to justify expenditures, and to optimize future renewal actions. Consequently, development of deterioration models that explain the behavior of wastewater lines and provide predictions regarding potential future condition levels is gaining importance. In this paper, deterioration models are generated to estimate the probability of failure values for sewer sections. A set of variables was obtained by examining the inventory and inspection databases of a sewer network. Three statistical methods (ordinal regression, multinomial logistic regression, and binary logistic regression) were employed in successive steps. Proportionality of odds assumption was tested for ordinal regression models, and suitability of this particular method was discussed. Estimated condition ratings were compared with observed data, and the binary logistic regression model was found to be more suitable for predicting ...

Risk Assessment of Wastewater Collection Lines Using Failure Models and Criticality Ratings

AbstractBecause of deteriorating condition levels of wastewater networks and financial constraints, sewer agencies are seeking methods to prioritize inspection of sewer pipes on the basis of risk of failure. Risk assessment of sewer pipes requires integration of the probability and consequences-of-failure values in a way that reflects the decision maker’s perception of risk. This paper presents the use of a weighted scoring method to determine criticality of sewer pipelines. The procedure involves identifying important factors, determining the relative importance of the selected factors, and summarizing the overall performance of sewer pipes in terms of these factors. Determination of risk of failure by combining the resultant consequence-of-failure values with the probability-of-failure values using simple multiplication, risk matrices, and fuzzy inference systems is presented. Application of these methods is illustrated by using the sewer network information obtained from a local wastewater agency. The ...

Use of Trenchless Technologies for a Comprehensive Asset Management of Culverts and Drainage Structures

Due to an aging and rapidly deteriorating transportation infrastructure, agencies are facing the challenge of making quick and reliable decisions regarding the repair and renewal of their assets. While comprehensive asset management strategies have been developed for the visible components of the highway system, such as bridges and pavement, culverts and drainage structures are often neglected. The investigators recently completed an MRUTC project in which they have investigated the current culvert asset management practices of transportation agencies and also developed the inventory and inspection protocols necessary for establishing an effective culvert asset management program. This study builds upon the findings of the previous research project and focuses on the application of trenchless technologies for inspection, construction, repair and renewal of culverts. A literature search, a survey of departments of transportation and a survey of technology providers have been conducted to identify and characterize trenchless technology methods used for buried pipes. The limitations of trenchless technologies in terms of applicability to culverts are investigated. Steps of establishing a comprehensive culvert asset management strategy are identified. Based upon the findings a decision support system is developed which will help the decision makers identify the optimum repair/renewal procedures as a function of the condition of the culvert.

Culvert Asset Management Practices and Deterioration Modeling

Drainage infrastructure systems and culverts constitute an important portion of highway assets that require routine inspections, maintenance, and timely repair and renewal. Variations in structural characteristics (i.e., material type, shape, and dimension), environmental exposure, and wide geospatial distribution of these infrastructure assets accompanied with strict budget restrictions pose significant challenges for transportation agency officials. Deterioration models constitute one of the most essential components of any infrastructure asset management strategy; these models provide insight on the significant factors that affect infrastructure condition states and expected behavior of infrastructure assets under different conditions. The objectives of this study are to provide a review of previous studies on factors that affect culvert performance and durability and those on culvert asset management, to present current practices of transportation agencies with regard to management of culverts, and, last, to present development of a preliminary deterioration model that will allow decision makers to identify significant factors that affect deterioration of metal culverts and prioritize inspection procedures. The preliminary deterioration model presented in this study is developed by employing binary logistic regression with a forward stepwise variable selection method on data obtained from the Ohio Department of Transportation.

Development of an asset management framework for culvert inventory and inspection

The deteriorating highway culvert infrastructure has become a major challenge for the 21 st century. While more importance usually is given to highway embankments, pavements, and bridges, the maintenance of culverts has commonly been neglected. As many culverts reach the end of their design life, the state Departments of Transportation (DOTs) are in need of a model to track the existing culverts and forecast their conditions. Therefore, the main goals of this research is to develop a framework for culvert inventory and inspection by providing protocols and condition rating systems for culvert inventory and inspection, and validate the developed framework by conducting field pilot studies. Performance scores for the culverts are calculated using an analytical hierarchy process (AHP) to determine the magnitude of the deterioration and assist in short and long term planning. This study focuses on concrete, corrugated metal, and plastic culverts spanning less than or equal to 10 feet (3 meters). The developed model contributes to an effective culvert asset management strategy.

Accelerating construction of roadway bridges using alternative techniques and procurement methods

Approximately a quarter of the bridges in the United States are classified as either functionally obsolete or structurally deficient by the United States Department of Transportation (USDOT). As such, transportation agencies are challenged to handle the increasing need of upgrades with limited resources. Accelerated Bridge Construction (ABC) can reduce the construction duration and can decrease the environmental and socio-economic impacts of repair and upgrade activities by minimizing traffic disruptions. As several states are using accelerated construction techniques, a standard guideline would be highly beneficial for these agencies in developing or improving the ABC decision-making process. As problems are often project specific, a decision tool can assist in determining the viability of ABC over traditional construction methods and in selecting appropriate construction and contracting strategies on a case-by-case basis. This paper presents findings of a recent survey with regards to utilization of ABC strategies by state Departments of Transportation (DOTs), and a decision support framework which consists of three models: (1) Analytical Hierarchy Process (AHP) based ABC vs. traditional construction decision-making model; (2) ABC alternatives selection model; and (3) procurement method and contract selection model. The paper also discusses the use of ABC in New York State and describes a New York State bridge project to validate the AHP model. First published online 02 May 2017

Life-cycle benefit-cost analysis framework for ramp-metering deployments

The primary objectives of ramp metering are to reduce congestion on freeways by restricting the total flow entering the freeway and to discourage short-distance travelers from using the freeway. Life-cycle cost analysis of ramp-metering deployments has received attention in particular for identifying the strategy with the lowest cost. However, increasing concerns over the effects of congestion on the environment and increasing rates of accidents are urging decision makers to consider the environmental and social effects of ramp-metering deployments in addition to agency costs. This paper presents a high-level benefit–cost analysis framework for ramp-metering deployments. The framework was constructed in consideration of the triple bottom line of sustainability (i.e., economic, environmental, and social factors). More specifically, the framework is made up of four main components: (a) life-cycle cost analysis, (b) analysis of benefits achieved through travel time savings, (c) analysis of benefits achieved through reductions in energy consumption, and (d) analysis of benefits achieved through reductions in the number of accidents. A hypothetical case study is used to demonstrate the application of the framework. A sensitivity analysis is conducted to determine the effects of higher traffic demand on the benefits achieved. It is expected that the proposed framework can improve the high-level decision-making procedures of transportation agencies in regard to the deployment of ramp meters.