Assessment of time-dependent structural resistance of RC bridges in the Barak valley region, Assam, India

The reinforced concrete (RC) bridges deteriorate essentially due to strength loss induced by aging of the structure, extreme weathering conditions, and unplanned increased service loads. However, these load variations and aging factors equally could compromise structural reliability, and service life for continuous satisfactory operation of service bridges for future performance. A reasonable model of bridge strength and applied loads becomes the basis of accurate prediction of bridge functionality. Hence, time-dependent reliability approaches could be used efficiently to gain a reliable understanding of issues facing by the bridges in the study area for appropriate solutions. In this paper, the reliability of bridges under harsh conditions studied using time-variant and time-invariant reliability models in which both load and resistance considered as a time-dependent parameter. A combination of condition rating (CR) and time-dependent load employed to attain accurate insights about the degradation of structural resistance of the existing bridges. The result shows the significant impact of aging as well as traffic loads influence in the service life of both national highways (NH) and rural road service bridges. These observations might be used to adopt appropriate planning strategies as well as rational decisions to ensure the safety of the bridges for future operation.

Bridge maintenance management based on routine inspection data: a quantitative approach

The United States National Bridge Inventory (NBI) records element-level condition ratings on a scale of 0 to 9, representing failed to excellent conditions. Current bridge management systems apply Markov decision processes to find optimal repair schemes given the condition ratings. The deterioration models used in these approaches fail to consider the effect of structural age. In this study, a condition-based bridge maintenance framework is proposed where the state of a bridge component is defined using a three-dimensional random variable that depicts the working age, condition rating, and initial age. The proportional hazard model with a Weibull baseline hazard function translates the three-dimensional random variable into a single hazard indicator for decision-making. To demonstrate the proposed method, concrete bridge decks were taken as the element of interest. Two optimal hazard criteria help select the repair scheme (essential repair, general repair, or no action) that leads to minimum annual expected life-cycle costs.

Data-driven estimation of deterioration curves: a railway supporting structures case study

A significant portion of railway network income is spent on the maintenance and restoration of the railway infrastructure to ensure that the networks continue to provide the expected level of service. The execution of the interventions – that is, when and where to perform maintenance or restoration activities, depends on how the state of the infrastructure assets changes over time. Such information helps ensure that appropriate interventions are selected to reduce the deterioration speed and to maximise the effect of the expenditure on monitoring, maintenance, repair and renewal of the assets. Presently, there is an explosion of effort in the investigation and use of data-driven methods to estimate deterioration curves. However, real-world time history data normally includes measurement of errors and discrepancies that should not be neglected. These errors include missing information, discrepancies in input data and changes in the condition rating scheme. This paper provides solutions for addressing these issues using machine learning algorithms, estimates the deterioration curves for railway supporting structures using Markov models and discusses the results.

CONDITIONAL ASSESSMENT SYSTEM FOR REINFORCED CONCRETE MARINE STRUCTURES – A CASE STUDY

Current study mainly focusses on the development of a conditional assessment system for reinforced concrete structures present in marine environment demonstrating with a case study of cargo berths (CB) at Deendayal Port Trust, Kandla, Gujarat, India. The maximum tidal range at the study area is nearly 8m, making the field non-destructive tests (NDT) challenging. The proposed assessment system is based on the damage level classification (DLC) of structure, evaluated by a set of widely used NDTs. The study further investigates the usage of DLC system in comparison with the Condition Rating (CR) method developed by Verma et al. NDTs were conducted at 182 locations between CB 7-10 and observed that the condition of the marine structure, indicated by CR system and DLC system is similar irrespective of their different test approaches. The proposed DLC assessment system is reliable, quick, efficient and requires relatively lesser efforts compared to the CR system.

Development of smartphone-based semi-prepared runway operations (SPRO) models and methods

The U.S. Army Engineer Research and Development Center (ERDC) has developed a method for predicting surface friction response by use of ground vehicles equipped with deceleration-based measurement devices. Specifically, the ERDC has developed models and measurement methods between the Findlay Irvine Mk2 GripTester and a variety of deceleration measurement devices: Bowmonk AFM2 Mk3, Xsens MTi-G-710, two Android smartphones, and two iOS smartphones. These models show positive correlation between ground vehicle deceleration and fixed-slip surface continuous surface friction measurement. This effort extends prior work conducted by the U.S. Army ERDC in developing highly correlative models between the Findlay Irvine Mk2 GripTester and actual C-17 braking deceleration, measured via the runway condition rating (RCR) system. The models and measurement methods detailed here are of considerable use to semi-prepared airfield managers around the world needing to measure safe landing conditions following inclement weather. This work provides the tools necessary for airfield managers to quantify safe landing conditions for C-17 aircraft by using easily obtainable equipment and simple test standards.

Evaluation of Illinois Bridge Deterioration Models

The National Bridge Inventory bridge inspection system ranks the condition of bridge components on a scale of zero to nine. The resulting condition ratings represent an important element considered in deciding measures for bridge maintenance, repair, and rehabilitation. Thus, forecasting future condition ratings well is critical to reliable planning for these activities and estimating the costs. The Illinois Department of Transportation currently has deterministic models for this purpose. This study’s objective is to review the current models using condition rating histories gathered from 1980 to 2020 in Illinois for the following bridge components: deck, superstructure, substructure, culvert, and deck beam. The results show the current Illinois Department of Transportation models are inadequate in forecasting condition ratings, producing overestimates of the transition times between two condition rating levels for these components / systems, except for the deck beam, which is underestimated. It is recommended that the mean transition times found in this study from condition rating histories are used to replace the current models as a short-term solution. Further research is recommended to develop probabilistic models as a long-term solution to address observed significant variation or uncertainty in condition rating and transition times between condition rating levels.