An optimum strengthening strategy for corrosion-affected reinforced concrete structures

Corrosion of reinforcing steel in concrete is the most predominant cause for deterioration of reinforced concrete structures, leading to many premature structural failures. To ensure the safety and serviceability of deteriorated structures, a risk-informed and cost-effective rehabilitation strategy is essential. The intention of the present paper is to develop an optimal strengthening strategy for corrosion-affected reinforced concrete structures strengthened with a widely used fiber-reinforced polymer (FRP) technique. In this strategy, the optimum strengthening time and the degree of strengthening-that is, the number of FRP layers-can be determined. Mathematical formulation of the proposed strategy, which is based on cost optimization, is provided in a generic format. Application of the proposed methodology is presented in a numerical example for a corrosion-affected reinforced concrete girder flexurally strengthened with FRP. The Genetic Algorithm (GA) method is used for finding the optimum solution. It is found in the paper that the proposed strategy can determine the optimum strengthening time and amount of FRP strengthening efficiently. It is also found that the ratio of cost of failure to cost of preventive maintenance governs the optimum time for maintenance action. The paper concludes that the developed strategy can assist structural engineers and asset managers in developing rehabilitation or replacement strategy for deteriorated infrastructure. © 2017, American Concrete

Time-dependent reliability method for service life prediction of reinforced concrete shield metro tunnels

Ageing and deterioration of underground tunnels is inevitable after their long-time in service. This necessitates a rigorous assessment of the probability of failure due to deterioration with a view to predicting remaining safe life. In the light of considerable research undertaken on prediction of service life of the aboveground structures, e.g. bridges, few such studies dealing with the underground structures, e.g. tunnels, have been carried out. The intention of this paper is to present a time-dependent reliability method to assess the tunnel probability failure due to different mechanisms of deterioration. Stochastic models are developed for four common failure modes of tunnel structures as identified by strength and serviceability criteria. Application of the proposed methodology is demonstrated in a case study. It is found in the paper that the reinforcement corrosion is a key factor that affects the probability of deterioration failure and that all deterioration scenarios need to be considered in the assessment of tunnel failures and prediction of their remaining safe life. The proposed method can help the asset managers and practitioners in developing rehabilitation or replacement strategy for existing tunnels with a view for better management of the valuable tunnel asset. © 2017 Informa UK Limited, trading as Taylor & Francis Group

Optimizing Federated Learning With Deep Reinforcement Learning for Digital Twin Empowered Industrial IoT

The accelerated development of the Industrial Internet of Things (IIoT) is catalyzing the digitalization of industrial production to achieve Industry 4.0. In this article, we propose a novel digital twin (DT) empowered IIoT (DTEI) architecture, in which DTs capture the properties of industrial devices for real-time processing and intelligent decision making. To alleviate data transmission burden and privacy leakage, we aim to optimize federated learning (FL) to construct the DTEI model. Specifically, to cope with the heterogeneity of IIoT devices, we develop the DTEI-assisted deep reinforcement learning method for the selection process of IIoT devices in FL, especially for selecting IIoT devices with high utility values. Furthermore, we propose an asynchronous FL scheme to address the discrete effects caused by heterogeneous IIoT devices. Experimental results show that our proposed scheme features faster convergence and higher training accuracy compared to the benchmark

Optimal inspection plan for deteriorating structural members using stochastic models with application to buried pipelines

The deterioration of structural systems is unavoidable after their long time in service. To ensure the safety of these systems, an effective inspection strategy with a minimal cost is essential. This paper presents an analytical approach for determining the optimal inspection plan using a cost-based criterion in which structural damage and failure are modeled as stochastic processes. This allows the consideration of the correlation of damages at different times in the reliability-based inspection plan. An example is provided to illustrate the application of the proposed methodology, taking the number of inspection actions and the critical damage level at which repair is performed as the optimization variables. The proposed procedure provides a fast solution for the optimization of an inspection plan with superior performance over those based on simulation. In addition, correlation has a big impact on the result of an optimal inspection plan matching that of the cost of failure. © 2019 American Society of Civil Engineers

Design for service life of underground space based on water seepage criterion

Ever increased urbanisation in the world has made the underground space a viable alternative to the expanding city space. Underground space usually operates under the water level whereby the water ingress is one of the most detrimental factors affecting its service life and sustainability. But little or no research has been conducted on design for service life of underground space based on the criterion of water seepage. This paper proposes a rational and practical methodology for design of service life of underground space as represented by its lining structures against water seepage. A stochastic model of water seepage depth in concrete lining is developed. The proposed methodology is verified with numerical method for prediction of the probability of failure due to water seepage. The merit of the proposed methodology is that it allows for the randomness and time variation of design variables and also directly relates to the real time in service of underground space. It is found in the paper that the correlation of water seepage depth between two points in time and the concrete constituent materials can significantly affect the probability of water seepage failure. The significance of the proposed methodology is that it can be used as a design guide for service life of underground space based on various design criteria. © 2019 Elsevier Lt

A theoretical framework for risk–cost-optimized maintenance strategy for structures

This paper presents a theoretical framework for developing a risk–cost optimised maintenance strategy for structures during their whole service life. A time-dependent reliability method is employed to determine the probability of structural failure and a generic form of stochastic model is developed for structural responses. To facilitate practical application of the proposed framework, a general algorithm is developed and programmed in a user-friendly manner. The merit of the proposed framework is that, in predicting when, where and what maintenance is required for the structure, all structural components and multi-failure modes are considered. It is found in the paper that, to ensure the safe and serviceable operation of the structure as a whole, some components need maintenance multiple times for different failure modes, whilst other components need “do nothing”. It is also found that ignorance of correlation amongst structural components and failure modes would underestimate the risk of structural failures in longer term and that the components with higher cost of structural failures require more maintenance actions. The paper concludes that the proposed framework can equip structural engineers, operators and asset managers with a tool for developing a risk–cost optimal maintenance strategy for structures under their management. © 2019, Iran University of Science and Technology

Optimal FRP-strengthening strategy for corrosion-affected reinforced concrete columns

Deterioration of reinforced concrete (RC) structures is unavoidable after their long time in service, with corrosion being the major mechanism of deterioration. In order to ensure safety of deteriorated structures, an effective rehabilitation plan is essential. Although considerable research on strengthening of RC structures using fibre-reinforced polymers (FRPs) composites has been undertaken, more is on the methods of strengthening and effects of corrosion on strength of RC columns than that on the prediction of optimum strengthening time. This paper presents a methodology for determining the optimal strengthening time and the required number of FRP layers for corrosion-affected RC structures with application to columns. The methodology is based on the time-dependent reliability method and the renewal theory. An example is provided to illustrate the application of the proposed methodology. It is found in this study that an optimum point for the formulated objective function exists, and that outcomes of optimisation problem, i.e. strengthening time and number of required FRP layers, are sensitive to corrosion rate. The significance of the proposed methodology is that it provides guidance for practitioners and asset managers to decide when and how to strengthen deteriorated structural members. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group

Analytical models for effective hydraulic sorptivity, diffusivity and conductivity of concrete with interfacial transition zone

This paper presents analytical models for evaluating effective hydraulic conductivity, diffusivity and sorptivity of concrete considering the properties of the Interfacial Transition Zone (ITZ) and the aggregate size distribution. Results of the proposed models compare well with the experimental results and those obtained from rigorous numerical Finite Element (FE) analysis. It is also found that a change of Interfacial Transition Zone (ITZ) properties has more influence on the effective hydraulic conductivity than it has on the effective hydraulic sorptivity. The significance of the proposed models is that they can estimate the hydraulic sorptivity and diffusivity of concrete by only knowing the hydraulic properties of mortar, effectively extricating the need for sophisticated and time-consuming FE analysis required for estimation of the effective hydraulic conductivity of concrete at the meso-scale. Furthermore, these models offer scientific insight into the effect of different components of concrete on its effective hydraulic properties. © 201

An optimum strategy for FRP-strengthening of corrosion-affected reinforced concrete columns

In order to ensure safety of deteriorated reinforced concrete (RC) structures, an effective rehabilitation plan is essential. Although considerable research on strengthening of RC structures using Fiber Reinforced Polymers (FRP) composites has been undertaken, prediction of optimum strengthening time has not adequately been studied. This paper presents a methodology for optimal strengthening of corrosion-affected RC columns. An optimization problem based on minimization of total cost is formulated, from which optimum strengthening time and number of required FRP layers can be obtained. The results from a worked example show that an optimum solution to the formulated strengthening problem exists, and it is sensitive to the corrosion rate and cost of failure to cost of strengthening ratio. The proposed approach is useful in the development of an effective strengthening schedule for existing corrosion-affected RC columns, and could benefit the asset managers and structural practitioner. © 2019 Taylor & Francis Group, London

Risk-cost optimised maintenance strategy for tunnel structures

Due to limited maintenance budget, effectively spending the available funds for maintaining infrastructures is increasingly sought by asset managers. Tunnel is an essential infrastructure that plays a pivotal role in transportation network, economy, prosperity, social well-being, quality of life and the health of its population. In the light of considerable research that has been or is being undertaken on "aboveground" infrastructure, e.g. bridges, this threat cannot be more apparent for underground infrastructure such as tunnels. The situation has been exaccrbatcd due to more unknowns and uncertainties relating to the factors such as underground water and soil/rock that affect the operation of tunnel infrastructure. In an ageing tunnel system, various potential deficiencies such as seepage, spalling, crack, delamination, steel corrosion, drainage, convergence and settlement of the lining structure can cause catastrophic life safety and economic consequences. Most collapses of tunnel structures in the world are related to tunnel deterioration with catastrophic consequences. Through an effective maintenance plan, the catastrophic failures of tunnels can be prevented. This research aims to develop a maintenance strategy for concrete tunnels which determines when (maintenance intervention times), where (segments of tunnel network) and what (failure mode of tunnel structure) maintenance actions need to be taken to ensure the safe and serviceable operation of tunnel with the intention to minimise the risk. The mathematical formulation of the proposed maintenance strategy, which is based on risk optimisation, is provided in a generic format. Application of the proposal to tunnel structures is presented in a numerical example. © The authors and ICE Publishing: All rights reserved, 2016