Civil Infrastructure Facilities Research Articles

Impact of ground surface subsidence caused by underground coal mining on natural gas pipeline

Underground mining of minerals is accompanied by a change in the rock mass geomechanical situation. This leads to the redistribution of stresses in it and the occurrence of unexpected displacements and deformations of the earth's surface. A significant part of the civil and industrial infrastructure facilities are located within the mine sites, where mining and tunneling operations are constantly conducted. Irrational planning of mining operations can lead to loss of stability and destruction of undermined facilities. Therefore, it is important to study the earth’s surface deformation processes during mining operations, which ensures safe and sustainable operating conditions. The research objective of this paper is to analyse the behaviour of a natural gas pipeline under the influence of underground mining activities, with a particular focus on understanding the effects of horizontal surface deformations and their potential impact on pipeline safety and structural integrity. Its performance and safety are determined on the basis of the found parameters of the earth's surface horizontal deformations and their comparison with permissible parameters characterizing the conditions for laying pipelines, depending on the mining-geological conditions and the degree of their undermining. Based on determined conditions for the safe undermining of the natural gas pipeline, it has been revealed that in its section between the PK212+40 and PK213+80 (140 m) pickets, the estimated parameters of the earth's surface horizontal deformations exceed their permissible values. This can cause deformation and damage to the pipeline. For the safe operation of the pipeline during the period of its undermining, in order to eliminate the hazardous impact of mining the longwall face, additional protection measures must be applied. It is therefore recommended that the gas pipeline between the PK212 and PK214+20 pickets be opened prior to the displacement process (200 m from the stoping face), thus reducing the density of the gas pipeline-soil system. Recommendations for controlling the earth’s surface deformations within the natural gas pipeline route are also proposed, which will ensure premature detection of the negative impact of mining operations.

An Insight into the Characteristics of the September 24, 2019, MW 5.8 Mirpur, Pakistan, Earthquake and Reconnaissance of the Induced-Failure Modes in Buildings and Civil Infrastructure Facilities

An Insight into the Characteristics of the September 24, 2019, MW 5.8 Mirpur, Pakistan, Earthquake and Reconnaissance of the Induced-Failure Modes in Buildings and Civil Infrastructure Facilities

ASSESSING THE PERFORMANCE OF UNITS FOR THE SYNTHESIS OF OLIGODYNAMIC SOLUTIONS FOR WATER TREATMENT

Introduction: Fresh water suitable for water supply has been depleted due to production activities. Thus, closed water supply cycles are required at civil infrastructure facilities. The quality of water must meet the requirements on its use for various purposes. It is common knowledge that water is essential in providing adequate health and sanitary conditions for the public. Therefore, issues of water treatment remain in the focus of researchers. Water disinfection is one of the mandatory methods used in water purification and treatment. Currently, chlorination is still the main technology for water disinfection. However, it is responsible for toxic, carcinogenic, and other types of negative effects on the human body. In this paper, we consider the use of oligodynamic solutions as a new, rapidly-developing direction in water treatment. In the course of our study, we addressed a method of swimming pool water disinfection using units of oligodynamic synthesis and examined the results of treated water quality analyses. Methods: The study was based on the statistical analysis of water quality indicators in pools with water treated with silver and copper ions. The analysis made it possible to determine the hygienic safety and reliability of products. To assess hygienic safety and reliability, we analyzed the composition and properties of the product (oligodynamic solution) as well as the composition and concentration of impurities in pool water and determined if the disinfecting properties of water are preserved and proper levels of copper and silver ions (not exceeding MAC) in pool water are maintained. Results: The paper provides a rationale for procedures to analyze and determine the safety and reliability of small-scale units producing disinfection solutions to ensure optimal swimming conditions in swimming pools. Discussion: The obtained results indicate that it is expedient to apply oligodynamic water treatment to ensure the hygienic safety and reliability of swimming pools. The technology suggested fully meets the requirements of sanitary regulations on water quality.

Maximum entropy method for flood frequency analysis: A case study of the Grand River in Ontario, Canada

Flood frequency analysis provides the fundamental information for the design of hydraulic and civil infrastructure facilities as well as water resources management. The available procedures to determine flood distributions and their parameters from historical data suffer from restriction on the family of presumed standard classical distributions, such as gamma distribution and extreme value distributions. This paper presents a distribution-free approach for flood frequency analysis by using the combination of maximum entropy method and Akaike’s information criterion. The determination procedure is given in a flowchart. It is distribution-free because no classical distributions were presumed in advance and the inference result gives a universal form of probability curves. Comparative studies from historical flood data show that the proposed method can, accurately and reasonably, characterize the probabilistic information of observed or transformed flood data.

The Effect of Shrinkage-Compensation on the Performance of Strain-Hardening Cement Composite (SHCC)

This study investigated the effects of shrinkage compensation on the tensile and cracking responses of strain-hardening cement composite (SHCC) by adding calcium sulfoaluminate (CSA)-based expansive additive (EXA) to the mixture. Such responses are closely related to the durability of concrete structures, of dumbbell-shaped SHCC specimens, and reinforced SHCC ties. For this study, two SHCC mixtures and a conventional concrete mixture with a specific compressive strength value of 30 MPa were prepared and measured in terms of shrinkage history, compressive strength, flexural strength, and direct tensile strength. The test results show that the mechanical properties of shrinkage-compensated SHCC with 10% CSA-based EXA are superior to those of conventional SHCC and concrete mixtures. Also, reinforced tension ties with shrinkage-compensated SHCC exhibited the best multiple cracking and tension-stiffening behavior among the three types of tension ties tested. The results show that shrinkage compensation using CSA-based EXA in SHCC with rich mixture is effective for resisting crack damage. Shrinkage-compensated SHCC may be used for civil infrastructure facilities that require high levels of durability and are exposed to extreme environments.

Modeling the damage and recovery of interdependent critical infrastructure systems from natural hazards

Understanding the impact of disasters to civil infrastructure network will guide strategic pre-disaster hazard mitigation and post-disaster recovery planning of a community. The facilities in civil infrastructure network depend on each other to exchange product, information or services. When disaster happens, these dependencies would aggravate the initial damage and lead to cascading failures. Thus, understanding the dependencies among infrastructure facilities is essential in modeling the damage and recovery of a community under disruptive events. This study builds upon the Dynamic Inoperability Input–output Model to assess the recovery of the civil infrastructure facilities by considering the facility-level dependencies. The recovery of the integrated network was assessed utilizing the characteristic parameters from graph theory. This methodology was demonstrated with a hypothetical infrastructure network, consisting of power, water and telecommunication systems under a hurricane. The sensitivity of the network recovery to the dependency measures was investigated, which showed that the recovery time is sensitive to the level of dependency between different systems. The proposed methodology was compared with a conventional model with system-level interdependencies and showed that considering facility-level dependencies would yield more refined result. The model was then applied to simulate the power system restoration of Galveston City, Texas under Hurricane Ike.

Modeling the damage and recovery of interdependent civil infrastructure network using Dynamic Integrated Network model

In a modern society, civil infrastructure facilities in different systems depend upon each other for product input and/or information sharing. Thus, understanding such dependencies and properly modeling them is essential to assess the performance of the civil infrastructure systems during and following a disruptive event, which lays the foundation of assessing the community resilience. This paper introduces the Dynamic Integrated Network model which is developed to assess the damage and recovery of the network of all considered systems following a disaster by considering the facility-level dependencies. A hypothetical study region consisting of electric power, potable water and cellular systems under a scenario hurricane is used to demonstrate the proposed model. A comparative study is performed with the case when inter-system dependency is ignored. This study confirms the importance of incorporating the inter-system dependencies to improve the estimation on the recovery process.

Adaptive Decision Framework for Civil Infrastructure exposed to Evolving Risks

Abstract Adaptive decision-making (ADM) is a structured process of learning, improving understanding, and ultimately adapting management decisions in a systematic and efficient way, aimed at reducing uncertainties over the course of the management timeframe. This approach holds a great potential for dealing with the challenges faced by civil infrastructure facilities, especially those exposed to evolving risks caused by changes in environmental and urban settings, evolving expectations and preferences of the public, tightening budgets, and unpredictable political circumstances over their lifetime. This paper suggests ADM as a way of continuously reevaluating the risks and providing more adaptive and flexible management actions to enhance infrastructure resilience under dynamic changes and evolving conditions. The proposed ADM is illustrated with a benchmark problem based on a testbed residential community in Kathmandu, Nepal to explore the effect of incremental building expansion on the seismic risk to a community and examine the feasibility and effectiveness of ADM in improving resilience.

Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis

Frequency analysis of hydrometeorological and hydrological extremes is needed for the design of hydraulic and civil infrastructure facilities as well as water resources management. A multitude of distributions have been employed for frequency analysis of these extremes. However, no single distribution has been accepted as a global standard. Employing the entropy theory, this study derived five generalized distributions for frequency analysis that used different kinds of information encoded as constraints. These distributions were the generalized gamma (GG), the generalized beta distribution of the second kind (GB2), and the Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B) and Halphen type inverse B distribution (Hal-IB), among which the GG and GB2 distribution were previously derived by Papalexiou and Koutsoyiannis (2012) and the Halphen family was first derived using entropy theory in this paper. The entropy theory allowed to estimate parameters of the distributions in terms of the constraints used for their derivation. The distributions were tested using extreme daily and hourly rainfall data. Results show that the root mean square error (RMSE) values were very small, which indicated that the five generalized distributions fitted the extreme rainfall data well. Among them, according to the Akaike information criterion (AIC) values, generally the GB2 and Halphen family gave a better fit. Therefore, those general distributions are one of the best choices for frequency analysis. The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.

Generalized Beta Distribution of the Second Kind for Flood Frequency Analysis

Estimation of flood magnitude for a given recurrence interval T (T-year flood) at a specific location is needed for design of hydraulic and civil infrastructure facilities. A key step in the estimation or flood frequency analysis (FFA) is the selection of a suitable distribution. More than one distribution is often found to be adequate for FFA on a given watershed and choosing the best one is often less than objective. In this study, the generalized beta distribution of the second kind (GB2) was introduced for FFA. The principle of maximum entropy (POME) method was proposed to estimate the GB2 parameters. The performance of GB2 distribution was evaluated using flood data from gauging stations on the Colorado River, USA. Frequency estimates from the GB2 distribution were also compared with those of commonly used distributions. Also, the evolution of frequency distribution along the stream from upstream to downstream was investigated. It concludes that the GB2 is appealing for FFA, since it has four parameters and includes some well-known distributions. Results of case study demonstrate that the parameters estimated by POME method are found reasonable. According to the RMSD and AIC values, the performance of the GB2 distribution is better than that of the widely used distributions in hydrology. When using different distributions for FFA, significant different design flood values are obtained. For a given return period, the design flood value of the downstream gauging stations is larger than that of the upstream gauging station. In addition, there is an evolution of distribution. Along the Yampa River, the distribution for FFA changes from the four-parameter GB2 distribution to the three-parameter Burr XII distribution.

Reliability assessment of aging structures subjected to gradual and shock deteriorations

Civil structures and infrastructure facilities are susceptible to deterioration posed by the effects of natural hazards and aggressive environmental conditions. These factors may increase the risk of service interruption of infrastructures, and should be taken into account when assessing the structural reliability during an infrastructure's service life. Modeling the resistance deterioration process reasonably is the basis for structural reliability analysis. In this paper, a novel model is developed for describing the deterioration of aging structures. The deterioration is a combination of two stochastic processes: the gradual deterioration posed by environmental effects and the shock deterioration caused by severe load attacks. The dependency of the deterioration magnitude on the load intensity is considered. The Gaussian copula function is employed to help construct the joint distribution of correlated random variables. Semi-analytical methods are developed to assess the structural failure time and the number of significant load events (shocks) to failure. Illustrative examples are presented to demonstrate the applicability of the proposed model in structural reliability analysis. Parametric studies are performed to investigate the role of deterioration-load correlation in structural reliability.

A risk de-aggregation framework that relates community resilience goals to building performance objectivess

Resilience is often regarded as an attribute of communities rather than of individual buildings, bridges, and other civil infrastructure facilities. Previous research to support development of resilient infrastructure has considered, for the most part, actions and policies to achieve resilience objectives at the community level. While it is clear that a community cannot be resilient without resilient individual facilities, few attempts have been made to relate the performance criteria for individual facilities to community resilience goals in a quantitative manner. This paper presents a method for relating risk-informed performance criteria for individual buildings exposed to extreme hazards to broader community resilience objectives and illustrates the application of the method to two residential building inventories. The paper demonstrates the feasibility of de-aggregating community resilience goals to obtain design performance objectives for individual facilities and thereby relating community goals to requirements in codes and standards that govern design of buildings and other structures.

Analytical review and evaluation of civil information modeling

Abstract Building information modeling (BIM) has been widely adopted in the building industry. However, the use of BIM in civil infrastructure facilities, sometimes referred to as civil information modeling (CIM) has been slow in its application. Industry and academia are increasingly putting effort into CIM study and implementation, but so far there has been no comprehensive review of their effort in this regard. This paper presents a framework to evaluate the current practices of CIM adoption for various civil infrastructure facilities. In this study, civil infrastructure facilities were divided into nine categories for evaluation and the effort with regard to CIM adoption for each civil infrastructure category was evaluated in six aspects. Based on the evaluation and comparison results of 171 case studies and 62 academic papers on CIM, research gaps were identified and recommendations were made. For example, the findings show that data schema development for civil infrastructure facilities other than bridges, roads, and tunnels are lacking. The results and research gaps revealed by this study are useful for both researchers and practitioners.

Sensitivity of Flood-Depth Frequency to Watershed-Runoff Change and Sea-Level Rise Using a One-Dimensional Hydraulic Model

AbstractClimate change and sea-level rise are expected to alter the likelihood of extreme events, such as floods, within the design lifetime of infrastructure components. Critical civil infrastructure facilities, including wastewater treatment, transportation, and energy, need site-specific flood contingency plans that reflect the effects of changing climate. This study developed a sensitivity analysis method to assess future flood risk by estimating flood frequency under conditions of higher sea level and streamflow response to increased precipitation intensity. The method was applied to an ungauged location on a tidal estuary in the Mid-Atlantic region as a case study. One-dimensional (1D) unsteady flow analysis using a hydraulic analysis software developed by the U.S. Army Corps of Engineers was used to predict discharge and water surface elevation along the estuary reach, subject to prescribed boundary conditions of upstream discharge and downstream water surface elevation. A current-climate flood-dep...

Life cycle performance goals for civil infrastructure: intergenerational risk-informed decisions

Civil infrastructure facilities play a central role in the economic, social and political health of modern society. Such facilities are susceptible to ageing, which is stochastic in nature and makes their reliabilities time dependent. Life-cycle engineering analysis and risk-informed decision tools have advanced in recent years for managing public investments in performance assurance and risk mitigation of civil infrastructure. However, certain civil infrastructure projects may be designed for service periods that are substantially longer than what has been typically expected of buildings, bridges and similar facilities, extending the potential consequences of life-cycle engineering decisions far beyond the limits for which there is practical experience. Current assessment procedures will require modification to evaluate performance of civil infrastructure facilities over extended time frames and to support sustainable and equitable decisions affecting long-term public safety. This paper considers a number of key issues that must be addressed in life-cycle reliability assessment of civil infrastructure facilities that must remain functional for service periods of several generations, and introduces perspectives on risk that are germane to ensure sustainability and intergenerational equity in risk-informed decision-making.

The role of risk aversion in nuclear plant safety decisions

Risk to civil infrastructure facilities from extreme natural and manmade hazards is characterized by involuntary exposure and potentially severe consequences to the public. Individuals and the public tend to overstate involuntary risks that are poorly understood or involve the possibility of fatalities. Such exaggerations of risk perception influence policy-making and the development of appropriate strategies for mitigating and managing the risk. Regulatory decision-making for nuclear power plant safety represents a case that is affected by exaggerated risk perception caused by fear. The recent meltdowns at the Fukushima Daiichi Plant in Northeast Japan in March 2011 reinforced such fears and fueled opposition to the further development of nuclear power as a solution to the nation's growing energy demands. In this paper, we analyze the US Nuclear Regulatory Commission (NRC)'s regulations regarding to the operation of nuclear power plants utilizing a decision model known as cumulative prospect theory (CPT), which permits risk-averse behavior to be modeled in assessing both likelihoods and consequences of a hazardous event. The investigation is extended to different requirements that are influenced by the International Commission on Radiological Protection for an international perspective. Finally, we consider how risk attitudes can be incorporated in future decisions with an example of retrofitting Browns Ferry Nuclear Plant in accordance with the Severe Accident Mitigation Alternatives stipulated by the USNRC.

Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model

This paper considers a difficult but practical circumstance of civil infrastructure management—deterioration/failure data of the infrastructure system are absent while only condition-state data of its components are available. The goal is to develop a framework for estimating time-varying reliabilities of civil infrastructure facilities under such a circumstance. A novel method of analyzing time-varying condition-state data that only reports operational/non-operational status of the components is proposed to update the reliabilities of civil infrastructure facilities. The proposed method assumes that the degradation arrivals can be modeled as a Poisson process with unknown time-varying arrival rate and damage impact and that the target system can be represented as a fault-tree model. To accommodate large uncertainties, a Bayesian algorithm is proposed, and the reliability of the infrastructure system can be quickly updated based on the condition-state data. Use of the new method is demonstrated with a real-world example of hydraulic spillway gate system.

Structural reliability and performance-based engineering

Civil infrastructure facilities must be designed to withstand demands imposed by their service requirements and by natural environmental events. In the past four decades, structural reliability methods have matured to the point that they now provide the framework for addressing safety and serviceability issues in modern codified structural design, and most countries have adopted such methods for code development. While the normal design process usually results in a constructed facility with a degree of integrity that is also available to withstand challenges from unforeseen events, events outside the traditional design envelope may result in severe damage or economic losses and, in extreme instances, precipitate catastrophic collapse. In an era of heightened public awareness of infrastructure performance, performance-based engineering (PBE) offers a new paradigm that may allow structural engineers to meet these challenges and to better match building design with owner, occupant and social performance expectations. Successful implementation of PBE will require understanding and acceptance of the supporting quantitative structural reliability risk assessment methods and risk-informed decision tools summarised in this paper.

Sensitivity of uncertainties in performance prediction of deteriorating concrete structures

Deterioration models for the condition and reliability prediction of civil infrastructure facilities involve numerous assumptions and simplifications. Furthermore, input parameters of these models are fraught with uncertainties. A Bayesian methodology has been developed by the authors, which uses information obtained through health monitoring to improve the quality of prediction. The sensitivity of prior and posterior predicted performance to different input parameters of the deterioration models, and the effect of instrument and measurement uncertainty, is investigated in this paper. The results quantify the influence of these uncertainties and highlight the efficacy of the updating methodology based on integrating monitoring data. It has been found that the probabilistic posterior performance predictions are significantly less sensitive to most of the input uncertainties. Furthermore, updating the performance distribution based on ‘event’ outcomes is likely to be more beneficial than monitoring and updating of the input parameters on an individual basis.

Infrastructure Asset Management Education: Active Learning and Engagement-Based Practices

Asset management of civil infrastructure facilities and systems is gaining importance both in practice and in academia as the public demands increased accountability in government, laws are passed requiring infrastructure asset management, and growth and development accelerate the deterioration of already aged infrastructures. In response, more agencies continue to adopt and develop their asset management practices and more academic institutions and continuing education programs define courses and programs in civil infrastructure asset management. This paper focuses on an infrastructure management class offered at the graduate level mainly for civil engineering and transportation planning students. The outline of the class and a brief overview of active and engagement-based learning techniques are presented, and the way these techniques are integrated with the delivery of the asset management material is described.