Amlan Mukherjee

Calculation of Greenhouse Gas Emissions for Highway Construction Operations by Using a Hybrid Life-Cycle Assessment Approach: Case Study for Pavement Operations

Large quantities of greenhouse gases (GHG) are emitted in producing and acquiring materials for the construction, maintenance, and rehabilitation of highway infrastructure. The objective of this paper is to develop and illustrate a method that can be applied by state agencies to quantify the life-cycle emissions associated with different pavement designs. It applies existing life-cycle assessment (LCA) methods that integrate process-level construction data. The research emphasizes the construction phase and contributes a method that can be used to develop and analyze construction phase life-cycle inventories. It describes on-site collection of material and equipment usage data during construction and rehabilitation operations. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs on the basis of estimated inventories, this paper proposes a shift to a context-sensitive process-based approach that uses actual observed construction data to ca...

Modeling Blockage Failures in Sewer Systems to Support Maintenance Decision Making

The objective of this research is to develop and implement a stochastic method that can be applied to characterize random failures in critical infrastructure systems. We particularly focus on blockage failures in sewer systems that are nonmechanistic and result from combination of external factors, including deterioration in condition. The method was implemented using a data set consisting of sewer blockage failure records from a small municipality. Statistical tests were conducted to: (1) ensure that available data set is representative and (2) estimate parameters of distributions that appropriately characterize failure event arrival pattern. Failure trends were also analyzed to identify the influence of local factors and justify the choice of the distributions used to characterize interarrival times. Based on the analysis, we explored the challenges in developing a reliability model across the life cycle of a sewer system. In addition, specific examples were also presented to illustrate how the method can be applied to support system maintenance decisions. The results of this study illustrate how the memoryless property can be assumed in analyzing failure events, while explicitly considering context specific influences. Finally, the methods described in this paper are extensible and can be applied generally to analyzing random failures in other infrastructure systems as well.

Project Emissions Estimator: Implementation of a Project-Based Framework for Monitoring the Greenhouse Gas Emissions of Pavement

Because of the need to address challenges of global climate change, a project-based framework was developed and implemented for life-cycle assessment (LCA) that could be used to estimate the carbon footprint for typical construction work items in highway reconstruction and rehabilitation projects. The proposed framework considers the life-cycle emissions of products and processes involved in the raw material acquisition and manufacturing phase as well as the pavement construction phase. The framework also accounts for emissions from vehicular use and maintenance operations during the service life of the pavement. The framework introduces methods based on LCA to develop inventories of project emissions for highway construction, rehabilitation, and maintenance projects as well as to analyze inventories for the calculation of project-level construction metrics for estimating emissions. Fourteen highway construction and rehabilitation projects in Michigan were used to implement the method and validate the approach. In addition, the project emissions estimator (PE-2), a web-based tool that can be used to estimate and benchmark the carbon dioxide footprint of highway construction projects, is introduced. Results further the understanding of LCA methods for pavements while providing an emission estimation tool that can be used by decision makers to monitor and assess project emissions.

Developing Construction Management Events in Situational Simulations

Abstract: The challenge and promise of educational computer simulations are to provide user experiences that allow for immersion into a dynamic system in which participants discover the ramifications of their decisions in a complex environment. Researchers at the University of Washington, in collaboration with Michigan Technological University, are developing situational simulations to meet the needs of construction management education. This article explores the development of simulation events where simulation variables are changed due to an event, and then the player is challenged to interact with the simulation by making decisions that impact the project outcome. A simulation event includes the players experience, variables altered by the event, and variables changed by the player. This article defines the concept of simulation events within the context of situational simulations; explains how events are triggered, represented, and handled within the simulation and database; describes how players engage with the simulation; and identifies the challenges of incorporating the social dynamics of project management into the simulation environment.

An integrated assessment of continuously reinforced and jointed plane concrete pavements

Purpose – This paper aims to provide an integrated framework of life cycle assessment (LCA) and life cycle cost analysis (LCCA) for assessing alternative technologies, processes, and/or activities, with focus on concrete pavements.Design/methodology/approach – LCA and LCCA are used to evaluate environmental and economic impacts of substituting different percentages of fly ash and slag into continuously reinforced concrete pavement (CRCP) and jointed plane concrete pavement (JPCP). Impacts are determined over different life cycle phases.Findings – An LCA of the extraction phase indicated that JPCP pavement had 33‐62 percent less emissions than CRCP pavements, when only steel consumption was considered. When cement was considered, JPCP pavement had almost 40 percent greater emissions then CRCP for all mix types. An LCCA showed that over the entire life cycle phases studied, CRCP pavements had about 46 percent more costs than JPCP. However, when only maintenance costs were considered, CRCP pavement cost 80 p...

Using situational simulations to support decision making in co-dependent infrastructure systems

In this paper we introduced an integrative network-based approach to modelling co-dependent infrastructure systems and simulating them within the general purpose framework of situational simulations. We introduced and discussed the underlying mathematical model of the simulation, and also discussed typical information that will drive it – specifically considering the case of the City of Houghton, Michigan, in the USA. We also implemented the situational simulation using a proposed process model and the information model, thus providing a prototypical product interface. The simulation is interactive and it allows decision makers to account for complex adaptive interactions among co-dependent infrastructure systems, and to account for non-linear feedbacks and counter-intuitive behaviour. The significance of this research is twofold: 1. It provides an underlying model to represent and reason about co-dependent infrastructure systems. 2. It implements the model within the general purpose framework of situational simulations that can be used by public infrastructure emergency management agencies to test crisis management strategies, assess risk, and specifically identify and prepare for events that expose system vulnerabilities. This paper seeds an agenda for interdisciplinary future research with the ultimate goal of developing products that enhance decision making in managing co-dependent infrastructure systems.

Project Emission Estimator: Tool for Contractors and Agencies for Assessing Greenhouse Gas Emissions of Highway Construction Projects

Motivated by the need to address the challenges of global climate change, this paper develops and implements a project-based life-cycle framework that can be used to estimate the carbon footprint for typical construction work items found in reconstruction, rehabilitation, and capital preventive maintenance projects. Through applying existing life-cycle assessment methods and inventories, the proposed framework considers the life-cycle emissions of products and processes involved in the raw material acquisition and manufacturing phase and in the pavement construction phase. The framework also estimates emissions from vehicular use and maintenance operations during the service life of the pavement. The Project Emission Estimator (PE-2), a web-based tool that implements the project-based life-cycle framework, can be used to benchmark the carbon dioxide (CO2) footprint of highway construction projects. This paper suggests ways contractors and state transportation agencies can implement the PE-2 to benchmark and help reduce the CO2 footprints of highway construction projects.

Using situational simulations to collect and analyze dynamic construction management decision-making data

In this paper we lay the foundations for studying decision-making in complex dynamic construction management scenarios using situational simulations as experimental testbeds. We draw on research conducted in dynamic decision making, construction data-mining and situational simulations to develop methods to study human decision-making data collected in ICDMA - a situational simulation of a real four story steel frame office building construction project. Specifically, we address challenges in the collection, organization and analysis of human subject data. We define a discipline driving the collection of human decision-making data, establish a semantics to organize the data and a simple mathematical syntax to represent it. We also present an analysis of preliminary experimental work and show that our method can be used to analyze patterns in complex construction decision-making. Finally, we present an agenda of research in construction decision-making using situational simulations that can be conducted using our proposed methods.

Implementing a general purpose framework using multi-agents for construction management education

The need for contextually rich educational experiences in construction education has led researchers to explore alternatives using gaming and simulation environments. The work done so far has concentrated on special and general purpose simulations of construction operations with limited interactivity. We claim that it is necessary to have an extensible general purpose framework, for developing a wide variety of situational simulations of construction management processes, that can be used to create interactive environments for training managers. We have introduced such a framework and developed it using multiple autonomous agents. The Virtual Coach is an implementation of the developed framework. It was tested on a class of 19 construction management senior students, and proved to be a useful educational tool.

Markov chain applications in modelling facility condition deterioration

Condition states of civil infrastructure such as pavements and bridges are usually indexed on discrete scales. Historical condition data is modelled using Markov chain to estimate transition probabilities from one condition state to another, the rate of change and the time spent in any given state. The usefulness of such models is a function of the completeness of the available records and underlying assumptions of homogeneity. However, complete sets of condition data are not always easily available. In addition, the transition probabilities between states are assumed to be homogeneous, even though they tend not to be. Therefore, the objective of this study is two-fold: First, to maximise the usage of limited available data in estimating transition probabilities between condition states; and second to assess the sensitivity of model predictions to variations in transition probabilities between condition states. The paper presents a novel method to estimate transition probabilities based on the simulation of long term behaviour of a Markov chain model. Next, building on existing research, a Monte Carlo simulation of a non-homogeneous Markov chain model is used to explicitly consider heterogeneity in transition probabilities.