Changbum R. Ahn

Sustainability analysis of earthmoving operations

Emissions from construction equipment are the main contributor of environmental impacts from construction processes, and mitigating these impacts is an important aspect of operations design and planning. To this end, emission estimation models play an important role in environmental management of construction operations. This paper presents an emission model that integrates with discrete-event simulation (DES) for more accurate emission estimates from construction operations compared to existing models. The paper also presents a case study which analyzes sustainability of an earthmoving operation, to demonstrate the application of DES for estimating emissions.

Importance of Operational Efficiency to Achieve Energy Efficiency and Exhaust Emission Reduction of Construction Operations

Construction operations generate significant air pollutant emissions, including carbon emissions and diesel exhaust emissions. Controlling operational efficiency is the most important strategy for reducing air pollutants emitted from construction operations. However, current practices to assess air pollutant emissions from construction operations tend to ignore the variability of the operational efficiency that results from different resource allotting and scheduling. In this context, this paper presents a methodology for incorporating the analysis of operational efficiency into quantifying the amount of exhaust emission from construction operations. Case studies are presented to examine how and to what extent planning decisions affect the amount of air pollutants emitted from construction operations and to identify the impact that possible alternatives have on the schedule and cost of projects. The findings of case studies indicate that considering environmental aspects in the planning stage could contribute to a project’s increased integrated value, which includes schedule, cost, and environmental impact.

Comprehensive Fall-Risk Assessment of Construction Workers Using Inertial Measurement Units: Validation of the Gait-Stability Metric to Assess the Fall Risk of Iron Workers

AbstractIn construction worksites, slips, trips, and falls are major causes of fatal injuries. This fact demonstrates the need for a safety assessment method that provides a comprehensive fall-risk analysis inclusive of the effects of physiological characteristics of construction workers. In this context, this research tests the usefulness of the maximum Lyapunov exponents (Max LE) as a metric to assess construction workers’ comprehensive fall risk. Max LE, one of the gait-stability metrics established in clinical settings, estimates how the stability of a construction worker reacts to very small disruptions. In order to validate the use of Max LE, a laboratory experiment that asked a group of subjects to simulate iron workers’ walking tasks on an I-beam was designed and conducted. These tasks were designed to showcase various fall-risk profiles: walking with a comfortable walking speed presented a low fall-risk profile; carrying a one-sided load and walking at a faster speed on the I-beam both presented ...

Application of low-cost accelerometers for measuring the operational efficiency of a construction equipment fleet

AbstractMonitoring the operational efficiency of construction equipment offers great opportunities to enhance not only the productivity but also the environmental performance of construction operations. However, existing enabling technologies still suffer from a lack of economic feasibility, as well as technological compatibility with equipment fleets that are outdated or that consist of diverse manufacturers’ models. In this context, this paper examines the feasibility of measuring the operational efficiency of equipment using low-cost accelerometers. Acceleration data in three axes were collected from a real-world operation of excavators that performed various duty cycles. Multiple features were calculated from acceleration data, and several classifiers using these features were tested to classify equipment operation into engine-off, idling, and working modes. An accuracy of over 93% was obtained in the classification of excavators’ operation. This result has demonstrated that the application of low-cos...

The validation of gait-stability metrics to assess construction workers' fall risk

Falling from height is the top cause of injuries and fatalities in the construction industry. Understanding the fall risk at different work environments can help to prevent fall accidents on a jobsite. While many previous studies attempted to assess the fall risk on a construction site, most of them are qualitative or subject to cognitive biases. In this context, this paper aims to introduce and validate a quantitative measure that allows researchers to characterize the fall risks of construction workers. In particular, this paper focuses on validating the fall risk predictive power of Maximum Lyapunov exponent (Max LE), which is one of the gait-stability metrics established in clinical settings. The kinematic data were collected using an inertial measurement unit (IMU) sensor attached to the right ankle of the subject performing different tasks. The Max LE for each tasks were then calculated based upon the IMU measurements. The results indicated a significant difference in the Max LE between different tasks, which indicates that Max LE has the potential to evaluate the dynamic stability of construction workers.

Detecting the Hazards of Lifting and Carrying in Construction through a Coupled 3D Sensing and IMUs Sensing System

Construction companies in Hong Kong suffer huge losses due to labor fatalities and injuries. More than 25% of all of the injuries and fatalities in all industries in Hong Kong are caused by the construction industry. Different from the U.S., whose top injury cause is fall to lower level for fatal injuries (34%) and nonfatal injuries (23%); the most frequent type of injuries in Hong Kong is lifting and carrying (19.2%). Recently, automated 3D sensing systems (Kinect) have been employed to identify motion related hazards to improve construction safety condition. However, limitations (such as extreme light conditions, occlusions and misrepresentations) of 3D sensing systems hinder its application in engineering practices. To resolve those limitations, this research proposed a coupled system, which integrates and synchronizes the Kinect with Inertial Measurement Unit (IMUs). With the help of the coupled system, IMUs could uninterruptedly collect motion data (accelerations and angular rates) even under extreme light conditions or under occlusions; while Kinect could provide a reference system for IMUs to construct postures. The whole sensor network will be able to capture complete and reliable data, even if Kinect fail to work properly. Moreover, the proposed coupled system will also promote other human related research, such as productivities and labor tracking.

Lessons learned from utilizing discrete-event simulation modeling for quantifying construction emissions in pre-planning phase

Construction operations have a tremendous impact upon both the environment and public health due to the generation of significant amounts of airborne emissions, including greenhouse gases and other traditional criteria air pollutants. Quantifying emissions in the pre-planning phase of construction operations is the first step in identifying mitigation opportunities. The authors therefore have quantified construction emissions produced by various types of construction operations through the use of discrete-event simulation (DES). The paper focuses upon the utilization of DES in various case studies and delineates the lessons learned. An overview of each case project is provided, the benefits and limitations of DES are identified, and means to mitigate these limitations are discussed. The lessons learned from the case studies utilized in the paper are helpful; simulation practitioners and researchers can exploit these studies in simulation models that examine the environmental aspects of construction operations.

Identifying Safety Hazards Using Collective Bodily Responses of Workers

AbstractCurrent construction hazard identification mostly relies on safety managers’ ability to identify hazards using their prior knowledge about them. Consequently, numerous latent hazards remain unidentified, which poses significant risks to construction workers. To advance current hazard identification capabilities, this study examines the feasibility of harnessing and analyzing collective patterns of workers’ bodily responses (balance, gait, etc.) to identify safety hazards on a jobsite. To test the hypothesis that the abnormality of workers’ bodily responses in one location highly correlates with the likelihood of a safety hazard in that location, this project collected data on the bodily responses of 10 subjects who participated in five experiments. These test subjects wore inertial measurement unit (IMU) sensors on their body. Then the collected response data were analyzed using three metrics [average, standard deviation, and Shapiro-Wilk statistic (W)]. The data showed that the normality of worke...

Integrated Framework for Estimating, Benchmarking, and Monitoring Pollutant Emissions of Construction Operations

AbstractConstruction operations are highly energy-intensive and account for significant environmental impacts, including greenhouse gases (GHG) and other engine exhaust associated with material procurement/delivery and on-site construction activities. The opportunities for mitigating air pollutant emissions from construction operations can be captured by estimating and benchmarking during the preconstruction phase and then monitoring during the construction phase. However, a formal process model to manage the environmental aspects of on-site construction activities has yet to be clearly delineated, although recently several research efforts have appeared in relevant areas such as the development of in-use emission factors of construction equipment, methods for reliably estimating emissions at the project level, embodied carbon footprint benchmarking methods, and practical monitoring tools. Such a lack of a formal process model causes the misinterpretation of the benefits from recent research efforts in ea...

Automated Detection of Near-miss Fall Incidents in Iron Workers Using Inertial Measurement Units

1 Ph.D Student, Construction Engineering and Management, Charles Durham School of Architectural Engineering and Construction, University of NebraskaLincoln, W113 Nebraska Hall, Lincoln, NE 68588; PH (402) 472-5631; email: kyang11@unl.edu 2 M.S. Student, Computer Science and Engineering Department, College of Engineering, University of Nebraska-Lincoln, W113 Nebraska Hall, Lincoln, NE 68588; PH (402) 472-5631; email: saria@cse.unl.edu 3 Assistant Professor, Construction Engineering and Management, Charles Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, W113 Nebraska Hall, Lincoln, NE 68588; PH (402) 4727431; email: cahn2@unl.edu 4 Associate Professor, Environmental, Agricultural, Occupational Health Science, 984388 Nebraska Medical Center, Omaha, NE 68198-4388 and Construction Engineering and Management, Charles Durham School of Architectural Engineering and Construction, W113 Nebraska Hall, College of Engineering, University of Nebraska, Lincoln, NE 68588-0500; PH (402) 472-5078; email: tstentz1@unl.edu