Yongwei Shan

Investigating the Latent Factors of Quality of Work-Life Affecting Construction Craft Worker Job Satisfaction

AbstractPrevious research in other disciplines identified that job satisfaction plays a major role in employee performance and retention. This paper examines the relationship between job satisfacti...

Developing Predictive Models of Superstructure Ratings for Steel and Prestressed Concrete Bridges

A large number of deficient bridges may endanger the public and affect the economy at a broader scale. Bridge superstructure rating is a critical element that affects the overall sufficiency rating of a bridge. Accurately predicting the superstructure performance of a bridge may help agencies better prioritize their resources for maintenance and repairs. The main objective of the paper is to utilize data mining techniques to develop reliable models to predict the superstructure rating of bridges. This research utilizes the national bridge inventory (NBI) database as the main source of information. A focused subset was created based on the defined scope of the research: year built (≥ 1955), kind of material-design (prestressed concrete and steel), type of design (stringer/multi-beam or girder), and deck type (concrete cast-in-place). This paper takes three approaches for model development including linear regression, decision tree, and neural network. The best model was identified for each superstructure material through comparisons among different models. In addition, a discussion of individual variables and their contributions to predict superstructure rating was performed. The identified models provide insight into when a bridge superstructure needs maintenance and reconstruction.

Comparing the economic, energy, and environmental impacts of biodiesel versus petroleum diesel fuel use in construction equipment

ABSTRACT Advocates for biodiesel claim that it is a clean, renewable, and cost effective fuel that provides economic and environmental benefits while easing the energy impacts of petroleum diesel; however, these claims are often anecdotal in nature and may not be based on empirical data. This paper presents the results of a case study that analyzes the economic, energy, and environmental impacts of biodiesel versus petroleum diesel fuel use in construction equipment. Using real world data, statistical comparisons were performed on a fleet of backhoes, motor graders, and wheel loaders. Hypothesis testing was used to determine whether or not there was a statistically significant difference between B20 and petroleum diesel in fuel prices, fuel use rates, and emissions rates. Scatterplots were developed to show how the two fuels are related to each other. Results indicated that there was no statistically significant difference between the national average prices of B20 and petroleum diesel; however, there were statistically significant differences between B20 and petroleum diesel for fuel use rates and emissions rates. It was concluded that B20 has slightly higher economic and energy impacts than petroleum diesel, but B20 did show potential for lower emissions rates for some pollutants.

Using Data Analytics to Characterize Steel Bridge Deterioration

Bridges are a key component of transportation infrastructure. Currently, decisions on what material should be used to build a bridge superstructure are primarily driven by the initial costs in design/construction, but subsequent repair and maintenance costs are less emphasized. Moreover, limited budgets for bridge construction and maintenance require new processes to optimize decision making in choosing appropriate materials for bridges. This study aims to characterize the performance of steel bridge superstructures considering factors such as age, average daily traffic (ADT), design load, and structure length. This paper applies data mining techniques to the 2013 national bridge inventory (NBI) database for bridges whose superstructure material is steel or steel continuous and whose deck type is concrete cast-in-place. This study develops a model to predict the probability of a steel bridge superstructure being deficient given the characteristics of the bridge. The contribution of the paper is that the analyses will help stakeholders better understand what parameters are significant to the superstructure deterioration, and what type of steel bridges are more likely to have deficient superstructures.