For the Texas Department of Transportation (TxDOT), accurately predicting durations for right-of-way (R/W) acquisition and utility adjustment on highway projects has been deemed as one of the most important capabilities that regional districts should possess. Because this need is so pressing, TxDOT has sought to establish an effective methodology for predicting the durations of these two pre-construction processes. The “Right-of-Way Acquisition and Utility Adjustment Process Duration Information (RUDI) tool” was developed, which is an Excel-based tool that takes into consideration user inputs regarding project circumstances such as schedule urgency and levels of uncertainty. In this study, the accuracy of RUDI and the key drivers that affect the durations of R/W acquisition and utility adjustment have been examined in order to assess RUDI’s effectiveness in implementation on projects, to identify critical needs for enhancing RUDI, and to understand how practitioners can better predict durations needed for R/W acquisition and utility adjustment. RUDI proved useful in predicting durations with better accuracy in spite of limited data availability. Specifically, RUDI provided practitioners with reasonable duration ranges that can be used in better forecasting the durations of utility adjustment. Moreover, the study revealed that practitioners with more than 13 years of experience and R/W acquisition specialization showed better performance in estimating durations for R/W acquisition. Accurately estimated durations for utility adjustment were mostly provided by practitioners working at districts located in urban or metropolitan areas in Texas. The drivers identified significantly influential in predicting durations for R/W acquisition by the practitioners include “TxDOT Project Type,” “District R/W Annual Budget,” “Dedication of Funds to the Project,” “Funding Limitations for the Project,” “Level of Political Pressure,” “Need for Residential Relocation,” “Level of Local Availability of Replacement Housing Facilities,” and “Likelihood of Title Curative Actions,” “Status of Environmental Clearance,” “Status of Right-of-Way Map,” “Frequency of Eminent Domain,” “Right-of-Way and Utility Scope,” and “Number of Parcels for Acquisition.” Likewise, for estimating utility adjustment durations, the drivers deemed highly influential and important by the practitioners include “Dedication of Funds to the Project (R/W and Construction),” “Funding Limitations for the Project,” “Have Subsurface Utility Engineering (SUE) Investigations been Performed,” “Adjustment is Reimbursable Utility or Non-Reimbursable Utility,” “Status of Environmental Clearance,” “Status of Right-of-Way Map,” “Right-of-Way and Utility Scope,” “Number of Utilities Located in Private Easement,” and “Responsiveness of Utility Companies to TxDOT Needs.” These drivers should be considered key data points in RUDI because they can provide users with more duration ranges that can be useful in forecasting actual durations of R/W acquisition and utility adjustment on highway projects. The study also revealed that further research is needed to maximize the benefits of the RUDI tool, although validating the study’s findings was restricted due to a lack of data. Additional studies for improving the RUDI tool should focus both on collecting more recent data and reconstructing the tool in terms of function and structure. / text

State DOTs (department of transportation) spend billions of dollars on construction and maintenance of transportation projects every year. In addition, significant sums go to preliminary and construction engineering (PE and CE). For many projects, DOTs utilize engineering services from consultants, to supplement in-house engineering. The cost and quality of consultant’s engineering services compared to in-house, are important issues to justify the involvement of consultants. This report provides an analysis of those issues on Texas Department of Transportation (TXDOT) projects. Traditionally, the costs of PE and CE are calculated as a fixed percentage of total project construction cost, and the efficiency of engineering organizations is assessed by comparison of their gross percentages. However, the results presented here show that project scope and complexity are significant factors in PE and CE cost. Therefore, simplistic comparisons of PE and CE percentages can be misleading when applied across a mixed program of projects. / text

The purpose of this study was to improve flexible base course performance within the state of Texas while reducing TxDOT’s testing burden. The focus of this study was to revise the current specification with the intent of providing a “performance related” specification while optimizing sample sizes and testing frequencies based on material variability. A literature review yielded information on base course variability within and outside the state of Texas, and on what tests other states, and Canada, are currently using to characterize flexible base performance. A sampling and testing program was conducted at Texas A&M University to define current variability information, and to conduct performance related tests including resilient modulus and permanent deformation. In addition to these data being more current, they are more representative of short-term variability than data obtained from the literature. This “short-term” variability is considered more realistic for what typically occurs during construction operations. A statistical sensitivity analysis (based on the 80th percentile standard deviation) of these data was conducted to determine minimum sample sizes for contractors to qualify for the proposed quality monitoring program (QMP). The required sample sizes for contractors to qualify for the QMP are 20 for gradation, compressive strength, and moisture-density tests, 15 for Atterberg Limits, and 10 for Web Ball Mill. These sample sizes are based on a minimum 25,000 ton stockpile, or “lot”. After qualifying for the program, if contractors can prove their variability is better than the 80th percentile, they can reduce their testing frequencies. The sample size for TxDOT’s verification testing is 5 samples per lot and will remain at that number regardless of reduced variability. Once qualified for the QMP, a contractor may continue to send material to TxDOT projects until a failing sample disqualifies the contractor from the program. TxDOT does not currently require washed gradations for flexible base. Dry and washed sieve analyses were performed during this study to investigate the need for washed gradations. Statistical comparisons of these data yielded strong evidence that TxDOT should always use a washed method. Significant differences between the washed and dry method were determined for the percentage of material passing the No. 40 and No. 200 sieves. Since TxDOT already specifies limits on the fraction of material passing the No. 40 sieve, and since this study yielded evidence of that size fraction having a relationship with resilient modulus (performance), it would be beneficial to use a washed sieve analysis and therefore obtain a more accurate reading for that specification. Furthermore, it is suggested the TxDOT requires contractors to have “target” test values, and to place 90 percent within limits (90PWL) bands around those target values to control material variability.

The trend to outsource the engineering functions in state departments of transportation (DOTs) to private consultants has increased in recent years. However, most DOTs do not have a strategic approach to the outsourcing of engineering functions or projects. This thesis addresses that gap by examining outsourcing decision-making in the Texas Department of Transportation (TxDOT) and developing a rationalized procedure. TxDOT, the largest state DOT in terms of annual construction program,expends about 65% of its engineering on consultants. Staff from 18 of TxDOTs 25 districts were interviewed for this research, and Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis is used to identify improvements to the current decision-making processes. A framework is presented for systematic assessment of the outsourcing potential of engineering functions, which would enable TxDOT districts to determine what engineering work to contract out cost-effectively without sacrificing core competencies. / text

The VCOST budgeting tool uses a drive cycle simulator to improve fuel economy predictions for vehicle fleets. This drive cycle simulator needs to predict the efficiency of various components of the vehicle's powertrain including any differentials. Existing differential efficiency models either lack accuracy over the operating conditions considered or require too great an investment. A fundamental model for differential efficiency is a cost-effective solution for predicting the odd behaviors unique to a differential. The differential efficiency model itself combines the torque balance equation and the Navier-Stokes equations with models for gear pair, bearing, and seal efficiencies under a set of appropriate assumptions. Comparison of the model with existing data has shown that observable trends in differential efficiency are reproducible in some cases to within 10% of the accepted efficiency value over a range of torques and speeds that represents the operating conditions of the differential. Though the model is generally an improvement over existing curve fits, the potential exists for further improvement to the accuracy of the model. When the model performs correctly, it represents an immense savings over collecting data with comparable accuracy. / text