Colorado Department Of Transportation Research Articles

Evaluating of 14H-Piles’ Load Capacity in Cohesionless Soils for Edward’s Project Using ?-Method and Finite Element Method

Abstract: This paper presents a comprehensive study on evaluating the load capacity of 14H-piles in cohesionless soils for Edward's infrastructure project[1]. The project, overseen by the Federal Highway Administration (FHWA) and the Colorado Department of Transportation (CDOT), focuses on bridge replacements in Edwards, Colorado, with an emphasis on foundation improvements using driven pile foundations[2]. The research utilizes Finite Element Analysis (FEA) and the β-method to assess the total bearing capacity of 14H-piles in sandy soil conditions[3]. Field exploration, including Standard Penetration Tests (SPT), is conducted to determine soil parameters, followed by calibration of soil strength parameters. The study involves modelling the piles using the Soil-Structure Interaction 3-D program (SSI3D) and comparing the total bearing capacity obtained from FEA with nominal capacities calculated by the β-method. Additionally, the paper discusses load resistance and factor design, as well as the importance of static load testing for validation[4]. The results highlight the efficacy of FEA in predicting pile behaviour and provide valuable insights for foundation design in similar geological settings.

Development of load-resistance-factor-design-based prestressed concrete tub girders in Colorado

This paper presents a new tub girder series for Colorado, conforming to the articles of the American Association of State Highway and Transportation Officials’ AASHTO LRFD Bridge Design Specifications. Although the B618 tub girders developed by the Colorado Department of Transportation in the 1990s have been successfully used for decades, the need for an upgrade is essential to satisfy the requirements of contemporary bridge design and construction. After examining the performance of tub girders selected from six transportation agencies in the United States, an optimization algorithm was employed to generate efficient prototype sections. Then, detailed investigations were conducted to examine various practical aspects concerning the serviceability and ultimate limit states of AASHTO LRFD specifications. Parametric analysis with five bridge superstructures that accommodate up to four traffic lanes demonstrated the applicability of the prototype girders. A simplified version of the prototype sections was also delineated for regional precasters. Furthermore, a comparative study was carried out to evaluate the geometric stability and production costs of the prototype, simplified, and existing B618 girders.

Recommendations for cradle-to-gate environmental product declarations (EPD) in ‘Buy Clean’ procurement based on CDOT’s experience

The use of environmental product declarations (EPDs) in procurement of construction materials has been of increasing interest to government agencies, and adoption in the United States has been driven in part by ‘Buy Clean’ legislation. Buy Clean encompasses green procurement policies that promote the purchase of construction materials and products with lower environmental impacts, considering the life-cycle impacts associated with those materials. Most EPDs for transportation infrastructure construction materials are ‘cradle-to-gate’, or representative of the material production stage of a product and not the entire life cycle; however, these EPDs can allow meaningful quantitative comparisons of environmental and sustainability indicators and serve as a mechanism for measuring improvements in environmental impacts during the production of materials. This paper describes how cradle-to-gate EPDs are used, presents a case study of initial implementation of an EPD policy by the Colorado Department of Transportation, and provides recommendations to address some of the challenges that agencies and stakeholders can face when developing or participating in new EPD programs. It is desired that the recommendations and case study presented in this paper will help provide pathways to agencies for the successful enactment of Buy Clean policies and enable mitigation of actual or perceived barriers to program implementation.

Converting detailed estimates to primary estimates with data augmentation

In general, preliminary or primary cost estimates are used to select contractors from among bidders in Japan. The primary cost estimate must be accurate, otherwise the contractor selected from the bidding process will lose profit. A general contractor in the world does not have a super-skilled engineer who can achieve the accurate primary cost estimates. The conventional primary estimate has a high error range and low reliability. An automated system converting detailed estimates to primary estimates has been highly demanded in the world. This paper presents a prototype AI converter that can accurately and automatically convert detailed cost estimates into primary estimates. Converting detailed cost estimates to primary estimates lies in a regression problem. This paper proposes a feature-elimination based data augmentation method for regression problems. The empirical experiment shows that the proposed data augmentation method is quite effective with an Extra-Trees ensemble method. The proposed method was empirically examined by using Colorado Department of Transportation (CDOT) dataset for accurately predicting constructions costs with the Extra-Trees algorithm and random forest algorithm respectively. The CDOT dataset is one and only one of the largest datasets available in public for constructions costs quotation/estimation of roads, bridges and buildings.

Optimizing Expert-Based Decision-Making of Pavement Maintenance using Artificial Neural Networks with Pattern-Recognition Algorithms

Light pavement rehabilitations and low-cost treatments are extensively employed among transportation agencies on roads with relatively low traffic volumes to optimize available resources. One concern with this approach entails the difficulties of determining the optimal timing for treatment application. Making the best use of limited resources requires improvements in maintenance decision-making for selecting treatments considering all affecting factors and previous experience. This paper presents a machine learning approach in the decision-making process for determining the most appropriate pavement maintenance and rehabilitation alternatives for low-volume paved roads at the network level. Based on regional experts’ recommendations and engineering judgments in Colorado, a wide range of 884 cases of pavement-treatment patterns were generated. Then an artificial neural network (ANN) was trained with pattern-recognition algorithms. Two ANN prediction models were developed on the basis of pavement condition data, represented by six condition indices, and road lengths. The objective of training the models is to evaluate the variability of maintenance practices among five engineering regions within the Colorado Department of Transportation (CDOT). The outcome of this study describes the implementation gaps of pavement-preservation activities among CDOT regions resulting from limited maintenance funding. The regional maintenance selection can be processed by the developed ANN decision-making tool to recommend alternatives from regional recommendations as well as similar applications statewide to fit pavement management needs and expected performance.

Drivability life of pavement: a new numeric in pavement management system

ABSTRACT In recent years, the Colorado Department of Transportation (CDOT) developed Drivability Life (DL) index to estimate useable pavement service life for roadway segments. The DL process is similar in concept to the Remaining Service Life (RSL). The DL of pavement is a measure, in years, of how long a roadway segment will have acceptable driving conditions. A preliminary experimental study conducted by CDOT concluded that the DL can be efficiently used in Pavement Management System (PMS). For detail analysis, CDOT incorporated DL in their 2013 and 2014 PMS database. This paper presents the results from the experimental study and performed a preliminary analysis on the low volume roads in the State of Colorado. Analysis confirmed that the RSL can be replaced by DL, and may help representing more accurate pavement condition of a roadway segment, thus help maintaining the roadway networks efficiently.

Integration of optimization methodology to evaluate pavement maintenance strategies for deteriorated low-volume roads

Low-volume roads (LVRs) are restricted with limited maintenance funding due to the recent national economic downturn. Only few selected LVRs with deteriorated pavements are typically rehabilitated in which poor LVRs are expected to continue deteriorating to extreme levels of distress. Colorado Department of Transportation (CDOT) is evaluating pavement treatments on LVRs to find the most cost-effective maintenance strategies. As part of these efforts, a comprehensive optimization analysis is adopted in this paper to investigate alternative maintenance strategies and define the capital improvement plans for deteriorated LVRs with marginal pavement conditions. A proposed strategy was found to enhance the effectiveness of current policies followed by CDOT. However, the results emphasize the need for additional resources at network level for dealing with deteriorated LVRs. The optimization procedure described in this paper can be followed by other agencies nationwide to identify strategies and establish funding needs that secure higher funding from decision makers.

Carbon nano-tube as water reducer in CDOT Class E 12 hr concrete mix

To address maintenance and durability issues for concrete pavement, the City and County of Denver explored the use of carbon nano-tube admixtures. This research documents the hardened and fresh properties of two mix designs that use carbon nano-tube admixture as a water reducer. The authors performed compressive strength, slump and air-entrainment tests. Results indicate that the 3 gallon-per-yard (GPY) (14.85 l/m3) mix provides both the highest slump and the highest compressive strength, while meeting the air-entrainment specifications for Colorado Department of Transportation (CDOT) Class E 12 h Concrete Mix. While additional testing is recommended to evaluate long-term maintenance impacts, initial results are promising and suggest that adoption of a 3 GPY (14.85 l/m3) mix may be a viable alternative for CDOT. The contribution of this research is to document preliminary laboratory and in-situ testing of carbon nano-tube admixtures in concrete pavement mix design.

Applying Large-Scale Optimization to Evaluate Pavement Maintenance Alternatives for Low-Volume Roads using Genetic Algorithms

Over the last decade, significant progress has been made to customize the maintenance policies of low-volume roads (LVRs) to local needs and available resources. Low-cost treatments and surface repairs are extensively employed to reduce annual maintenance costs. Colorado Department of Transportation (CDOT) uses chip seals and thin overlays as the available treatment options applied to LVRs. However, the effectiveness of these treatments differs depending on the existing condition of pavements. Some surface treatments and light rehabilitations provide only short-term effectiveness. Multi-year optimization techniques can support decision makers with a set of optimal maintenance activities to achieve specific pavement performance targets. This study applies large-scale optimization to compare the current CDOT maintenance policy with an alternative strategy recommended for low-volume paved roads in Colorado. Genetic algorithms were applied in the optimization models because they are capable of resolving the computational complexity of optimization problems in a timely fashion. The optimized maintenance alternatives were comprehensively investigated for a LVR network in Colorado over a specific planning horizon. The specific optimization constraints and limitations prevailing in LVRs are addressed and introduced in the problem formulation of the optimization process. The results of both performance and cost analysis emphasize the effectiveness of the proposed maintenance strategy compared with the existing one. The alternative policy provides much more benefit-cost saving while preserving the overall pavement performance of the network. This approach is expected to be efficient to quantify the mid- and long-term financial impact of different treatment policies applied to LVRs within modest resources.

The Case for Flux‐Based Remedial Performance Monitoring Programs

The Case for Flux‐Based Remedial Performance Monitoring Programs

Developing a methodology to evaluate the effectiveness of pavement treatments applied to low-volume paved roads

ABSTRACTA significant number of agencies allocate low funding levels for their low-volume roads (LVRs) as part of their pavement management system (PMS) funding strategies. Although agencies have been applying a number of low-cost treatments, the effectiveness of the applied treatments towards improving pavement performance is not well understood or documented. The application of low-cost treatments on roads has different levels of impact on the pavement performance depending on the initial pavement condition. This study introduces a methodology of evaluating in-practice surface treatments on LVRs. The methodology can be implemented by different transportation agencies using historical data of pavement condition and treatment records. A case study of managing LVRs in Colorado was investigated using the historical PMS data of Colorado Department of Transportation (CDOT). The performance of pavement in the context of fatigue, longitudinal, and transverse cracking was analysed and the results show different trends of common treatment options applied to LVRs. It was concluded that some surface maintenance strategies are effective long-term treatments for fatigue, longitudinal, and transverse cracking. However, the effectiveness of these treatments depends mainly on the initial condition index. The findings of this study permits increased understanding of selected maintenance treatments. An appropriate maintenance strategy was developed including all effective treatments. The comprehensive long-term analysis of road maintenance and costs shows that the proposed maintenance strategy is more cost-effective compared to the current policy followed by CDOT.

Best practices to support and improve pavement management systems for low-volume paved roads

ABSTRACTThe most important issue in managing low-volume roads (LVRs) is to define standards and practices applied on roads. In recent years, transportation agencies have dealt with considerable challenges for managing LVRs. These challenges include reductions in maintenance budgets; impact of industrial activities; and ineffective treatments applied on paved roads. The Wyoming Technology Transfer Centre (WYT2/LTAP) conducted online surveys as part of a research project conducted jointly with the Colorado Department of Transportation. The objective of the surveys is to document what the transportation agencies, including state departments of transportation (DOTs), are doing to face these challenges. Four online surveys were sent to the TRB LVRs committee, eight DOTs, local governments in Colorado and the material advisory committee in the Colorado DOT. These surveys have an average of 26 questions dealing with pavement management system (PMS) specifications recommended for low-volume paved roads. Seventy-one transportation agencies responded to the survey. This paper summarises the responses to the survey showing innovative programmes, procedures and products that are successfully meeting LVRs pavement management needs.

Simple-Made-Continuous Steel Bridges with Steel Diaphragms

Simple-made-continuous (SMC) bridges are a relatively new innovation in steel bridge design. The majority of SMC bridges currently in use are constructed with concrete diaphragms. This article presents the results of numerical analysis and physical laboratory testing of an alternative simple-made-continuous (SMC) connection scheme that uses steel diaphragms in lieu of concrete diaphragms. A bridge using steel diaphragms was constructed by the Colorado Department of Transportation in 2005, and the connections on this bridge serve as the basis for the research discussed herein. The results of the analysis and testing provided information for the development of a design methodology based on the physical behavior of the SMC connection. The paper also compares the steel-diaphragm SMC connection to concretediaphragm SMC connections and demonstrates that the steel-diaphragm design has several desirable features. For a diaphragm cost, which is similar in cost to other SMC schemes, the steel-diaphragm design requires less total construction time. Additionally, because the girder ends are exposed, it is easy to verify that the girders have fully weathered (for weathering steel), they may be easily inspected, and there is no concern about cracking of a concrete diaphragm at re-entrant corners around the steel bridge girders.

Developing Pavement Distress Deterioration Models for Pavement Management System Using Markovian Probabilistic Process

In the state of Colorado, the Colorado Department of Transportation (CDOT) utilizes their pavement management system (PMS) to manage approximately 9,100 miles of interstate, highways, and low-volume roads. Three types of deterioration models are currently being used in the existing PMS: site-specific, family, and expert opinion curves. These curves are developed using deterministic techniques. In the deterministic technique, the uncertainties of pavement deterioration related to traffic and weather are not considered. Probabilistic models that take into account the uncertainties result in more accurate curves. In this study, probabilistic models using the discrete-time Markov process were developed for five distress indices: transverse, longitudinal, fatigue, rut, and ride indices, as a case study on low-volume roads. Regression techniques were used to develop the deterioration paths using the predicted distribution of indices estimated from the Markov process. Results indicated that longitudinal, fatigue, and rut indices had very slow deterioration over time, whereas transverse and ride indices showed faster deterioration. The developed deterioration models had the coefficient of determination (R2) above 0.84. As probabilistic models provide more accurate results, it is recommended that these models be used as the family curves in the CDOT PMS for low-volume roads.

Economic Impacts from Geologic Hazard Events on Colorado Department of Transportation Right-of-Way

The economic impacts from geological hazards that occur within or adjacent to Colorado Department of Transportation (DOT) right-of-way can be measured in support of exposure estimation for risk-based asset and performance management. The events include rockfalls, rock slides, landslides, debris flows, and sinkholes and can be categorized as routine maintenance, regular program activities, and urgent response. The statewide economic impacts from geologic hazards were grouped into two categories: ( a) direct costs for maintenance labor and equipment, engineering, and construction and ( b) indirect costs, including property damage, injury or fatalities, traveler delay, lost productivity, loss of revenue to businesses and communities, and environmental impacts. Annual direct department costs from geologic hazard events average about $17 million to $20 million, which includes maintenance staff response to approximately 8,500 work orders each year. Most work orders are high-frequency events that are addressed daily by maintenance staff. Conversely, some events occur less frequently and have a larger economic impact, particularly for users and communities. In 2014, the economic impact from geologic hazards on Colorado DOT roadways was estimated to be nearly $30 million. Historical data indicate that the 2014 estimate is conservative when high-volume roadways are affected or when more large events occur in a single year. For example, the economic impact for two rockfall events on I-70 in 2004 and 2010 was estimated to be more than $40 million each, adjusted to 2015 dollars. When average Colorado DOT direct expenses are included, the economic impact in those years may have exceeded $60 million.

Risk and Resilience Analysis for Highway Assets

Transportation agencies own tens of thousands of assets, providing essential mobility and economic services to the communities they serve. Moving Ahead for Progress in the 21st Century and subsequent legislation require asset managers to implement risk-based asset management. A discussion is presented on the application of one quantitatively based framework—the American Society of Mechanical Engineers Innovative Technology Institute's Risk and Resilience Analysis and Management for Critical Asset Protection—for analyzing risks posed by physical threats to highway transportation systems and assets. The application of this particular risk analysis framework by the Colorado Department of Transportation following the 2013 floods is recounted; the analysis was used to support requests for federal emergency response funding. Finally, the potential benefits of such analysis for highway transportation project planning and strategic planning are also examined.

Calibration of Pavement Rutting Prediction in Colorado Using Layer-Specific Rutting Model Coefficients for Hot-Mix Asphalt in AASHTOWare Pavement ME Design

The Colorado Department of Transportation (DOT) recently concluded a study to adopt the AASHTO Mechanistic–Empirical Pavement Design Guide (MEPDG) and the accompanying software into its routine pavement design practice. Implementation of the MEPDG in Colorado required local calibration of the MEPDG prediction models for distress and smoothness. This paper presents a discussion of the calibration of the “global” rutting model to account for Colorado’s unique climate, traffic, and soil conditions as well as the various asphalt concrete (AC) mix types used in the state. A key challenge during the local calibration effort was to produce a rutting coefficient for each AC mix type: Marshall, Superpave®, and polymer-modified asphalt (PMA). Local calibration of the MEPDG global models by using Colorado DOT input data was performed with a nonlinear model optimization tool available in the SAS statistical software. Global model coefficients were adjusted through local calibration for AC rutting, unbound aggregate base rutting, and subgrade rutting. Four of the 10 model coefficients were adjusted. The local calibration coefficient βr1turned out to be different for each of the three primary Colorado DOT ACs. As expected, of the three asphalt mixes, the PMA had the coefficient with the lowest value for βr1, and as a result this mix had the lowest AC rutting. The goodness of fit and bias test results indicated an adequate goodness of fit with minimal bias. This local calibration effort improved the overall prediction accuracy of the rutting model and its standard error.

Environmental Reviews and Case Studies: NEPA Strategies for Accelerating Project Delivery: Every Day Counts, Tiering, and Alternative Delivery in the I-70 Mountain Corridor

The Federal Highway Administration (FHWA) and the Colorado Department of Transportation (CDOT) have used Every Day Counts tools and other strategies to accelerate the National Environmental Policy Act (NEPA) process for projects intended to relieve congestion and improve safety in the Twin Tunnels area of Colorado’s Interstate 70 (I-70) Mountain Corridor. These Tier 2 projects follow the I-70 Mountain Corridor Tier 1 Programmatic Environmental Impact Statement (PEIS). The Tier 2 Twin Tunnels projects incorporated tools from the FHWA Every Day Counts Shortening Project Delivery Toolkit, including the Planning and Environmental Linkages concept, legal sufficiency enhancements, and programmatic agreements; the Construction Manager/ General Contractor (CM/GC) alternative delivery method; and a unique stakeholder engagement approach. These tools were effective in reducing the Tier 2 NEPA process to half its normal duration, thereby accelerating overall project delivery. The Tier 2 process was easier to implement because of the scaffolding developed during the Tier 1 process. Establishing an early involvement agreement related to legal reviews allowed FHWA attorneys to work with the project team at early decision points. Using the CM/GC alternative delivery method allowed for early input from the contractor on the preliminary design, avoided the need for NEPA re-evaluations during the final design or construction process, and led to new ideas for avoiding or minimizing impacts to environmental resources. Early and continuous engagement with partner agencies and other stakeholders allowed for quick feedback and provided the necessary support to move the project forward quickly.Environmental Practice 17: 278–290 (2015)

Perspectives from the Field: Applying LEAN Process Management to the NEPA Process: The Simplified EA/CE

The National Environmental Policy Act (NEPA) process and NEPA documents are constantly being assaulted as being too long, too cumbersome, too expensive, taking too long to accomplish, and not successfully accomplishing the goals of NEPA. Over the years, numerous efforts have attempted to reduce the overall cost, time, and size of NEPA documents. Unfortunately, most of these efforts have failed and, in many cases, actually have made things worse.Lean process management is a tool that can be used to effectively identify opportunities to improve the NEPA process and NEPA documentation in a manner that does not compromise the principles and requirements of NEPA, but allows for more effective and efficient development of NEPA documents. The result can be NEPA documents that are shorter, but overall documentation that is more complete than what is being developed today. The simplified environmental assessment/categorical exclusion template developed for the Colorado Department of Transportation (CDOT) is an example of what this process can accomplish when Lean is applied to NEPA, and the results are staggering. In the pilot, CDOT achieved a 75% reduction in the size of the document and a 50% reduction in review time. The second project to use the template saw even better results.Environmental Practice 17: 302–307 (2015)

67 Prevalence and perceptions of risk of alcohol vs. marijuana impaired driving among adults in colorado

Purpose This study will present the prevalence of self-reported marijuana and alcohol impaired driving, compare perceived risks of driving under the influence of alcohol versus marijuana, and examine risk factors associated with impaired driving. Methods Data are from a telephone survey conducted by the Colorado Department of Transportation in 2014. The survey included questions assessing substance use, perceptions of risks and consequences related to impaired driving, and frequency of impaired driving among a representative sample of Colorado adults. The sample (n = 770) was weighted to reflect the 2010 Census estimates for Colorado. Results Few respondents perceived it safe to drive under the influence of alcohol (6%). However, those who reported past month marijuana use were more likely to report that they could safely drive after using marijuana (49%) compared to those that did not use in the past month or those that used alcohol in the past month. Of those that used marijuana in the past month, 73% endorsed marijuana impaired driving is safer than alcohol impaired driving. Marijuana users reported driving under the influence of marijuana on an average of 5.1 days in the past month compared to alcohol users who reported driving alcohol impaired on 1.2 days. Marijuana impaired drivers were more likely to be male, younger (18–34) and have some college education as compared to a bachelor degree or more education. Conclusions Perceptions of risk associated with marijuana impaired driving is lower than that associated with alcohol, particularly for current marijuana users. Current marijuana users drive impaired more frequently than alcohol users. Significance Understanding who drives impaired and their perceptions of risk can inform prevention messaging and public awareness campaigns.