Flexible pavements become stiffer with age due to asphalt binder oxidation. This reduces the asphalt concrete’s capacity to relax under constant loading and increases the possibility of brittle cracking under repeated loading. Hence, asphalt binder oxidation reduces the durability of flexible pavements. It occurs faster at the pavement surface layer and decreases non-linearly with depth.
Mismatches between rheological/chemical properties of extracted (from field cores) and laboratory-aged binders have been attributed to unrealistic laboratory aging. It has been proposed to adjust the duration of aging in standard procedures to better capture depth and temperature effects. However, the effect of ultra-violet (UV) insolation on the oxidation process and profile is still unknown. Understanding the role of UV insolation on asphalt binder oxidation could improve modeling of asphalt binder aging and simulations of accelerated laboratory aging.
A repeatable method to insolate asphalt binder with UV light requires the insolation of other mix variables, including moisture condition and temperature. Therefore, an accelerated aging procedure that utilizes UV insolation, moisture, and temperature of asphalt binder and asphalt mixture has been developed, known as TEcnico Accelerated aGEing (TEAGE). In this study, controlled moisture, temperature, and uniform UV insolation have been used. Adequate film thickness and initial aging condition of asphalt binder have been selected. The evaluation process and testing results that support the developed UV aging method are presented.

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Ultra-violet (UV) Aging for Asphalt Binder Under Controlled Moisture and Temperature Conditions

Plants are a key part of LID/GSI bioretention systems. They provide functional value and multiple environmental, social, and community benefits. LID systems are touted as a visual amenity to communities through lush plantings and immersive landscapes. Achieving and maintaining LID as a community amenity takes work and practitioners have found it is more difficult than initially thought to bring the lush landscape to life. Plants need water and good soil conditions, competition with weeds needs to be controlled, and maintenance crews need to know what they are maintaining.
This workshop will give practical tips on how to create and maintain a planted landscape to survive and thrive. What are the best plant selections, what establishment regime is needed, and how little maintenance can be done? This interactive workshop will bring together landscape professionals and municipal program managers to give you the time tested and latest techniques to create bioretention landscapes to survive and thrive. Bring your planting challenges and share with the group while the experts provide strategies and solutions. Practical solutions will be discussed that you can incorporate into your planting designs and program.

Planting Strategies to Survive and Thrive: Keeping the Bio in Bioretention

**Abstract Text**
The recently-launched NASA Surface Water and Ocean Topography (SWOT) Mission will provide first-of-its-kind satellite swath altimetry by simultaneously measuring surface-water elevations and water extent. SWOT will provide these unique data for inland water bodies at high vertical (<10 cm) and spatial resolution (3-40m) over large spatial scales; every hour, SWOT observes more than half a percent of Earth’s area. For many large global rivers, nearly the entire river systems will be observed over the course of several minutes with repeat times of approximately once every ten days in mid-latitudes and up to eight times per 21-days in high latitudes. SWOT will greatly advance global observations of lakes and large rivers, particularly in locations lacking gage data. For regions with gage data, there are additional benefits including improving hydrologic and hydraulic modeling, refining water-balances of lakes and watersheds, estimating inland bathymetry, and assessing habitat conditions for fisheries. Because of the novel satellite instrument design and its first-of-its-kind observations, the calibration and validation (cal/val) of the data will be particularly important. CIRES is co‑leading cal/val of SWOT inland water measurements and data products. In this talk, an overview of SWOT will be presented, as well as cal/val plans for the satellite and observations, including plans for the western CONUS.



The NASA Surface Water and Ocean Topography (SWOT) Mission: Advancing Global Inland Hydrology (Room 322, June 26th, 3:30pm-5:00pm)

ASCE Update and Bridge Scour During Extreme Events

Resiliency through Subsurface Documentation

**Abstract Text**
Infrared quantitative image velocimetry (IR-QIV) is a large scale surface velocimetry method that uses infrared imagery to calculate the mean and instantaneous  velocity at high resolution in space and time, over large spatial areas (Schweitzer & Cowen, WRR 2021). IR-QIV can operate continuously for extended periods (days, weeks, etc.) without requiring artificial illumination or particle seeding of the flow. The high resolution, continuous, measurement capabilities of IR-QIV make it particularly well suited to applications such as fishery management studies, where metrics of the flow must be resolved and correlated with fish behavior.

We present results from using IR-QIV as part of a large fishery management project in California, USA. The junction of the Sacramento River and Georgiana Slough is a tidally forced, hydrodynamically complex river junction, at which navigational choices of migrating salmonids and other fish have significant impact on their survival rates. A bio-acoustic fish fence (BAFF) was installed on site by the California Department of Water Resources (DWR) to divert fish towards the routes with higher survival probabilities. IR-QIV measurements were conducted to inform management practices, and results are presented here, including comparison to ADCP velocity measurements conducted on site by the US Geological Survey (USGS).



Infrared Quantitative Image Velocimetry (IR-QIV) Measurements at a Tidally-Forced River Junction (Room 312, Tuesday June 27th, 2:00pm-3:30pm)

Extraterrestrial construction presents many interesting and new challenges. Transporting large amounts of construction materials from Earth is cost prohibitive. Thus, to take advantage of limited in situ extraterrestrial resources, this work focuses on a novel class of biopolymer-bound soil composite (BSC) materials. These quasi-brittle composites are produced by desiccating a mixture of soil, water, and a biopolymer binder to create a versatile material with uniaxial compressive strength comparable to concrete. This paper expands upon a BSC design methodology for regolith soils. Previous work has been successful in reliably designing BSC materials with graded sands that exhibit compressive strengths above 20 MPa. Lunar regolith, JSC-1A simulant presents an additional challenge due to the broad ranges of the soil particle sizes. Nineteen BSC mixes using JSC-1A regolith were tested with varying biopolymer solution concentrations and biopolymer to soil ratios. A maximum compressive strength of 25 MPa was obtained at a biopolymer concentration of 48% and a biopolymer to soil ratio of 12.4%. A brief discussion on the effect of manufacturing variables on compressive strength and bulk density is presented. Finally, a design tool is introduced to design regolith BSC for desired compressive strength for future use in the structural design of structures on the Moon, Mars, or other extraterrestial bodies.

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Designing Biopolymer-bound Regolith Composites for Maximum Compressive Strength

Megathrust subduction earthquakes from the Cascadia subduction zone can trigger catastrophic tsunamis in the Pacific Northwest. Coastal communities on Vancouver Island’s west coast are exposed to major fatality risks. An F-N curve is an exceedance frequency (F) plot in terms of the number of anticipated fatalities (N). Different slopes of societal risk tolerability limits that are expressed in the form of an F-N plot following the principle of ALARP (As Low As Reasonably Practicable) can represent different societal risk attitudes (e.g., risk-neutral versus risk-averse) toward specific hazards. The comparison of an F-N curve with such societal risk tolerability limits can inform the adequacy of current disaster risk management practices from the viewpoint of societal risks.



Developing an F-N curve for coastal communities subjected to tsunami fatality risks is not a trivial task. It requires careful and comprehensive consideration of uncertainties associated with the assessments of tsunami fatality risks to the exposed population. These uncertainties should account for possible tsunami scenarios (e.g., earthquake occurrence, rupture pattern, and tsunami inundation) as well as variable population exposures and fatality rates. In other words, the development of a tsunami F-N curve involves significant computations by running a viable tsunami catastrophe model that can quantify the fatality risks to individuals.



This study presents a tsunami fatality risk model for coastal communities in Tofino, British Columbia, which are exposed to potential threats from the Cascadia subduction megathrust tsunamis. To account for uncertainties in earthquake rupture scenarios, stochastic source models for the Cascadia subduction events are generated and implemented in Monte Carlo tsunami inundation simulations. The inundation model is developed with high-resolution bathymetry-topography elevation data in Tofino, allowing accurate representations of tsunami risks to the exposed population. To evaluate the number of fatalities as a function of inundation depth, the most recent tsunami fatality rate models from Japan are adopted by considering a range of spatial distributions of residents and visitors in Tofino, reflecting different daily and monthly variations of the exposed population. The results from the tsunami fatality risk model can be presented as a tsunami F-N curve and can be compared with several societal risk tolerability guidelines that have been adopted in British Columbia for disaster risk management purposes (e.g., landslides). The results of this investigation are particularly valuable for informing tsunami risk reduction policies (e.g., planning and design standards) based on quantitative risk metrics for exposed coastal communities in British Columbia.

Development of Tsunami Frequency-Fatality Numbers (F-N) Curve for Coastal Communities Subjected to Cascadia Subduction Earthquakes

Abstract: With the rapid development of urban rail transit, the shield tunnel in-service is inevitably affected by the surrounding construction, such as ground surface surcharge and adjacent excavation. The adjacent construction will cause the stress redistribution of the soil around the tunnel in-service and thus affect the deformation performance of the existing tunnel. This study investigates the effect of ground surface surcharge on the deformational behavior of shield tunnel in-service in spatially variable soil. A three-dimensional random field model of soil stiffness parameter is employed in this study. The soil elastic modulus is highlighted and modeled by an isotropic random field that is discretized by covariance matrix decomposition. On this basis, the reliability analysis of longitudinal deformation and transverse contraction of shield tunnel is carried out by using the random finite element method (RFEM) and Monte-Carlo (MC) algorithm. The research results reveal the deformation pattern of the tunnel caused by the ground surface surcharge and quantitatively describe the influence of the ground surface surcharge on the deformational performance of existing shield tunnel in spatially variable soil. It demonstrates that ignoring spatial variability leads to an underestimation of tunnel convergence, particularly when it is severely disturbed by nearby environments, as in this paper's ground surface surcharge. The work mentioned in this paper provides a theoretical support for the prediction and control of tunnel deformation in engineering practice.

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Modified matrix decomposition method for generating multivariate cross-correlated random fields

One of NASA’s goals is to identify and characterize potentially habitable environments in the Solar System and beyond. While the search for evidence of extant and extinct life, and conditions supporting life in the Solar System, has primarily focused on Mars, there is strong evidence that a number of outer solar system moons (e.g., Europa, Enceladus, and Titan) harbor subsurface oceans. These “ocean worlds” may be the best places to search for extant life beyond Earth. However, due to the extreme environmental conditions and communications constraints, current mission operations practice of pervasive ground control supervision will be unproductive, and substantially autonomous operations will be required. This paper provides an overview of an autonomy software testbed simulation facility, the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) that NASA Ames Research Center is developing to spur the development of such autonomous operation capabilities.

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OceanWATERS: An Autonomy Software Testbed Simulation for Ocean Worlds Missions

The stone column is one of the ground improvements that is widely used around the world. This technique is an effective method to improve the weak soil by increasing the bearing capacity of the soil, establishing a drainage path, and reducing the settlement which can be cost-effective and environmentally friendly. This is a new and effective technique, since many studies have been conducted on this technique to optimize the performance of the foundation of stone columns. However, there are still deficiencies related to the column-soil system modeling, design procedure, column backfill material types, and loading type (i.e. working or ultimate, static or dynamic). This paper highlights the gaps in the experimental, numerical, and theoretical analysis of the stone column in the published research papers and to provide future researchers with information that assigns the risk in designing and constructing this technique. This paper will focus on studies of a single and groups of columns that are installed in different weak soils as end bearing or floating columns while considering all column types. Summaries of the data and findings of the previous studies mentioned in this paper were tabulated to facilitate the accessing of the information by other researchers.

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Stone Column Ground Improvement Analysis: Gaps

Presentation Outline

Introduction and site suitability evaluation methods and tool
Municipal flood reduction examples and pollutant reduction performance
Hydrologic design overview
Structural design method developed from full-scale PICP load testing
Construction do’s and don’ts
Handling slopes and utilities
Maintenance evaluation methods and recent developments in cleaning equipment

Permeable Interlocking Concrete Pavement

The optimization of water networks supports the decision-making process by identifying the optimal trade-off between costs and performance (e.g., resilience, leakage, etc.). While the complex nature of water distribution systems (WDSs) has already been explored with complex network analysis (CNA), literature is still lacking a CNA of optimal water networks.

The aim of this work is to explore network characteristics of optimal networks. Therefore, different real WDSs are optimized with a two-objective methodology considering costs and resilience. Based on a systematic CNA of these Pareto-optimal solutions, a new CNA design approach for WDSs is proposed. The approach is based on the customized edge betweenness centrality and does not require hydraulic simulations during the optimization process. The results need to be checked only afterwards to confirm that the given pressure constraints are fulfilled. When compared to short execution time of the order of a few seconds required by the CNA design, the evolutionary optimization (EO) requires hours or even weeks of computational time to obtain the results (i.e., the CNA design is faster with a factor of up to 105). The proposed approach is even applicable to very large networks (more than 150,000 pipes), which cannot be tackled with EO approaches in acceptable CPU time.

Although the proposed approach partly outperforms the EO approach, the resilience range of the obtained solutions is smaller compared to the results of the EO algorithm. However, within the resilience range obtained by the CNA design lies the resilience value of the real design. Therefore, the proposed approach can provide useful results for tasks where a fast design without EO is required, i.e., without a wide range of solutions needed (e.g., in course of integrated studies, design for a great number of networks, to generate the initial population for EO or for implementation in engineering software).

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A Complex Network Approach for Pareto-Optimal Design of Water Distribution Networks

A carbon nanofiber aggregate (CNFA) contains carbon nanofibers (CNFs) as an admixture of selfconsolidating mortar and produces an electrical response under stress. CNFA is a sensor that notifies the health status and provides a signal for the structural health monitoring system. It is necessary to understand the working principle and behavior of a CNFA and observe if CNFAs show consistency under various stress. In this research, three sets of test methods were tested under different loading methods to investigate the electrical impedance of CNFA under compressive stress, including the sweep-frequency test, the response from load removal, and the response from a car wheel. The behavior of CNFAs and their consistency under various loading conditions relies on the fact that they are conductive under stress. First, the sweep-frequency test compares the electrical impedance for various frequencies ranging from 1 to 500 kHz when the CNFA is scanned without the load and with a constant load. After reaching the targeted load, it is kept constant. Second, the impedance of CNFA is recorded for a constant load and a selected frequency. The electrical response of the CNFA under constant load is compared with the electrical response without any load. Third, the car wheel provides the load to the CNFA. The three methods demonstrated a positive correlation between impedance and compressive stress. The variables considered in the tests are various concentrations of CNFs and the age of samples. Irrespective of these variables, the test results from three methods show consistency in the behavior of CNFA. Therefore, the correlation between the electrical impedance and the stress is validated based on the experimental study.

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Correlation of Impedance and Compressive Stress of Carbon Nanofiber Aggregates for Structural Health Monitoring

Nationwide initiatives are demanding the use of equitable and just resilience goals for guiding investment actions to mitigate the impacts of stressors on communities, paying special attention to disadvantaged and historically vulnerable communities. Modeling community response against these disruptive events requires adequate systems’ information (social, economic, physical, etc.) and robust approaches for capturing the multidimensional and uncertain nature of community resilience. Although the actual modeling approaches may portray inequitable impacts on underserved communities, these do not expose the exacerbated inequality from additional factors such as data scarcity, data quality and modeling biasedness, which is the focus of this paper. We explore the biases and inequities that may occur during modeling development, and which hinder our ability to predict actual and future community resilience. Furthermore, this study examines and discusses scenarios in which the results of existing approaches are likely to violate equity conditions without generating some alarm, being unable to capture the actual reduction of the model prediction confidence. A bridge transportation network is used for illustrative purposes. Different methods are evaluated to measure the potential biases on the model’s input information (such as bridge and road characteristics) and the infrastructure resilience predictions (e.g. damaged conditions after a seismic event occurs). Spatial distribution of biasedness and inequities are evaluated using metrics based on information theory and visualization tools. Time-dependent aggregated uncertainty on the information quality is also tracked and evaluated as a possible inequitable condition of the system. Correlations between different communities’ vulnerability and resilient metrics and model’s equity violations are found from the illustrative case. The heterogeneity in quality of information and shortfall of timely observations highly impacts specific clustered populations, which could be avoided if introducing smart resilience approaches. The insights presented in this study suggest that future efforts in improving resilience require modeling approaches able to self-guide collection of equitable information and to self-assess equity violations to reduce disparities on resiliency.

Exploration of biasedness and inequities in infrastructure resilience modeling

Recent hurricanes have caused significant damage to coastal buildings, which indicates the necessity for predicting damage and potentially developing mitigation strategies. However, the accuracy of existing models has not been adequately addressed that can adversely affect the reliability of outcomes. This presentation describes a data-driven validation of HAZUS-MH flood model. The validation is conducted based on a hindcast following Hurricane Ian (2022) impacted Fort Myers Beach to compare the observations with the model outputs. First, a comprehensive study is conducted to develop a hindcast, including estimating the first-floor elevation (FFE) and determining the overall Damage State (DS) rating from DS0 (no damage) to DS6 (the building is detached from its foundation) for buildings at the parcel level. The hindcast is developed for all 5,738 buildings located in Fort Myers Beach using different resources, such as satellite images, drone footage, and street views. Second, after a comprehensive Quality Assurance and Quality Control (QAQC), hindcasting is utilized to evaluate the uncertainty in model input and output variables. Third, the validation is not only carried out for HAZUS-MH flood model, but the outcomes are compared with those of other models, such as open-source Interdependent Networked Community Resilience Modeling Environment (IN-CORE) developed by Center for Risk-Based Community Resilience Planning. The findings can provide a better understanding of the reliability of existing models as well as better insight for decision-makers and emergency planners in coastal communities.

Model-data validation and uncertainty quantification of the IN-CORE and HAZUS-MH damage models for buildings impacted by Hurricane Ian (2022) at Fort Myers Beach, Florida

Over the last decades, the application of probabilistic safety assessment methods have been studied for geotechnical engineering structures in soil, as well as for civil engineering structures such as rock slopes and underground tunnels. In mining engineering, however, ground support design and underground excavation stability is still mostly assessed using deterministic methods.



Mining design differs from civil rock engineering design with respect to exhibiting more complex, and continuously changing, stress conditions, different excavation/extraction methods, and a larger scale of the operations. More importantly, civil engineering excavations are designed for public use and to be stable for long periods of time, and with a very low risk acceptance compared to mining. Design acceptance criteria can therefore focus on stability in civil engineering, while in mining engineering, the design acceptance criteria need to consider both safety of personnel and optimized financial value. Different excavations and portions of a mine also have different economic consequences of rock mass failure.



This paper explores the use of probabilistic design for mining activities and how to integrate probabilistic design into decision making in mining engineering. Relevant examples, on the use of probabilistic-based design methods, in civil and mining engineering are presented together with commonalities and case-specific characteristics. Open pit stability assessments are already suitable for probabilistic analysis, which are often also routinely applied. However, many underground mining issues first need identification of relevant limit states. The design acceptance criterion in mining should preferably be based on risk, which includes probabilistic assessment and risk evaluation components, since geomechanics aspects strongly influence both economy and safety. The accepted risk level to which the engineer needs to design should be aligned with the mining company risk profile and be linked to the different stages (collection of data, analysis, modification etc.) in the decision-making process. Based on experience from, and commonalities with, civil engineering the first step in the integration of probabilistic design in mining, should focus on the collection and uncertainty of data.

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Mining applications for probabilistic design

Christian and Baecher (2011) highlighted ten unresolved problems in geotechnical risk and reliability in the ASCE conference GeoRisk 2011. The top challenge in the list is “why are failures less frequent than our reliability studies predict?” They observed that previous reliability studies tend to over-predict failure probability: “at least an order of magnitude larger than the observed frequency”. The actual failure probability is often quite small. For example, the observed annual rates of slope failure in Hong Kong were 0.041% and 0.329% for engineered and non-engineered slopes in 2020. To address this challenge, this study proposes to explicitly model landslide triggering mechanism (e.g., rainfall infiltration) and utilize the fact that an existing slope stayed stable during past rainfall events to update uncertain soil parameters for predicting the time-variant slope failure probability under a future target rainstorm. Results showed slope survival records could be utilized to reduce uncertainties in soil parameters and enhance prediction of slope failure probability in both its absolute magnitude and variation over time.

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Enhancing Failure Probability Estimation for a Site-Specific Slope by Considering Its Survival Records from Past Rainfall Events

Fiber-reinforcement has been proven to be an effective technique for prevention of shallow failures on the slope face and for repair of existing slope failures. An appealing application for fiber-reinforced soil is the stabilization of infinite slopes. In this study, a reliability-based analysis is conducted to recommend a set of safety factors for practical design scenarios of fiber-reinforced frictional infinite slope in presence of various sources of uncertainty. Uncertainties entail the model uncertainty inherent in the prediction of the internal friction angle of the fiber-reinforced sand and the conventional uncertainties in the input parameters (internal friction angle of the unreinforced sand, unit weight of sand, and water level). Design charts are developed for an illustrative reinforcement scheme to allow the designer to select the suitable slope angle in function of the internal friction angle of the unreinforced sand given target reliability requirements.

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Reliability-based design of infinite frictional slopes reinforced by inclusion of fibers

**Abstract Text**
Detailed hydrological floodplain studies and modeling of flows in the vicinity of hydraulic structures require precise definition of channel topographies. In recent years, LiDAR datasets became commonly available nationwide in the United States thanks to the USGS 3DEP program. However, bathymetric surveys are usually needed for hydraulic studies involving deeper flows since conventional LiDAR measurements do not penetrate water. Additionally, often the LiDAR data sets collected prior to flood events do not represent the existing terrain. In this paper, a hybrid terrain measurement methodology using LiDAR, drone photogrammetry, sonar transducer, real-time kinematic GPS, and total stations to perform ground and underwater terrain mapping is presented. This methodology was successfully used conducting 1-, 2-, and 3-Dimensional hydraulic modeling in numerous state-wide bridge scour studies in Colorado.  The methodology takes advantage of various measurement techniques in assembling accurate topography in a time-efficient and practical manner. The drone photography coupled with  proper ground control points is used in providing detailed and precise survey results near the points of interest to supplement LiDAR data, if available. For bathymetric mapping, a floating continuous data acquisition system  is developed attached to an ultrasonic sonar transducer. A survey prism attached to the floating device allows the location of the equipment can be tracked very accurately with a robotic total station while being towed by a motorized vessel. The hybrid terrain generated using various layers of data sets can then be used for detailed hydraulic simulations such as 2-dimension or 3-dimension hydraulic modeling. Additional data sets using virtual reality photogrammetry are also used to supplement the hybrid terrain for design visualization and various roughness and loss coefficient selection.



Hybrid Channel Geometry Measurements for Hydraulic Studies (Room 322, Monday June 26th, 10:30am-12:00pm)

Traditionally, variations of Proctor compaction method by means of an Impact Hammer have been used for the fabrication of cement treated specimens in the laboratory. There are several systematic errors and practical concerns associated with compacting cement treated aggregate base materials in multiple layers in cylindrical rigid molds. Issues pertaining to the quality, uniformity, and internal structure of laboratory prepared samples greatly influence the reliability of data and confidence in the material properties for the analysis and design of transportation infrastructure. Therefore, this study was designed to investigate the influence of compaction techniques on the pore-structure distribution, as well as tensile and compressive strength properties of cement treated materials. The experiment design incorporated cement treated virgin aggregates and reclaimed materials to better understand the interactions between different aggregate sources, cement contents, and compaction methods on the mechanical behavior of cement stabilized base materials. X-ray Computed Tomography results revealed the superiority of the gyratory compactor to achieve uniform porosity distributions in orthogonal directions. The mitigation of boundary effects in gyratory compacted specimens resulted in superior compressive and tensile strength performance compared to specimens compacted using impact and vibration methods. The outcome of this research can be instrumental in the pavement design industry for the refinement of specimen production procedures for improved mixture design of cement stabilized base layers.

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Investigation of the Influence of Laboratory Compaction Methods on the Micro-Structure and Compressive Strength Properties of Cement Stabilized Materials

This paper investigates the effects of internal curing on the service life and consequently life cycle cost and environmental footprints of concert pavements. Literature studies indicate that internal curing enhances the durability of concrete through addressing shrinkage cracking, in addition to improving strength and integrity of the interfacial transition zone due to better hydration. Presented investigation relies on an experimental approach and examines transport properties of internally cured mixtures using fine lightweight expanded shale, clay and slate aggregates according to ASTM standards. The methodology utilizes these properties and incorporates a simulation of the performance of concrete using Life 365™ following fib Bulletin 34 procedures. Results include a comparative analysis of the performance of internally cured mixture in various climate zones per FHWA. Conclusions indicate the quantitative influence of fine lightweight aggregate on the extension of service life and reduction of life cycle cost, as well as environmental footprints, such as energy and emissions.

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Service Life Prediction of Internally Cured Concrete Pavements using Transport Properties

The Virginia Department of Transportation (VDOT) is currently taking steps toward incorporating performance-based criteria into asphalt mixture design in an effort to build more durable and longer-lasting pavements. As part of this effort, the indirect tensile (IDT) is selected as a test method for evaluating the cracking susceptibility of asphalt mixtures. VDOT also requires evaluating the susceptibility of asphalt mixtures against moisture-induced damage by means of AASHTO T283 standard. Apart from the difference in data analysis methodology, specimen thickness remains the major difference between the two tests. The IDT cracking test procedure specifies a specimen thickness of 62 mm, meanwhile the AASHTO T283 procedure requires a 95-mm thickness for a 150-mm diameter specimen. The objective of this study was to investigate if the test procedure in AASHTO T283 can be modified (i.e. reducing the specimen thickness) and only one test can be performed for assessing the resistance of asphalt mixtures to moisture and crack-related damage at the same time. In addition, several numerical indices from the test including cracking tolerance index (CT index) were evaluated to quantify the cracking and moisture susceptibility of asphalt mixtures. The test results from six plant-produced asphalt mixtures indicated that the moisture damage test as per AASHTO T283 can be performed on asphalt concrete specimens with a thickness of 62 mm and a diameter of 150 mm. The test results also indicated that the CT index was unable to provide the expected performance trends for asphalt mixtures subjected to a freeze-thaw cycle.

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Presentations