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A seven-span concrete bridge was constructed over the Wabash River in Lafayette, Indiana. The bridge, which has a total length of 305 m (1,000 ft) and typical spans of 46 m (152 ft), consists of six hammerhead bridge piers in the center and two end bents supported on open-ended and closed-ended pipe piles, respectively. According to the structural bridge design, the dead load carried by each pile ranges from 1,014 kN (228 kips) to 1,495 kN (336 kips), whereas the live load ranges from 512 kN (115 kips) to 1,188 kN (267 kips), depending on the location of the piles. A closed-ended and an open-ended test piles (with the same, or almost the same diameter for the production pile) were instrumented at the Bowen Laboratory, transported to the construction site, then driven into the ground, and statically load tested. The report presents in detail the results of the site investigation, pile instrumentation procedure, pile driving records and interpretations of the static load test results.

Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during construction projects drive up construction costs for INDOT and cause unexpected delays. To alleviate these problems and minimize change order costs associated with having unexpectedly high soil moisture conditions at the time of construction, a methodology was developed to allow INDOT engineers to estimate in situ soil moisture conditions early in the design phases of projects. The soil moisture prediction methodology is based on results from soil moisture flow simulations carried out using the HYDRUS-1D software. The soil moisture flow simulations in HYDRUS-1D required i) weather data, ii) groundwater table data and iii) in situ soil hydraulic (saturated and unsaturated) and index property data. These data were collected for all the counties in Indiana from five different sources: i) Indiana Department of Transportation (INDOT), ii) Indiana Geological Survey (IGS), iii) United States Department of Agriculture’s (USDA’s) Soil Survey Geographic (SSURGO), iv) the Department of Natural Resources (DNR) and v) Indiana State Climate Office (Iclimate). The results obtained from initial soil moisture flow simulations were first validated using field measurements from six IGS test sites located in Indiana where soil property data and continuous in situ soil moisture measurements at multiple depths were available for up to 3 years (2011-2014). Good agreement was observed between moisture content measurements and predictions. After validation of the developed moisture prediction methodology, ten-year moisture content simulations using HYDRUS 1D were performed for typical profiles in each county in Indiana using as input weather data from the iclimate database, groundwater data from DNR database and soil properties from IGS, INDOT a

Soil property values for use in geotechnical design are often estimated from a limited number of in situ or laboratory tests. The uncertainty involved in estimating soil properties from a limited number of tests can be addressed by quantifying the variability within individual soundings and of the collection of soundings at a site. It has been proposed that factors of safety or resistance factors used in design be linked to site variability. Site variability can be assessed by studying the correlation structure of in situ test data. The cone penetration test (CPT), which is a reliable and widely-accepted in situ test, can be used for this purpose. Soil behavior type (SBT) charts are often used to obtain the subsurface soil profile from CPT parameters such as the cone resistance and the sleeve friction. A soil profile generation algorithm was developed in this research to generate a soil profile from an individual CPT sounding using two modified SBT charts. Soils are variable in both the vertical and horizontal directions. A vertical variability index (VVI) was defined to quantify variability in a CPT sounding. The average of the VVIs for all CPT soundings performed at a site is the site VVI. A site horizontal variability index (site HVI) was also developed, based on cross-correlation between cone resistances, the cone resistance trend differences and the spacing between every pair of CPTs considered, to quantify the soil variability of a site in the horizontal direction. A site variability rating (SVR) system, integrating the vertical and horizontal site variability, was developed to assess the overall site variability. Depending on the SBT chart selected, the soil profile generated using the soil profile generation algorithm may be slightly different; however, the SBT chart effect on the variability indices that compose the SVR index is small. Close agreement was found between the SVRs obtained using the two SBT charts selected for this research. In order to illust

The Dynamic Cone Penetrometer (DCP) is a device that is used for the estimation of in situ compaction quality of constructed subgrades and embankments. It is a relatively inexpensive, light-weight and easy to use device that measures the dynamic penetration resistance of the compacted soil, from which an estimate of soil strength and stiffness characteristics can be made. Owing to its ease of use, many DOTs in the U.S. have employed the DCP in their compaction quality control procedures, and over the past few decades, extensive research has been carried out on the development of correlations between the results of the DCP test and the results of strength and stiffness tests performed on compacted soils (e.g., California bearing ratio, and resilient modulus) The objectives of this research are to refine DCP-based quality assurance and quality control correlations for compaction quality control developed by previous research studies carried out at Purdue for the Indiana Department of Transportation, especially focusing on i) grouping of the soils based on their mechanical response to the DCP loading, and ii) limiting the in situ moisture range of the soils used for development of correlations within -2% of the optimum moisture content of the tested soil. The factors outlined above are studied, and in particular, soil grouping is examined critically. The AASHTO (‘A-based’) classification employed previously for classification of soils is replaced by a new classification criteria specifically developed for the DCP test. Soils are grouped into one of the two categories of coarse-grained or fine-grained soils on the basis of the size of the dominant particle in the soil. The criteria developed for the classification of soil into one of these two categories is based on index properties of the soil, such as the standard Proctor maximum dry density, optimum moisture content, plasticity index (PI) and fines content (percentage passing0.075 mm sieve size). For the purpose of r

SPR-3811, Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during construction projects drive up construction costs for INDOT and cause unexpected delays. To alleviate these problems and minimize change order costs associated with having unexpectedly high soil moisture conditions at the time of construction, a methodology was developed to allow INDOT engineers to estimate in situ soil moisture conditions early in the design phases of projects. The soil moisture prediction methodology is based on results from soil moisture flow simulations carried out using the HYDRUS-1D software. The soil moisture flow simulations in HYDRUS-1D required i) weather data, ii) groundwater table data and iii) in situ soil hydraulic (saturated and unsaturated) and index property data. These data were collected for all the counties in Indiana from five different sources: i) Indiana Department of Transportation (INDOT), ii) Indiana Geological Survey (IGS), iii) United States Department of Agriculture’s (USDA’s) Soil Survey Geographic (SSURGO), iv) the Department of Natural Resources (DNR) and v) Indiana State Climate Office (Iclimate). The results obtained from initial soil moisture flow simulations were first validated using field measurements from six IGS test sites located in Indiana where soil property data and continuous in situ soil moisture measurements at multiple depths were available for up to 3 years (2011-2014). Good agreement was observed between moisture content measurements and predictions. After validation of the developed moisture prediction methodology, ten-year moisture content simulations using HYDRUS 1D were performed for typical profiles in each county in Indiana using as input weather data from the iclimate database, groundwater data from DNR database and soil properties from IGS, INDOT a

SPR-3408, Soil property values for use in geotechnical design are often estimated from a limited number of in situ or laboratory tests. The, uncertainty involved in estimating soil properties from a limited number of tests can be addressed by quantifying the variability within, individual soundings and of the collection of soundings at a site. It has been proposed that factors of safety or resistance factors used in, design be linked to site variability. Site variability can be assessed by studying the correlation structure of in situ test data. The cone, penetration test (CPT), which is a reliable and widely‐accepted in situ test, can be used for this purpose. Soil behavior type (SBT) charts, are often used to obtain the subsurface soil profile from CPT parameters such as the cone resistance and the sleeve friction. A soil, profile generation algorithm was developed in this research to generate a soil profile from an individual CPT sounding using two, modified SBT charts. Soils are variable in both the vertical and horizontal directions. A vertical variability index (VVI) was defined to, quantify variability in a CPT sounding. The average of the VVIs for all CPT soundings performed at a site is the site VVI. A site horizontal, variability index (site HVI) was also developed, based on cross‐correlation between cone resistances, the cone resistance trend, differences and the spacing between every pair of CPTs considered, to quantify the soil variability of a site in the horizontal direction. A, site variability rating (SVR) system, integrating the vertical and horizontal site variability, was developed to assess the overall site, variability. Depending on the SBT chart selected, the soil profile generated using the soil profile generation algorithm may be slightly, different; however, the SBT chart effect on the variability indices that compose the SVR index is small. Close agreement was found, between the SVRs obtained using the two SBT charts selected for this research. In order to illustrate the use of the algorithms, for VVI and HVI calculations and SVR of sites, CPTs from across the state of Indiana were analyzed. CPT data were obtained from, Purdue's own database, INDOT’s data repository and the U.S. Geological Survey (USGS) website. Site variability is calculated for specific, depths of interest. For example, that depth of interest will be shallower for shallow foundations than for deep foundations. Site, variability rating maps (SVR maps) for various depths of interest were constructed for the state of Indiana, illustrating the potential use, of the site variability assessment methodology. An optimal sounding spacing calculation methodology was also developed to make the, site investigation process more efficient, cost‐effective and reliable.