Deicer Scaling Resistance of Concrete Mixtures Containing Slag Cement Phase 2: Evaluation of Different Laboratory Scaling Test Methods, TPF-5(100), 2012

With the use of supplementary cementing materials (SCMs) in concrete mixtures, salt scaling tests such as ASTM C672 have been found to be overly aggressive and do correlate well with field scaling performance. The reasons for this are thought to be because at high replacement levels, SCM mixtures can take longer to set and to develop their properties: neither of these factors is taken into account in the standard laboratory finishing and curing procedures. As a result, these variables were studied as well as a modified scaling test, based on the Quebec BNQ scaling test that had shown promise in other research. The experimental research focused on the evaluation of three scaling resistance tests, including the ASTM C672 test with normal curing as well as an accelerated curing regime used by VDOT for ASTM C1202 rapid chloride permeability tests and now included as an option in ASTM C1202. As well, several variations on the proposed draft ASTM WK9367 deicer scaling resistance test, based on the Quebec Ministry of Transportation BNQ test method, were evaluated for concretes containing varying amounts of slag cement. A total of 16 concrete mixtures were studied using both high alkali cement and low alkali cement, Grade 100 slag and Grade 120 slag with 0, 20, 35 and 50 percent slag replacement by mass of total cementing materials. Vinsol resin was used as the primary air entrainer and Micro Air® was used in two replicate mixes for comparison. Based on the results of this study, a draft alternative test method to ASTM C762 is proposed.

Development of Bridge Load Testing Process for Load Evaluation, TR-445, 2003

Recent reports indicate that of the over 25,000 bridges in Iowa, slightly over 7,000 (29%) are either structurally deficient or functionally obsolete. While many of these bridges may be strengthened or rehabilitated, some simply need to be replaced. Before implementing one of these options, one should consider performing a diagnostic load test on the structure to more accurately assess its load carrying capacity. Frequently, diagnostic load tests reveal strength and serviceability characteristics that exceed the predicted codified parameters. Usually, codified parameters are very conservative in predicting lateral load distribution characteristics and the influence of other structural attributes. As a result, the predicted rating factors are typically conservative. In cases where theoretical calculations show a structural deficiency, it may be very beneficial to apply a "tool" that utilizes a more accurate theoretical model which incorporates field-test data. At a minimum, this approach results in more accurate load ratings and many times results in increased rating factors. Bridge Diagnostics, Inc. (BDI) developed hardware and software that are specially designed for performing bridge ratings based on data obtained from physical testing. To evaluate the BDI system, the research team performed diagnostic load tests on seven "typical" bridge structures: three steel-girder bridges with concrete decks, two concrete slab bridges, and two steel-girder bridges with timber decks. In addition, a steel-girder bridge with a concrete deck previously tested and modeled by BDI was investigated for model verification purposes. The tests were performed by attaching strain transducers on the bridges at critical locations to measure strains resulting from truck loading positioned at various locations on the bridge. The field test results were used to develop and validate analytical rating models. Based on the experimental and analytical results, it was determined that bridge tests could be conducted relatively easy, that accurate models could be generated with the BDI software, and that the load ratings, in general, were greater than the ratings, obtained using the codified LFD Method (according to AASHTO Standard Specifications for Highway Bridges).

Evaluation of Design Flood Frequency Methods for Iowa Streams, TR-533, 2009

The objective of this project was to assess the predictive accuracy of flood frequency estimation for small Iowa streams based on the Rational Method, the NRCS curve number approach, and the Iowa Runoff Chart. The evaluation was based on comparisons of flood frequency estimates at sites with sufficiently long streamgage records in the Midwest, and selected urban sites throughout the United States. The predictive accuracy and systematic biases (under- or over-estimation) of the approaches was evaluated based on forty-six Midwest sites and twenty-one urban sites. The sensitivity of several watershed characteristics such as soil properties, slope, and land use classification was also explored. Recommendations on needed changes or refinements for applications to Iowa streams are made.

Comparisons of Estimates of Annual Exceedance-Probability Discharges for Small Drainage Basins in Iowa, Based on Data through Water Year 2013, TR-678, 2015

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa. Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart. For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013). For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias. An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1–4 from the 1987 single-variable RREs and for flood regions 1–3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.