Main-Channel Slopes of Selected Streams in Iowa for Estimation of Flood-Frequency Discharges, November 2004

This report describes a statewide study conducted to develop main-channel slope (MCS) curves for 138 selected streams in Iowa with drainage areas greater than 100 square miles. MCS values determined from the curves can be used in regression equations for estimating flood frequency discharges. Multi-variable regression equations previously developed for two of the three hydrologic regions defined for Iowa require the measurement of MCS. Main-channel slope is a difficult measurement to obtain for large streams using 1:24,000-scale topographic maps. The curves developed in this report provide a simplified method for determining MCS values for sites located along large streams in Iowa within hydrologic Regions 2 and 3. The curves were developed using MCS values quantified for 2,058 selected sites along 138 selected streams in Iowa. A geographic information system (GIS) technique and 1:24,000-scale topographic data were used to quantify MCS values for the stream sites. The sites were selected at about 5-mile intervals along the streams. River miles were quantified for each stream site using a GIS program. Data points for river-mile and MCS values were plotted and a best-fit curve was developed for each stream. An adjustment was applied to all 138 curves to compensate for differences in MCS values between manual measurements and GIS quantification. The multi-variable equations for Regions 2 and 3 were developed using manual measurements of MCS. A comparison of manual measurements and GIS quantification of MCS indicates that manual measurements typically produce greater values of MCS compared to GIS quantification. Median differences between manual measurements and GIS quantification of MCS are 14.8 and 17.7 percent for Regions 2 and 3, respectively. Comparisons of percentage differences between flood-frequency discharges calculated using MCS values of manual measurements and GIS quantification indicate that use of GIS values of MCS for Region 3 substantially underestimate flood discharges. Mean and median percentage differences for 2- to 500-year recurrence-interval flood discharges ranged from 5.0 to 5.3 and 4.3 to 4.5 percent, respectively, for Region 2 and ranged from 18.3 to 27.1 and 12.3 to 17.3 percent for Region 3. The MCS curves developed from GIS quantification were adjusted by 14.8 percent for streams located in Region 2 and by 17.7 percent for streams located in Region 3. Comparisons of percentage differences between flood discharges calculated using MCS values of manual measurements and adjusted-GIS quantification for Regions 2 and 3 indicate that the flood-discharge estimates are comparable. For Region 2, mean percentage differences for 2- to 500-year recurrence-interval flood discharges ranged between 0.6 and 0.8 percent and median differences were 0.0 percent. For Region 3, mean and median differences ranged between 5.4 to 8.4 and 0.0 to 0.3 percent, respectively. A list of selected stream sites presented with each curve provides information about the sites including river miles, drainage areas, the location of U.S. Geological Survey stream flowgage stations, and the location of streams Abstract crossing hydro logic region boundaries or the Des Moines Lobe landforms region boundary. Two examples are presented for determining river-mile and MCS values, and two techniques are presented for computing flood-frequency discharges.

Visibility and Speed Estimation of Iowa State Highway Commission Snowplows, HR-174, 1975

Many accidents involving Iowa snowplows have happened in recent years. This study investigated the influence of time of day, sex of subject, type of snowplow sign and snowplow speed on the criteria of oncoming driver reaction time and his estimate of snowplow speed. Film strips were made of a car passing a snow-Plow under various experimental conditions. These experimental movie strips were viewed in the laboratory by college student drivers who were asked to indicate their reaction time to slow down and to estimate the speed of the snowplow being passed. The generally best sign condition for the snowplow was to have a striped rear sign and a speed-proportional flashing light in addition to the standard rotating beacon on top of the truck. Several recommendations were made.

Highway Work Zone Capacity Estimation Using Field Data from Kansas, TPF-5(081), 2015

Although extensive research has been conducted on urban freeway capacity estimation methods, minimal research has been carried out for rural highway sections, especially sections within work zones. This study attempted to fill that void for rural highways in Kansas, by estimating capacity of rural highway work zones in Kansas. Six work zone locations were selected for data collection and further analysis. An average of six days’ worth of field data was collected, from mid-October 2013 to late November 2013, at each of these work zone sites. Two capacity estimation methods were utilized, including the Maximum Observed 15-minute Flow Rate Method and the Platooning Method divided into 15-minute intervals. The Maximum Observed 15-minute Flow Rate Method provided an average capacity of 1469 passenger cars per hour per lane (pcphpl) with a standard deviation of 141 pcphpl, while the Platooning Method provided a maximum average capacity of 1195 pcphpl and a standard deviation of 28 pcphpl. Based on observed data and analysis carried out in this study, the suggested maximum capacity can be considered as 1500 pcphpl when designing work zones for rural highways in Kansas. This proposed standard value of rural highway work zone capacity could be utilized by engineers and planners so that they can effectively mitigate congestion at or near work zones that would have otherwise occurred due to construction/maintenance.

Wind Loads on Dynamic Message Cabinets and Behavior of Supporting Trusses, TR-612, 2013

Large Dynamic Message Signs (DMSs) have been increasingly used on freeways, expressways and major arterials to better manage the traffic flow by providing accurate and timely information to drivers. Overhead truss structures are typically employed to support those DMSs allowing them to provide wider display to more lanes. In recent years, there is increasing evidence that the truss structures supporting these large and heavy signs are subjected to much more complex loadings than are typically accounted for in the codified design procedures. Consequently, some of these structures have required frequent inspections, retrofitting, and even premature replacement. Two manufacturing processes are primarily utilized on truss structures - welding and bolting. Recently, cracks at welding toes were reported for the structures employed in some states. Extremely large loads (e.g., due to high winds) could cause brittle fractures, and cyclic vibration (e.g., due to diurnal variation in temperature or due to oscillations in the wind force induced by vortex shedding behind the DMS) may lead to fatigue damage, as these are two major failures for the metallic material. Wind and strain resulting from temperature changes are the main loads that affect the structures during their lifetime. The American Association of State Highway and Transportation Officials (AASHTO) Specification defines the limit loads in dead load, wind load, ice load, and fatigue design for natural wind gust and truck-induced gust. The objectives of this study are to investigate wind and thermal effects in the bridge type overhead DMS truss structures and improve the current design specifications (e.g., for thermal design). In order to accomplish the objective, it is necessary to study structural behavior and detailed strain-stress of the truss structures caused by wind load on the DMS cabinet and thermal load on the truss supporting the DMS cabinet. The study is divided into two parts. The Computational Fluid Dynamics (CFD) component and part of the structural analysis component of the study were conducted at the University of Iowa while the field study and related structural analysis computations were conducted at the Iowa State University. The CFD simulations were used to determine the air-induced forces (wind loads) on the DMS cabinets and the finite element analysis was used to determine the response of the supporting trusses to these pressure forces. The field observation portion consisted of short-term monitoring of several DMS Cabinet/Trusses and long-term monitoring of one DMS Cabinet/Truss. The short-term monitoring was a single (or two) day event in which several message sign panel/trusses were tested. The long-term monitoring field study extended over several months. Analysis of the data focused on trying to identify important behaviors under both ambient and truck induced winds and the effect of daily temperature changes. Results of the CFD investigation, field experiments and structural analysis of the wind induced forces on the DMS cabinets and their effect on the supporting trusses showed that the passage of trucks cannot be responsible for the problems observed to develop at trusses supporting DMS cabinets. Rather the data pointed toward the important effect of the thermal load induced by cyclic (diurnal) variations of the temperature. Thermal influence is not discussed in the specification, either in limit load or fatigue design. Although the frequency of the thermal load is low, results showed that when temperature range is large the restress range would be significant to the structure, especially near welding areas where stress concentrations may occur. Moreover stress amplitude and range are the primary parameters for brittle fracture and fatigue life estimation. Long-term field monitoring of one of the overhead truss structures in Iowa was used as the research baseline to estimate the effects of diurnal temperature changes to fatigue damage. The evaluation of the collected data is an important approach for understanding the structural behavior and for the advancement of future code provisions. Finite element modeling was developed to estimate the strain and stress magnitudes, which were compared with the field monitoring data. Fatigue life of the truss structures was also estimated based on AASHTO specifications and the numerical modeling. The main conclusion of the study is that thermal induced fatigue damage of the truss structures supporting DMS cabinets is likely a significant contributing cause for the cracks observed to develop at such structures. Other probable causes for fatigue damage not investigated in this study are the cyclic oscillations of the total wind load associated with the vortex shedding behind the DMS cabinet at high wind conditions and fabrication tolerances and induced stresses due to fitting of tube to tube connections.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.