Estimates of Total Fuel Consumption in Transporting Grain from Iowa to Major Grain-Importing Countries by Alternative Modes and Routes, 1985

This study measured fuel consumption in transporting grain from Iowa origins to Japan and Amsterdam by alternative routes and modes of transport and applied these data to construct equations for fuel consumption from Iowa origins to alternative final destinations. Some of the results are as follows: (1) The metered tractor-trailer truck averaged 186.6 gross ton-miles per gallon and 90.5 net ton-miles per gallon when loaded 50% of total miles. (2) The 1983 fuel consumption of seven trucks taken from company records was 82.4 net ton-miles per gallon at 67.5% loaded miles and 68.6 net ton-miles per gallon at 50% loaded miles. (3) Unit grain trains from Iowa to West Coast ports averaged 437.0 net ton-miles per gallon whereas unit grain trains from Iowa to New Orleans averaged 640.1 net ton-miles per gallon--a 46% advantage for the New Orleans trips. (4) Average barge fuel consumption on the Mississippi River from Iowa to New Orleans export grain elevators was 544.5 net ton-miles per gallon, with a 35% backhaul rate. (5) Ocean vessel net ton-miles per gallon varies widely by size of ship and backhaul percentage. With no backhaul, the average net ton-miles per gallon were as follows: for 30,000 dwt ship, 574.8 net ton-miles per gallon; for 50,000 dwt ship, 701.9; for 70,000 dwt ship, 835.1; and for 100,000 dwt ship, 1,043.4. (6) The most fuel efficient route and modal combination to transport grain from Iowa to Japan depends on the size of ocean vessel, the percentage of backhaul, and the origin of the grain. Alternative routes and modal combinations in shipping grain to Japan are ranked in descending order of fuel efficiencies.

Iowa Motor Vehicle Fuel Reduction Program, 1989

This report documents the results of a three million dollar traffic signal improvement demonstration program, known as the Iowa Motor Vehicle Fuel Reduction Program (the program). The program was funded with the use of oil overcharge funds and administered by the Iowa Departments of Natural Resources and Transportation. The objective of the program was to provide restitution to overcharged motorists by improving the efficiency of traffic signals. More efficient traffic signals reduce fuel consumption, delay, travel time, and automobile pollution while improving traffic safety. The program demonstrated the effectiveness of improving traffic signals and resulted in a 14.20-to-1 benefit-to-cost ratio.

Investigation of the Effect of Speed on the Dynamic Impact Factor for Bridges with Different Entrance Conditions, 2016

The dynamic interaction of vehicles and bridges results in live loads being induced into bridges that are greater than the vehicle’s static weight. To limit this dynamic effect, the Iowa Department of Transportation (DOT) currently requires that permitted trucks slow to five miles per hour and span the roadway centerline when crossing bridges. However, this practice has other negative consequences such as the potential for crashes, impracticality for bridges with high traffic volumes, and higher fuel consumption. The main objective of this work was to provide information and guidance on the allowable speeds for permitted vehicles and loads on bridges .A field test program was implemented on five bridges (i.e., two steel girder bridges, two pre-stressed concrete girder bridges, and one concrete slab bridge) to investigate the dynamic response of bridges due to vehicle loadings. The important factors taken into account during the field tests included vehicle speed, entrance conditions, vehicle characteristics (i.e., empty dump truck, full dump truck, and semi-truck), and bridge geometric characteristics (i.e., long span and short span). Three entrance conditions were used: As-is and also Level 1 and Level 2, which simulated rough entrance conditions with a fabricated ramp placed 10 feet from the joint between the bridge end and approach slab and directly next to the joint, respectively. The researchers analyzed and utilized the field data to derive the dynamic impact factors (DIFs) for all gauges installed on each bridge under the different loading scenarios.