MTTI recently hosted an informational meeting regarding two FRA BAA’s currently open for concept papers and proposals.
This year, there are 2 BAA’s:
BAA #1 is a general announcement with a listing for multiple research topics organized by FRA’s four research areas of Track, Rolling Stock and Equipment, Train Control, and Human Factors. This BAA requires a 2 step proposal process with submission of a concept paper to the FRA, who then extends an invitation for a full proposal submission if concept paper is selected.
BAA #2 is an announcement focused on Intelligent Railroad System Research, and is restricted to university and university-led teams as qualifying applicants. This BAA requires a full proposal submission. No concept paper is necessary.
For more information, including program guidelines, please visit the FRA BAA website.
For MTTI meeting recording and informational slides, please visit here.
The Michigan Tech Transportation Institute (MTTI) recently held a general meeting for the campus transportation community and its MTTI membership titled: Beyond Traffic: Growing Transportation Research @ Tech.
A networking reception and poster display opened the evening session before MTTI Director Pasi Lautala provided information to the group on MTTI resources available, plus upcoming funding opportunities. Executive Committee member Jake Hiller (CEE) delivered an introduction to the National Road Research Alliance (NRRA), in which MTTI has been a long time partner.
The National Road Research Alliance (NRRA), a pooled fund that focuses on solving problems for local, regional and national research, tech transfer and implementation needs, posted a profile of the Michigan Tech Transportation Institute (MTTI) in their March 2018 newsletter.
MTTI has long been a partner of the NRRA and will be hosting their Director Glenn Engstrom at a meeting open to all campus researchers on Tuesday, April 3 from 5-7:30 p.m. in the MUB alumni lounge. NRRA Newsletter
Open to all researchers on campus, join the Michigan Tech Transportation Institute (MTTI) to discuss transportation research opportunities on April 3, 2018 in the MUB Alumni Lounge. Find out how MTTI works and where you fit into the picture.
A reception and dinner will be hosted along with an address by keynote speaker Glenn Engstrom from the Minnesota Department of Transportation and the National Road Research Alliance (NRRA), a pooled fund that focuses on solving problems for local, regional and national research, tech transfer and implementation needs. MTTI partners with both MnDOT and the NRRA.
A reception will be held at 5:00 pm followed by dinner and keynote address.
Facilitated by and held on the grounds of the Keweenaw Research Center, the SAE International Clean Snowmobile Challenge (CSC) program is an engineering design competition for undergraduate and graduate students. The program provides participants with the opportunity to enhance their engineering design and project management skills by applying learned classroom theories in a challenging competition that tests their designs to reengineer an existing snowmobile to reduce emissions and noise. Participants’ modified snowmobiles will compete in a variety of events including emissions, noise, fuel economy/endurance, acceleration, handling, static display, cold start and design.
MTTI supported the 2018 Get WISE (Women in Science and Engineering) program where 225 local middle school girls visited Michigan Tech’s campus to participate in three STEM activities. This year the activities included building a bionic hand, participating in a space lander engineering challenge, and building flashlights.
MTTI Director Pasi Lautala recently facilitated the discussion at the 2018 Green Film Series on Michigan Tech’s campus for the film “Freightened: The Real Price of Shipping Goods” which investigates the world-wide freight shipping industry. MTTI also financially sponsored the event.
Task 1: Log and non-log product movement data collection
This study will use actual log movement data (both by truck and by train) by the participating forest products companies, as well as train routes and schedules from CN (and potentially E&LS) as a backbone for the spatial simulation model of the region. The main activities of the task 1 include log and non-log movement data collection. For the non-log movements, the main emphasis is in collecting data on origin-destination (O-D) pairs, both from the forest products companies and from the results of NRTC study.
Task 2: Development of GIS network and yard/siding/mill constraints
We are expecting the GIS (Geographical Information System) maps of truck/rail movements to be the first main outputs from our study. These electronic maps developed based on the log movement data will show not only the actual locations and capacities of yards and sidings, but the transportation infrastructure of study area.
Task 3: Log /non-log movement data reduction/cleaning (as necessary) and conversion to a common format
In this task, we will clean up and convert the log movements to a common format. We will identify the log volumes through each O-D pair, including volumes through rail sidings/yards. Data collected in the previous tasks will be collated and organized with the development of commodity flows. Commodity flows will provide the movements of goods (log) in the study area and will be the basic dataset for average daily/monthly O-D matrix of log movements.
Task 4: Development of operational constraints (rail) and operational model
The studies on the freight mode choice, especially the competition between truck and rail are becoming critical to improve the efficiency of freight transportation system. In this task, we will investigate observed/unobserved factors influencing freight mode choice, including truck and rail. The average daily/monthly O-D matrix of log movements in the previous task will utilize to develop log freight mode choice model.
Task 5: Development of “non-log” product movement graphics, data tables and maps
In the same way as in Task 2 and 3 for a log product, this task identifies the “non-log” volume through each O-D pair and develops movement tables based on data collected in previous Task 1. The task includes generating volume matrices and GIS maps on the movements to identify opportunities.
Task 6: 1st simulation runs and development of results
In this task, we will develop the first simulation model that seeks to optimize log transportation considering the operational constraints of rail. This model will analyze log movements (from several companies/mills) by rail and truck, and look at where and how opportunities may be created to improve the business case for CN or a short line operator to provide cost effective service. One potential example is identifying locations where larger shipment sizes can be concentrated at once. Figure 1 presents the framework of the spatial model, using all processes from Tasks 1 to 5 as its main components.
Task 7: Industry/sponsor review of results
Progress report will be provided to get industry/sponsor reviews of the optimization and non-log movement results. This report will include the results of five tasks in the phase 1 (from Task 1 to Task 5) as well as the results derived from the first operational simulation model of task 6.
Task 8: 2nd simulation runs and analysis of additional logistics considerations.
We will run the second simulation and analyze on the car demand, effects on log trucks, opportunities for reduced peaking and consolidated rail yards. The comments/opinions from the first review will be reflected in the second simulation runs.
Task 9: Industry sponsor/review of results and final report
Dr. Pasi Lautala will provide coordination of the project and data collection from industry stakeholders.
Dr. Kuilin Zhang will lead the operational constraint and model development for log transportation model. He will also lead the analytical tasks related to the model, supported by the graduate research assistants.
Dr. Zhang is an advisor for the project on freight modeling and OD elimination using traffic counts. This project develops a statewide passenger and freight travel demand model for Michigan, including data assessment, model specification development, model development, model calibration and validation, forecasting future years, model documentation, and training.