When: June 8-July 17, 2020
Location: PNW Hammond Campus
Each participant will receive a stipend of $6,150 for completing the 6-week summer research program and full academic year activities.
This RET program at Purdue University Northwest consists of a 6-week summer research program and full-academic year activities focus on using simulation and visualization technologies in “smart” manufacturing to increase energy efficiency, optimize production, predict mechanical failures, and improve safety and product quality. The goal is to enhance STEM education and stimulate high school and community college students’ STEM interest through partnership with participant teachers, university mentors, and industry engineers using simulation and visualization technologies for innovative industrial solutions and model-based manufacturing.
This program is sponsored by the National Science Foundation.
Engineering, technology, science and math teachers from high schools or community colleges are eligible to apply. Potential candidates can be teachers who have teaching experiences in one or more of the following courses:
Chemistry I & II
Civil Engineering & Architecture
Computer in Design & Production
Engineering Design & Development
Introduction to Design
Introduction to Engineering
Introduction to Manufacturing
Physics I & II
Principles in Engineering
Project Lead the Way
The participants are expected to dedicated 40 hours per week working with faculty mentors, graduate students, and industry engineers in one of the five projects described in the next section.
The participants are expected to write a research report and develop a curricular module at the end of the program.
The participants are expected to participate in full-academic year activities after the 6-week summer program.
Project 1: Performance Analysis of Natural Gas Combustion in a Blast Furnace
Project Description/Objective: Investigate the Effects of Natural Gas (NG) Injection in a Blast Furnace
A blast furnace is a large vertical chemical reactor utilized in the conversion of iron ore to liquid iron during steelmaking. Operating a blast furnace is both energy- and cost-intensive. Since NG prices have decreased in recent years, it has become an attractive alternative fuel for increasing energy efficiency and productivity. However, using NG greatly impacts several furnace operational parameters. Computational fluid dynamics (CFD) has been applied to simulate NG combustion in a blast furnace, but further research is needed to analyze NG performance. In collaboration with steelmaking industry partners, CIVS and SMSVC have already developed a detailed blast furnace geometry and CFD model which will be used by teachers in this research.
Project 2: Energy Efficiency of a Steel Slab Reheat Furnace
Project Description/Objective: Investigate the Effects of Operating Conditions on the Energy Efficiency of a Slab Reheat Furnace
Reheat furnaces are commonly used in the steel rolling process, which is a critical part of the production of steel plates and coils. These furnaces impact both the quality and cost of the final steel product. During furnace operations, non-uniform temperature distributions create large stresses during the rolling process, which can result in an industrial accident. CIVS has created a CFD model for the slab reheat furnace to examine furnace operations. The model will be able to predict the heating process in the slab and give details about the temperature distribution in a three dimensional space with the objective of optimizing the design to make it cost-effective.
Project 3: Structural and Fatigue Analysis of an Overhead Crane in a Steel Plant
Project Description/Objective: Investigate the Effects of Operating Conditions on the Stress and Life-span of an Overhead Crane
In the steel industry, the overhead crane is used in processes that require heavy lifting. An overhead crane consists of traveling bridge-like girders spanning two parallel runways. The lifting component of the crane, known as the hoist, travels along the bridge with a trolley. As one of the most important components of the steel factory, large overhead cranes are capital Intensive units that typically remain in service for many decades. Currently, there are many cranes approaching the end of their design life, which is a time when there is a frequent need for repair and maintenance, increasing costs. To ensure continued operations, many large-scale cranes undergo scheduled maintenance and repairs. The application of modern computational methods, such as finite element analysis (FEA), can enhance repair and maintenance by helping to identify structurally critical areas within an equipment assembly. Working with steelmakers, CIVS has developed an overhead crane geometry and FEA simulation, and general methodology that can be applied to existing and/or proposed large-scale overhead cranes. The main objective of this project is to structurally analyze a large-scale overhead charging crane in a steel melt shop, using numerical simulation and visualization.
Project 4: Optimization of Rolling Mill Production Line Throughput
Project Description/Objective: Investigate the Effects of Operating Conditions on the Throughput of a Rolling Mill Production Line
Many systems used in shaping and treating of steel require prior simulation to determine proper process control. Production lines such as those in rolling mills rely on sensors and process-control systems to measure and regulate the speed and thickness of steel as it is reduced prior to coiling. Operating conditions of production lines are constantly being adjusted based on scheduling, desired steel properties, inventory, and limitations of the equipment. These systems use sensors and associated control systems to adjust process parameters, such as speed, gap thicknesses, and working pressures of the line equipment. The values of these variables require careful selection to ensure high product quality and throughput, and issues such as equipment life or possible failure via overstress must be considered. Optimizing throughput while maintaining process variables within an acceptable envelope is a continuous goal in the industry. With computer simulation, a production line can be modeled and run at different conditions to compare results and provide a basis for optimizing throughput. A steel industry rolling mill will be modeled and used to predict real operating conditions. A parametric study will be conducted to determine an optimal configuration to contend with a variety of typical operating conditions and scenarios encountered in the steel industry.
Project 5: Investigation of Cause and Prevention of Incidents through Safety Training
Project Description/Objective: Investigate the Cause of Incidents in a Particular Safety Area in the Steel Industry and Determine Preventive Measures Through Safety Training
While modern steelmaking has advanced significantly, the industry still involves hazardous processes. Fall protection requires thorough understanding of the hazard and correct use of safety equipment. Selecting incorrect or damaged fall-protection equipment, or choosing incorrect anchor points, can result in fatality. A web-based interactive 3D simulator was created to provide an engaging experience for trainees to accompany traditional training materials. The main objective of this project is to research the most important elements of a safety simulator for steel industry training and design a learning scenario in coordination with steel industry safety professionals.
The application must be submitted online by 5 PM on February 14, 2020. The application should include:
1. a resume showing the courses the applicant teaches
2. a letter of support from the high school principal or chair of the department, and
3. a personal statement/essay (up to two pages) describing teaching philosophy; which of the 5 projects are they interested in; and how they plan to apply the research experience to the classroom.
Send all three required documents to email@example.com to apply.
For more information, please contact:
Chenn Zhou, Ph.D.
Professor of Mechanical Engineering, Director of the Center for Innovation through Visualization and Simulation (CIVS)
Chien-Chung Chen, Ph.D., P.E.
Associate Professor of Civil Engineering
Don Gray, Ph.D.
Associate Professor of Electrical Engineering
Purdue University Northwest (PNW)
School of Engineering at PNW
PNW Center for Innovation through Visualization and Simulation (CIVS)
National Science Foundation (NSF)
For more information and full details, go to https://academics.pnw.edu/engineering/research-experience-for-teachers/