Experiential Capstone Program
The Chemical Engineering (ChE) Professional M.S. Program's (PMP) Experiential Capstone Program enable students to apply knowledge acquired in the PMP curriculum to a specific application of relevant importance. The project integrates science, engineering, design, and economics to achieve specific goals, such as the development of innovative technology, refinement of new analytical tools, or improved understanding of material properties, synthesis, and processing. Students have the opportunity to select industrial based or academic based projects led under the guidance of our industrial partners or the guidance of ChE faculty, respectively. Industry projects typically consist of teams in which a group of 2-4 students work with a mentor from an industrial partner, while students working on academic projects join the laboratory of a Purdue Chemical Engineering faculty member on individual or team based projects. Examples of past projects are listed below.
Product Development Engineering
Students will primarily assist in the implementation of design input requirements, design verification and validation activities, risk assessments, and assisting in scale up or transfer to manufacturing activities for a variety of advanced biomaterial platforms. Additionally, students will utilize equipment qualification and process validation methods in order to source test, qualify, and validate a tray sealer.
SO2 Catalytic Oxidation
Using Aspen plus as the model simulator, students are to create a kinetic model for the oxidation of SO2. Based on the results of the simulations, students are to report which conditions give the most promising formulas.
Parameter Estimation Initial Guess Generation
Modeling experimental data can prove to be a difficult task depending on the complexity of the models. This can make it challenging to determine to pertinent kinetic parameters. A way to circumvent this issue is by using first guess parameters with the aid of a search algorithms. Students within this project are to evaluate several algorithms to determine model parameters and decrease the chance of failure for the model.
Model-based Experimental Design for Model Discrimination
When designing a model from experimental data, there are occurrences where more than one model is able to explain observations. In order to avoid having multiple models, researchers carefully conduct new experiments at different conditions to determine which models still fit the new set of data. The objective of this project is to develop a systematic mechanism that would help eliminate ambiguity in the model selection process by eliminating inappropriate candidates.
A Systems Engineering Approach for Managing Changes in Chemical Process R&D Labs
The Market Assessment and Techno-Economic Evaluation of Polymer-based 3D Printing Processes
Students are review the various polymer-based 3D printing technologies and determine the pros and cons and how they fare against current manufacturing technologies. They will also assess the market size and determine what is the projected growth of this niches market.
Acoustically Induced Vibration of Piping Systems
High flow rates and high-pressure letdown systems can generate vibrations in piping systems that eventually lead to fatigue. Research has been conducted to determine the sound power level (PWL) caused by this phenomenon. This project is centered on researching investigations on this matter and incident reports caused by this. Students are also to make recommendations to measure PWL’s in various phases.
Identification and Validation of a Surfactant Formulation for Chemical Enhanced Oil Recovery in the Illinois Basin
The Illinois basin possess oil within its sandstone and carbonate reserves. Significant time has been invested to understanding the physical characteristics of the mineralogy in order to employ surfactants to recover oil. Students will research an existing library of commercial surfactants to determine optimum formulations and test them within a laboratory setting to aid in oil recovery.
Improved Modeling of LNG Fire Jets
Overly conservative models can cause expensive and cost ineffective decisions to be made. One area where calculations can be improved is the modeling of liquid methane or natural gas (LNG) jet fire modeling. By using a liquified petroleum gas (LPG) model researchers can hope to more accurately calculate safety data and reduce costs. Students are too review these LPG and LNG jet fire models and make appropriate calculations based on the project mentor’s requirements.
Quantification of Toxicity Effects of H2S Ingress into Buildings / Temporary Refuge
H2S is prevalent in sour fields and its potent toxicity has prevented project fruition due its high cost in mitigating this danger. The goal of this project is to develop that can calculate time dependent concentrations due to accumulation in temporary refuges and the effects of prolonged exposure in these areas as well.
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