Project1_FINALnonames

Project1_FINALnonames - ENU 4134 Project#1 Fall 2011 – D...

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Unformatted text preview: ENU 4134 Project #1, Fall 2011 – D. Schubring 1 Analysis of Real Pressure Drop Data DUE: Friday, October 7 ALLOWED COLLABORATION: You may collaborate and divide labor within your group however you choose. One report is required per group. No collaboration outside of your group is permitted. Most industrial systems use two-phase, one-component flow (steam-water, refrigerants), but many experiments use two-component flow to keep down costs and separate the fluid dynamic effects from those rooted in heat transfer. A databank of two-component vertical flow data has been provided on the website. These are low-pressure air-water annular (or wispy-annular) flows in a 23.4 mm tube and in a 31.8 mm pipe. Pressures and mass flow rates are provided; you should assume a constant temperature of 10 ◦ C. In addition, total pressure drop data are provided for all flows, along with estimates of film thickness for selected flow conditions. In this assignment, you will look at modeling of pressure drop for annular flow, including the film roughness concept that uses film thickness measurements to estimate pressure drop. As part of an in-class example, a single flow condition will be studied (with solutions provided using several of these correlations) to ensure that you implement the models correctly. 1 Assignment 1. Apply the HEM, Lockhart-Martinelli, and M¨uller-Steinhagen and Heck models to the data- bank provided on the website. Note that only a subset of data includes film thickness mea- surements. (As discussed in class, this is a more challenging measurement than is pressure drop.) For Lockhart-Martinelli and HEM, use the void fraction from each correlation. For M¨uller-Steinhagen and Heck, use α from the Lockhart-Martinelli model. Ignore the acceleration term ( Ma gas < . 3 – ignore dα/dz term as well). For the HEM and LM, assume the McAdams single-phase friction factor. For the HEM, assume μ TP = μ l . You should report mean errors, mean absolute errors (MAE), and root mean square errors (RMS) for each correlation. Consider dp/dz as the metric of comparison. Using n FC as the number of flow conditions considered, dp/dz corr as the result of your correlation, and dp/dz exp as the experimental data, these are defined by: MeanError = 1 n FC X FC dp/dz corr- dp/dz exp dp/dz exp × 100% (1) MAE = 1 n FC X FC dp/dz corr- dp/dz exp dp/dz exp × 100% (2) RMS = v u u t 1 n FC X FC dp/dz corr- dp/dz exp dp/dz exp × 100% !...
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Project1_FINALnonames - ENU 4134 Project#1 Fall 2011 – D...

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