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About dudleybenton

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  1. You misunderstand the principle. Whether some working fluid is hot or cold compared to what humans consider normal atmospheric conditions isn't what determines whether or not a device is efficient. When I taught thermodynamics at university, I would always give a test question regarding a cup of coffee cooling to room temperature or a can of beer warming to room temperature. Both generate entropy (dS>0). I work out this example in my book, Thermodynamics. There are several reasons we build power plants using steam instead of air as the working fluid. The latent heat is a very important part of this. Water and ammonia have two of the largest latent heats of any substance known. This is why ammonia was used in refrigeration for decades, even into the 1990s and beyond at some skating rinks and commercial facilities. Another reason is the HUGE difference in specific volume (V=1/density). For a flowing device, dW=VdP. The work required to pump liquid water up to 200 or more atmospheres is nothing compared to what it would cost to pump gaseous air up to that same pressure because of the difference in V. Expansion works in our favor too. The specific volume of steam at atmospheric temperature is significantly larger than air (compare molecular weights of 18 vs 29 and the ideal gas constant R/MW). With a large V, we get more power out of expanding steam than air.
  2. Some of these items are more important than others. The basic design of heat exchangers is driven by the application. Consider a fuel gas heater and an oil cooler on a typical stationary gas turbine, such as you might find at a combined cycle power plant. You will not likely ever need to clean the fuel gas heater. The operating pressure will exceed 40 atm. You wouldn't use a plate design. The oil cooler might need to be cleaned several times per year. A plate design held together with threaded rods is often used. It's easy to dismantle and clean. The working pressure isn't too high, it doesn't matter if it leaks a bit (the oil isn't going to explode), and it can stay out in the weather. Consider a feed water heater in a supercritical coal-fired power plant. It has a working pressure of 350 atm and is completely welded together. You would have quite a time cutting it apart with an acetylene torch. It matters if the fluids are clean, dirty, or corrosive. You don't use expensive alloys unless it's necessary. If you inspect any industrial plant or manufacturing facility, you will see a variety of heat exchangers. These diverse solutions illustrate human creativity and ingenuity. We're always looking for a better way to solve problems.
  3. I have always stressed both theory and practice. It has served me well throughout my long career. I've literally crawled in and out of power plants, paper mills, and various industrial facilities all over the world. I can solve a differential equation while replacing a CV joint. For inspiration and real-life examples, please read my book entitled, "Living Math," available on Amazon http://www.amazon.com/dp/B01LXZYLVX The eBook will be free on March 17 and 25, then April 4, 10, and 18.
  4. The answers you get to this question may not be what you're looking for. "Extraction" has a definite meaning in the context of steam turbines. In a Rankine cycle with regenerative heating, steam is bled off the turbine at various stages and directed to feedwater heaters, which raise the temperature of the compressed liquid upward toward the inlet of the boiler, as with an economizer. This actually decreases the power output of the steam turbine, but it increases the efficiency of the overall process. This is often illustrated in textbooks, showing that the regenerative Rankine cycle is more rectangular (closer to Carnot in shape) and generates less entropy for the same work output; thus, the increase in efficiency. You must distinguish between extracting steam (i.e., a mass flow rate) and extracting power (i.e., an energy flow rate). I suspect you mean to ask, "is is possible to get more power out of a steam turbine? (with the same input)" While the answer to this question is technically, "yes," that doesn't mean it is practical to do so or that anyone has figured out how. I have been asked many times why we don't just build more efficient machines or just increase the efficiency to 100% so that there will be no waste heat? Many smart and resourceful people have been trying to do just that for a very long time. The big bad oil companies don't have a secret carburetor that would get 500 miles per gallon locked away in a safe in Switzerland so that they can gouge motorists at the pump. Humanity has accomplished many remarkable things, which is good reason to keep on trying to do better. Before we can do better, we must understand what has already been done--then try to improve upon it. This has always been the challenge for the next generation. The expression "standing on the shoulders of giants" is applicable in this case. You need to read Ken Cotton's book, "Evaluating and Improving the Performance of Steam Turbines." It's expensive, but well worth it. Ken Cotton was very influential in the development of the modern steam turbine and one such giant.
  5. You are quite right. The true uncertainty of the process you're describing is much more complicated than it may seem from reading the literature. I have a particular interest in this subject, work for a company that is intimately concerned with such things, and am currently collaborating with a group retired professors to adequately address this gap in the literature. Not only does the sensor itself present multiple uncertainties, at the very least both random and systematic, but the sampling process also contains uncertainty. So does the analog-to-digital conversion. Thermocouples have greater uncertainty than platinum RTDs, due to consistency and sampling. It is very difficult to accurately measure small DC voltages. I once set up a test to prove this to a colleague, using everything from a cheap analog multimeter from Radio Shack to a digital one costing many thousands of dollars--all connected to a single nominal 1.5V C size Duracell battery. There is also the matter of how long do you sample a moving target? Most systems of practical interest vary over time. There are far too many people who think that, if you sample long enough, you will know a quantity with certainty; but this is not the case. There are also far too many people who think you're supposed to divide the uncertainty or the standard deviation by sqrt(n), which magically makes all the uncertainty vanish. This is just ignorance and wishful thinking. There are glaring errors in prestigious test codes, including ASME PTC-19.1 (Test Uncertainty) and even ISO JCGM 100 (Evaluation of measurement data--Guide to the expression of uncertainty in measurement), which can be demonstrated with actual data and also Monte Carlo simulations. In recent years, NIST has begun using different words, including "repeatability," which means, "We keep getting the same number, but we have no idea if it's right." History is littered with examples of people who were absolutely sure beyond a shadow of a doubt that they were obtaining accurate measurements of something we now know doesn't exist or isn't what they thought it was. I encourage you to diligently pursue this matter and consider all of the complicating circumstances you can think of in doing so. I don't mean to be overly negative. Just because we may not know something to the level of precision that we might like, doesn't mean that what we do know is worthless or that attention to detail is without reward.
  6. The attached data set is derived from actual performance of an engine that is very well maintained, as is the instrumentation. Sadly, this is not often the case in the power industry, making this an extraordinary data set. In the spreadsheet you will find the ambient conditions, operational controls, fuel data, reported performance, and regressions. These regressions (for generator output and heat input) are curve fits you can use for various analyses and can be scaled to match your specific engine. EOH is equivalent operating hours, which is the literal running time plus adjustments for start up, shut down, and cleaning. Your regression should be based on absolute humidity, not relative humidity (Google "psychrometrics" for details). Controls include grid frequency (generator rotational speed), anti-icing, and inlet guide vane angle (think: accelerator pedal position on a car). Fitting power is straight-forward. You always want to perform a regression on heat input rather than heat rate, as the former is a single entity and the latter is the ratio of two (see ASME PTC-22 and PTC-46 for discussion). The scatter is remarkably tight for power and heat input due to the exceptional maintenance. The scatter for heat rate is significantly more because it's a quotient. The multi-variate regression is easily obtained by copying cells B4:M7329 to the clipboard, launching CURVEFIT, selecting Y(X1,X2,...), and pressing "Fit Curve". The result, ready for Excel, is copied to the clipboard by pressing "Copy Fit to Clipboard". Switch to Excel, press Alt-F11, and paste. It's that simple. You can download CURVEFIT anytime for free. GT_performance_data.xls
  7. This would be a good project for a team of seniors or a graduate student. Consider prevailing wind as it varies over the face of the Earth and where to best deploy turbines. You can get daily data from about 15,000 stations from the NCDC server, which is operated by NOAA. It's in files called GSOD (Global Surface Summary of the Day). Information on the data sets and coverage are available on their web site. The animation below shows typical values over decades just for illustration. The other figure shows station locations. Most of the stations are in heavily populated areas.
  8. I have already suggested the cube covered with a folded graph under the topic of natural draft cooling tower curves. You might also use spheres of different color and size, as illustrated in the two attached animations created with Tecplot. Similar animations can be created with TP2, a free tool available on the web.
  9. From aerodynamics to hydrodynamics, the MacCormack method of alternating differences has proven to be a powerful way of modeling fluid flow. There are many articles on the web, for instance, Wikipedia has a page on this topic. This technique was brought from aerospace to hydroelectric reservoirs by my mentor, Dr. William R. Waldrop. Several techniques are discussed in the attached paper. Calculated flows from a typical reservoir are shown in these two figures. The source code (C or FORTRAN) is available for free. TVA3-519.pdf
  10. One of my mentors, Dr. William R. Waldrop, was in the US Air Force working at Lockheed when NASA was developing the Saturn V booster. Lockheed had promised NASA to deliver a 3D CFD model of the five-engine booster but hadn't yet delivered and weren't sure how. Bill Waldrop and Dr. Frank Tatom accomplished this feat in the days of mainframes and punch cards. Each weekend they would bring NASA's biggest computer to its knees. Bill wanted to pursue a Ph.D. but couldn't find a university that would allow him to extend the work in aerodynamics. Instead, he got a position at LSU to work on, "Three-Dimensional Flow and Sediment Transport at River Mouths" (the Mississippi delta). Consider this statement from the Acknowledgement section of his dissertation... "Much of the credit for this accomplishment should go to Drs. R. C. Farmer and J. C. Coleman for advice and guidance during this effort and for having the confidence in an aerodynamisist who had the audacity to enter two new fields at the PhD level." When Bill was the Assistant Director of the TVA Engineering Laboratory, he hired me to work on power plants. His breadth of understanding of fluid flow guided a diverse array of projects and many publications. I highly recommend teams comprised of members with different backgrounds when solving difficult problems.
  11. I used to teach a course at university on process optimization. There are several simple problems that can be solved using Excel. For example, it takes so long to produce X and a different time to produce Y and another time to switch over from one to the other. If you must produce a total of Z, what is the optimal approach? The Tom's cracker factory is less than a mile from my house. [Sadly, they have since closed )-;] They made cheese and also peanut butter crackers on the same machines and it takes a while to switch over. There is also a factory in town that makes plastic door mats and also special mats to use at the driving range to whack golf balls. That is also done on the same machine. Shutting the machine down and bringing it up again wastes $15,000; so the decision is not made lightly. I have attached a few spreadsheets, of course, one of them must be McDonalds Big Mac and fries! AutoAssembly.xls cabinets.xls carsales.xls mcdonalds.xls WhittWindowCo.xls
  12. With improvements in design, turbochargers are being deployed in more diverse applications, not just to get more power out of an automobile engine. [You should know that a supercharger doesn't impact the efficiency nearly as much as the power output, so that it's like increasing the displacement; while a turbocharger impacts the efficiency, not just by some constant, but differently over the range of operation.] The first figure shows typical performance curves. The second shows how these may be displayed in Excel. The third shows a section of the spreadsheet where the regression is performed and the fourth shows another way Excel will graph it. The spreadsheet is also attached. I had to first digitize the curves, which can be facilitated by coloring each one with a marker, scanning the image, and using DIGITIZE, which has the option of automatically digitizing everything of one color (ctl-A) or each of the 16 default Windows colors (except black and white) in sequence (ctl-alt-A). You can download DIGITIZE for free anytime. turbocharger.xls
  13. I was testing a cooling tower at a big coal plant. There were 3 circ water pumps, which the operator suspected were not all performing the same. The 2-meter cement conduits were buried with no access ports, so using a pitot tube was out. I injected Rhodamine dye at the intake of each pump and sampled at the condenser water box. I then had to resolve the differences from only knowing the mixture. The distance from the cooling tower to the condenser was about 0.5 km. The first figure shows a finite element conceptual model of the conduits. The second shows the actual dye measurement. The third shows particle tracking results and the fourth shows the particle tracking model display screen capture. You can download the code (PTRAX) for free. It comes with some examples and works with 2D or 3D and several element shapes.
  14. Besides keeping the lights on, homes warm, and cars rolling, what is the greatest application of mechanical engineering? Amusement park rides, of course! If you aren't fascinated by these designs, then you should probably switch majors to something like business or marketing. Do you know why the Death Drop is curved the way it is? Calculus of Variations--that chapter at the back of the book you never got around to covering. Turn off the TV, get the book out, and read it now. The quickest path down a slide has a certain shape, called a brachistochrone. It was recognized by the ancient Greeks. Don't you just know somebody named Thrillacus (an aspiring mechanical engineer, of course) tried to build one along the aqueduct in 300 BC? Newton developed this branch of mathematics and was the first we know of to prove the equation.
  15. If you aren't excited about designing a machine to hurl a vegetable across a field, you might need to consider a major besides mechanical engineering. What an excellent homework assignment for dynamics class. I've attached a spreadsheet to get you started. Now this is a game you can really sink your teeth into! pumpkin.xls
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