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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 -
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How does gauge pressure of tyre vary if a car goes up a mountain or hill?
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wind power - where to focus effort?
Daniel Bravo replied to dudleybenton's topic in Technology Focus & New Emerging Fields
According to James Lovelock only on nuclear energy. The others is good for development but the cost to the planet for been inefficient is huge. -
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Difference between hot working and cold working
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Plz add me in what's group...7908191635 -
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.
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how would you visualize data in 4 or even 5 dimensions
dudleybenton posted a question in Question & Answers
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. -
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
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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.
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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
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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
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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.
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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.
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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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Did you know that automobile performance can be described by calculus? Newton's law of motion dF=m*dV and dP=V*df so that dP=m*V*dV or dP=m*d(V²) which is where m(V²)/2 comes from and why it's twice as hard to accelerate from 60 mph than 30 mph? Did you know that quarter-mile times and trap speeds can also be related by separating and integrating these same ordinary differential equations? I have attached a figure based on 106 car tests reported by a popular magazine. Calculus yields the quarter-mile time to be t=(9mX²/8P)^(1/3), which is very close to the regression obtained with Excel. The trap speed is V=(3PX/m)^(1/3), also close to what Excel comes up with. Mechanical engineers: PAY ATTENTION IN MATH CLASSES AND DON'T TRY TO AVOID THE TOUGH ONES.
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People rarely consider the fact that solar panels will not always receive the theoretical (clear sky) total irradiation either directly (DNI) or diffusely (GHI). Phoenix, AZ is famous for it's "clear" skies; but a human's opinion of what is or isn't "clear" is not what counts. In fact, the sky over Phoenix is only *technically* clear part of the time, as shown in the figures below, which are *measured* data, not human observation. If you plan to pay for your solar field by selling electricity, you had better account for the fact that it won't be getting that ideal input throughout the official daylight hours. I also attached an animation of what a solar collector field looks like from above--something you don't often see in promotional brochures.
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A car manufacturer (which will remain unnamed) once made a decision to close a factory and put a whole lot of people out of work. The problem was piston clearance. The newly designed engine was deemed essential to continued sales, but the existing facility could not meet the clearance requirements due to outdated equipment. The analysis, performed by a professor I had in college, indicated that perhaps 7% of the engines wouldn't make it off the lot before seizing up. As many as 27% were likely to fail within the first year. Given the dimensions and clearances and assuming these to be normally-distributed (a bell-shaped curve), we can perform an analysis with Monte Carlo. The attached spreadsheet contains just such an analysis for the shaft on an electric motor. The lines in the figure show the allowable and unacceptable combinations of shaft and sleeve diameters. sleeve_shaft_clearance.xls
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Something not often covered in school is the fact that measurements aren't a single number. I have lots of data from many different types of instruments and assure you that the values are rarely distributed normally or even symmetrically. If you don't consider uncertainty (both random and systematic) you are taking on risk. At a billion dollar power plant or manufacturing facility this can be financially devastating. One of the simplest examples is a heat exchanger. The flows and temperatures are only certain to with limits. You should familiarize yourself with uncertainty and confidence intervals. One way of illustrating this is with Monte Carlo, as in the attached spreadsheet. For this simple example, which assumes the measurements are all normally-distributed, the Monte Carlo results fall right on top of the theoretical ones with only 65,535 cases. heat_exchanger.xls
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Over the past 40 years, I have conducted many simulations of various power systems. One thing I've always needed to drive these simulations is meteorological data. You can get this free from over 15,000 weather stations around the world. It is called the Global Surface Summary of the Day (GSOD) and is maintained in a database on servers located in North Carolina operated by the National Climate Data Center (NCDC) of the US National Oceanographic and Atmospheric Administration (NOAA). The files are by year on ftp://ftp.ncdc.noaa.gov/pub/data/gsod in UNIX tar balls. You will need the untar and gzip utilities or you can use WinZip. Pick the station or stations nearest the site in question. Stations are kept in the file called isd-history. You can extend the daily min, max, and averages into hourly values, as illustrated in the attached Excel spreadsheet. I wrote a program that does all this automatically plus interpolates temperatures and barometric pressure over the whole earth. This isn't computer-generated speculation. It's actual recorded data, spatially interpolated. The black specks are the stations reporting data on that particular day. synthesized_hourly.xls
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Find the nearest tractor pull and you will get many new ideas to make more power. I once water injected a V4 outboard on a 13 foot boat that briefly flew with a 40-ft rooster tail... until it ripped the thing right off the transom. Of course, more power is not a plus for an aircraft engine. The FAA is obsessed with safety and couldn't care less about power. Forget aircraft... think swamp boat!
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I downloaded the book and will read it... thanks!
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I took more math classes than the math majors--not a one wasted. I often call myself an applied mathematician. Math has enabled me to do all sorts of things besides mechanical engineering. I worked with several remediation teams when none of the geologists or geohydrologists or civil engineers could handle the mathematics. I solved several of the biggest pollution nightmares in North America, including the most expensive cleanup ever--on Western Cape Cod in the Kennedy's back yard. My particle tracker and 3D model builder software were the premier tools of choice for contractors working for the US Departments of Defense and Energy plus the Environmental Protection Agency for over a decade. I don't mean to be critical, but it has been my experience that engineers who don't have the "knack" (see Dilbert for details) and don't have a strong command of mathematics, end up in management. Of course, some people prefer management. I'd rather be drawn and quartered.
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My wife has a 1904 Gearhart sock knitting machine. She cranks out everything from baby booties to socks that fit Shaquille's size 22 feet! It's fascinating to watch and realize that someone created these more than a hundred years ago and sold them for $11. Now you can hardly find one for $1100.
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A friend of mine, Charles F. Bowman, has written a book (Thermal Engineering of Nuclear Station Balance-of-Plant Systems) on this subject that is soon to be published by CRC Press. It contains more than just BoP, including the cycles and components you are interested in. Chuck was the lead thermal designer on several of TVA's large coal-fired plants (Cumberland, Paradise, Bull Run) and all of TVA's nuclear plants (Browns Ferry, Sequoyah, Watts Bar, Bellefonte, Hartsville, Yellow Creek, Phipps Bend). He is a wealth of knowledge and experience. He has published many papers, some of which you may be able to find online. Also a lot of EPRI papers, which are very difficult to obtain. Many of the papers I've written on the subject can be downloaded from ResearchGate or my website. I have attached three. They're not as interesting as the book, but it hasn't been released yet and I don't know the timeline. I have a lot of software you can download for free. Analysis of Browns Ferry Nuclear Operation with Four and Six Cooling Towers.pdf Analysis of the Paradise Fossil Plant Cooling System.pdf Sensitivity_of_Power_Supply_to_Extreme_Meteorology.pdf
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Back in the late 1970's when I was working on an MS, ocean thermal energy conversion (OTEC) was the rage. There was a guy who went around to conferences with a machine. He dumped ice into one container and poured coffee or hot water into the other. It was a small organic Rankine cycle generating unit and would light up a bulb. He got funding and hopes were high for a full-scale offshore plant. That never happened. The idea *will* work. The demonstration model would light up a bulb. Of course, the ice and hot water didn't last long and the ocean thermal difference is nowhere near that large, but the concept is sound. The problem is cost-effectiveness. Such a system (think Carnot efficiency) is so inefficient and costs so much per watt to build, that it isn't worth the investment. Many more practical and less expensive devices are readily available. Don't be discouraged, just think farther outside the box and keep at it!
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I will throw out a topic here for others to consider... Scheduling power assets is becoming more important, especially in Africa, where development is rapid. You can investigate this with an Excel spreadsheet. You can get and simulate demand over time (throughout the day and also with seasons). You can select a few assets and see how they might meet this demand. Consider a base-load plant, perhaps coal-fired, that ramps up slowly and is not quickly responsive. Add a 2x1, 3x1, or 4x1 combined cycle with duct firing. You can run one or more engines with or without the steam tail. You can experiment when to activate duct firing. You might even add solar panels or a hydro-electric dam. Each of these options provides different levels of power and also expense. The ramp rate (how long it takes to get from one power level to the other) varies with each type. You can get this information off the Web. If you can't find something, I have lots of real data. After you get this working, you can think about how to schedule maintenance on each asset.
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