Since the invention of the internal combustion engine, automotive engineers, speed junkies and racecar designers have been searching for ways to boost its power. One way to add power is to build a bigger engine. But bigger engines, which weigh more and cost more to build and maintain, are not always better. Another way to add power is to make a normal-sized engine more efficient. Adding either a turbocharger or a supercharger is a great way to achieve forced air induction. Both superchargers and turbochargers pressurize the air intake to above atmospheric pressure. The difference between the two devices is their source of energy. Turbocharger is an exhaust gas driven compressor used in internal-combustion engines to increase the power output of the engine by increasing the mass of oxygen entering the engine. A key advantage of turbochargers is that they offer a considerable increase in engine power with only a slight increase in weight.Unlike turbochargers, which use the exhaust gases created by combustion to power the compressor, superchargers draw their power directly from the crankshaft. Superchargers increase intake by compressing air above atmospheric pressure, without creating a vacuum. This forces more air into the engine, providing a "boost." With the additional air in the boost, more fuel can be added to the charge, and the power of the engine is increased. There are three types of superchargers: roots, centrifugal, twin-screw. The main difference among them is how they move air to the intake manifold of the engine. Roots and twin-screw superchargers use different types of meshing lobes, and a centrifugal supercharger uses an impeller, which draws air in. Although all of these designs provide a boost, they differ considerably in their efficiency and sizes. The biggest advantage of having a supercharger is the increased horsepower.
Sunday, 18 March 2012
Friday, 27 January 2012
Best Books For Mechanical Engineering
Best Books Recommended For Mechanical Students During Their Self Study
- Engineering Thermodynamics By
- P.K.Nag
- D.S. Kumar
- A.Cengel Michael A. Boles
- R.K.Rajput
- Fluid Mechanics By
- R.K.Bansal
- D.S.Kumar
- F.M. White
- Dr P.N. Modi,Dr S.M. Seth
- Theory Of Machines By
- R.S. Khurmi
- V.P. Singh
- Rattan
- Thomas Bevan
- Mechanics Of Solids
- R.K. Rajput
- R.K. Bansal
- Sadhu Singh
- E.P. Popov
- Stephan H.Grandall,Nounman C.Dahl & Thomas J.Hardner
- Production Technology By
- Ghosh & Malik
- P.N. Rao
- R.K. Jain
- P.C. Sharma
- Little
- Raghuvanshi
Monday, 23 January 2012
FM
I'll admit when I first saw the words "Dimensional Analysis," I felt my skin flush; my heart started beating faster; my mind began racing; and I scanned the exits of the room I was in. Classic fight or flight, with an emphasis on the latter.
But as I read, I realized my first reaction was silly. That said, I couldn't stop thinking that a lot of this was hand-waving. Can we legitimately summarize this discussion (or least summarize the justification) by observing that "in physics, almost everything is continuous" so arguments like this just work?
More precisely, what exactly is "length scale" or "characteristic length" supposed to represent? Is this along the lines of the length of the box everything is contained in, or is this the length of the smallest phenomenon observable/significant? What about in problems with a large container and small phenomena of global significance?
Also, why do we put a bar on the velocity scale U?
Finally, how is Reynolds number in any way well-defined? Can't I just say the scales are approximately this or that and get entirely different values?
Onto the next section, when can we legitimately make the lubrication assumption and get realistic results? I want to say for "slippery" fluids, but what does that even mean?
When we get a time estimate for the length of time needed to remove an adhering object, what assumptions are we making about the way it's pulled off? I feel like this should be clear, but wasn't really for me.
Overall, really cool stuff. I'm amazed that despite the sophistication of the equations, we can get tangible and useful numerical results.
But as I read, I realized my first reaction was silly. That said, I couldn't stop thinking that a lot of this was hand-waving. Can we legitimately summarize this discussion (or least summarize the justification) by observing that "in physics, almost everything is continuous" so arguments like this just work?
More precisely, what exactly is "length scale" or "characteristic length" supposed to represent? Is this along the lines of the length of the box everything is contained in, or is this the length of the smallest phenomenon observable/significant? What about in problems with a large container and small phenomena of global significance?
Also, why do we put a bar on the velocity scale U?
Finally, how is Reynolds number in any way well-defined? Can't I just say the scales are approximately this or that and get entirely different values?
Onto the next section, when can we legitimately make the lubrication assumption and get realistic results? I want to say for "slippery" fluids, but what does that even mean?
When we get a time estimate for the length of time needed to remove an adhering object, what assumptions are we making about the way it's pulled off? I feel like this should be clear, but wasn't really for me.
Overall, really cool stuff. I'm amazed that despite the sophistication of the equations, we can get tangible and useful numerical results.
SUNDAY, APRIL 13, 2008
Reading 4/14/2008: Lecture 7
First derivation is very cool. Energy minimization leads to the fluid cylinder instability. Makes sense, and the derivation is simple enough.
Very cool to see Bessel functions popping up, though given the type of equations and the space on which we're solving them, this doesn't seem particularly surprising, comparing to experience with Math 180.
Overall, it all makes sense to me. It's very interesting to see that what is fundamentally a stability analysis can be performed by linearizing and solving the system and then looking at solutions for which the waves grow. I'm a little unclear as to where the "asymmetric modes" part of the final paragraph comes from, but the fact that wavelengths greater than a threshold value grow to infinity actually makes sense to me.
NB: Sorry I've missed so many blog entries. If I can find time, I'm going to go back and write them, but these past two weeks have been absolutely vicious.
Very cool to see Bessel functions popping up, though given the type of equations and the space on which we're solving them, this doesn't seem particularly surprising, comparing to experience with Math 180.
Overall, it all makes sense to me. It's very interesting to see that what is fundamentally a stability analysis can be performed by linearizing and solving the system and then looking at solutions for which the waves grow. I'm a little unclear as to where the "asymmetric modes" part of the final paragraph comes from, but the fact that wavelengths greater than a threshold value grow to infinity actually makes sense to me.
NB: Sorry I've missed so many blog entries. If I can find time, I'm going to go back and write them, but these past two weeks have been absolutely vicious.
WEDNESDAY, APRIL 2, 2008
Reading 4/2/2008: Lecture 3 Notes
I wish I'd had more time to blog recently, but life has been a little too crazy.
At any rate, this is cool stuff. It's nice to see how the free-surface boundary conditions play out in the mathematical PDEs framework, and it's even cooler to see a fairly rigorous proof of Bernoulli's theorem. Obviously the same concepts are there, but, well I'm a mathematician, so it's better now.
Definitely cool to see the Fourier transform appear in the end, too. I'd be curious to hear about the general applicability of the FT in fluids - it's certainly a big hammer and great for making this smooth. (No pun intended.)
The series expansion strangely reminded by of perturbation theory from big quantum; I'm guessing this is a fairly standard approach, I think it's more the notation. That said, I wonder how applicable the linearized equations are and/or what are their drawbacks?
At any rate, this is cool stuff. It's nice to see how the free-surface boundary conditions play out in the mathematical PDEs framework, and it's even cooler to see a fairly rigorous proof of Bernoulli's theorem. Obviously the same concepts are there, but, well I'm a mathematician, so it's better now.
Definitely cool to see the Fourier transform appear in the end, too. I'd be curious to hear about the general applicability of the FT in fluids - it's certainly a big hammer and great for making this smooth. (No pun intended.)
The series expansion strangely reminded by of perturbation theory from big quantum; I'm guessing this is a fairly standard approach, I think it's more the notation. That said, I wonder how applicable the linearized equations are and/or what are their drawbacks?
WEDNESDAY, MARCH 12, 2008
Reading 3/10/2008: Section 3.6
Late, I know, but better than never.
This stuff honestly is straightforward. Having seen complex variable before, the approach is a little weird (partial derivatives of a complex function and chain rule usage are a little suspect, but it works).
Laplace's equation is solved pretty thoroughly in a bunch of classes, so that's pretty much par for the course. It is really cool to see the stuff on p. 197 about using the real vs. complex part as the potential. Didn't know you could look at it that way.
What exactly happens physically at the interface where, mathematically, the pressure becomes negative? That was really my only major question from the chapter.
This stuff honestly is straightforward. Having seen complex variable before, the approach is a little weird (partial derivatives of a complex function and chain rule usage are a little suspect, but it works).
Laplace's equation is solved pretty thoroughly in a bunch of classes, so that's pretty much par for the course. It is really cool to see the stuff on p. 197 about using the real vs. complex part as the potential. Didn't know you could look at it that way.
What exactly happens physically at the interface where, mathematically, the pressure becomes negative? That was really my only major question from the chapter.
WEDNESDAY, MARCH 5, 2008
Reading 3/5/2008: Sections 3.4-3.5
Section 3.4: Very cool; we have a number that can tell is whether we make the assumption of diffusion-dominance or vorticity-dominance. Makes sense to me, though where do we get the characteristic length scale from? And why does it shrink with turbulence? Otherwise, everything is clear.
Section 3.5: The derivation of small Bernoulli is very straightforward, though the result is quite cool. For big Bernoulli, we demand that a flow is irrotational - where are some examples where this really breaks down in a big way? Also, how might one measure &phi, the velocity potential function, much less its time rate of change?
The connection with the Laplacian here makes sense given our assumptions, but is a nice touch. The dipole/etc. thing is worth discussing in class. I've never understood physicists' fascinating with dipoles, but maybe I can with a little more detail.
Section 3.5: The derivation of small Bernoulli is very straightforward, though the result is quite cool. For big Bernoulli, we demand that a flow is irrotational - where are some examples where this really breaks down in a big way? Also, how might one measure &phi, the velocity potential function, much less its time rate of change?
The connection with the Laplacian here makes sense given our assumptions, but is a nice touch. The dipole/etc. thing is worth discussing in class. I've never understood physicists' fascinating with dipoles, but maybe I can with a little more detail.
MONDAY, MARCH 3, 2008
Reading 3/3/2008: Sections 3.2-3.3
Section 3.2: Okay, cool. Our equations reduce with the acoustic approximation to something much more tractable. Very nice. I'm a little curious why we can assume (3.58) can only be satisfied in the two ways mentioned in the book. If I had a little more time, I would sit down and just prove this, but I wonder if there's a quick answer?
What are the real-world implications of S-waves decaying so rapidly? If the waves are only significant very, very close to the source, where do they arise/where are they important in practice?
How is the scattering effect of particles in p. 163 accounted for in fluid models?
Overall, this section seemed pleasantly simple. We get some nasty dispersion relations, but they're easy enough to use, and reduce to forms that are fairly easy to work with. Cool stuff.
Section 3.3: A section with "Theorem" in the title. Yay, math. Honestly, everything here made good sense. I wish I could see a more rigorous proof of the theorem, but for our purposes, this seems pretty good to me.
The bit at the end about vortex tubes is awesome. So THAT'S what a tornado is...
What are the real-world implications of S-waves decaying so rapidly? If the waves are only significant very, very close to the source, where do they arise/where are they important in practice?
How is the scattering effect of particles in p. 163 accounted for in fluid models?
Overall, this section seemed pleasantly simple. We get some nasty dispersion relations, but they're easy enough to use, and reduce to forms that are fairly easy to work with. Cool stuff.
Section 3.3: A section with "Theorem" in the title. Yay, math. Honestly, everything here made good sense. I wish I could see a more rigorous proof of the theorem, but for our purposes, this seems pretty good to me.
The bit at the end about vortex tubes is awesome. So THAT'S what a tornado is...
Reading 2/27/2008: Section 3.1
Woo, Fluids.
So we can immediately dispense with &mu, simplifying things quite nicely. Very cool derivation, and seemingly quite rigorous. I'm not entirely clear why we can assume &xin,n is zero, but I'm assuming it's because Smm is &Phi.
The derivation of the new equation of state is very cool. It's remarkable to see that dp can be characterized completely and uniquely in terms of &rho. I'm not quite sure where the book is going with the "exact differential" comment, but I'm assuming that means something to physicists that it lacks in meaning to me.
Why do we assume viscous stresses are linearly proportional to velocities? What is the origin of this postulate? That was one of the major aspects unclear in the section. Otherwise, the derivation of Newtonian viscosities was clear enough.
And holy cow, we have Navier-Stokes! If only we could solve them generally...
I'm a little unclear what is meant by a volume force in (3.27) - is this just to emphasize that this is a force separate from the external (e.g. gravitational) force?
On p. 151 I just want to point out that the word "magma" is bloody awesome. Everyone should incorporate it into their daily speech immediately. No, seriously. I mean it.
Overall a fantastic section.
So we can immediately dispense with &mu, simplifying things quite nicely. Very cool derivation, and seemingly quite rigorous. I'm not entirely clear why we can assume &xin,n is zero, but I'm assuming it's because Smm is &Phi.
The derivation of the new equation of state is very cool. It's remarkable to see that dp can be characterized completely and uniquely in terms of &rho. I'm not quite sure where the book is going with the "exact differential" comment, but I'm assuming that means something to physicists that it lacks in meaning to me.
Why do we assume viscous stresses are linearly proportional to velocities? What is the origin of this postulate? That was one of the major aspects unclear in the section. Otherwise, the derivation of Newtonian viscosities was clear enough.
And holy cow, we have Navier-Stokes! If only we could solve them generally...
I'm a little unclear what is meant by a volume force in (3.27) - is this just to emphasize that this is a force separate from the external (e.g. gravitational) force?
On p. 151 I just want to point out that the word "magma" is bloody awesome. Everyone should incorporate it into their daily speech immediately. No, seriously. I mean it.
Overall a fantastic section.
Thursday, 19 January 2012
What are some things that mechanical engineers know and others don't?
That the father of computers is a mechanical engineer.
Charles Babbage (1791-1871), computer pioneer, designed the first automatic computing engines. He invented computers but failed to build them
He designed something called Difference Engine which is a Mechanical Computer
A mechanical computer is built from mechanical components such as levers and gears, rather than electronic components.
A difference engine is an automatic mechanical calculator designed to tabulate polynomial functions. The name derives from the method of divided differences, a way to interpolate or tabulate functions by using a small set of polynomial coefficients. Most mathematical functions commonly used by engineers, scientists and navigators, including logarithmic and trigonometric functions, can be approximated by polynomials, so a difference engine can compute many useful tables of numbers.
Artistic display of a portion of Difference Engine #1
Part of Charles Babbage's difference engine (#1), assembled after his death by his son, Henry Prevost Babbage (1824–1918), using parts found in Charles' laboratory
Difference Engine No. 2, built faithfully to the original drawings, consists of 8,000 parts, weighs five tons, and measures 11 feet long.The first complete Babbage Engine was completed in London in 2002, 153 years after it was designed
First complete model of difference Engine #2
The London Science Museum's difference engine, the first one actually built from Babbage's design. The design has the same precision on all columns, but when calculating polynomials, the precision on the higher-order columns could be lower.
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