# General update: Will be away from blogging for a while

I won’t come back for some 2–3 weeks or more. The reason is this.

As you know, I had started writing some notes on FVM. I would then convert my earlier, simple, CFD code snippets, from FDM to FVM. Then, I would pursue modeling Schrodinger’s equation using FVM. That was the plan.

But before getting to the nitty-gritties of FVM itself, I thought of jotting down a note, once and for all, putting in writing my thoughts thus far on the concept of flux.

If you remember, it was several years ago that I had mentioned on this blog that I had sort of succeeded in deriving the Navier-Stokes equation in the Eulerian but differential form (d + E for short).

… Not an achievement by any stretch of imagination—there are tomes written on say, differentiable manifolds and whatnot. I feel sure that deriving the NS equations in the (d + E) form would be less than peanuts for them.

Yet, the fact of the matter is: They actually don’t do that!

Show me a single textbook or a paper that does that. If not at the UG level, then at least at the PG level, but one that is written using the language of only plain calculus, as used by engineers—not that of advanced analysis.

And as to the UG/PG books from engineering:

What people normally do is to derive these equations in its integral form, whether using the Lagrangian or the Eulerian approach. That is, they adopt either the (i + L) approach or the (i + D) approach.

At some rare times, if they at all begin fluid dynamics with a differential form of the NS equations, then they invariably follow the Lagrangian approach, never the Eulerian. That is, they invariably begin with only (d + L)—even in those cases when their objective is to obtain (d + E). Then, after having derived (d +L) , they simply invoke some arbitrary-looking vector calculus identities to “transform” those equations from (d + L) to (d +E).

And, worse:

They never discuss the context, meaning, or proofs of those identities. None from fluid dynamics or CFD side does that. And neither do the books on maths written for scientists and engineers.

The physical bases of the “transformation” process must remain a mystery.

When I started working through it a few years ago, I realized that the one probable reason why they don’t use the (d +E) form right from the beginning is because: forget the NS equations, no one understands even the much simpler idea of the flux—if it is to be couched entirely in the settings of (d+E). You see, the idea of the flux too always remains couched in the integral form, never the differential. For example, see Narasimhan [^]. Or, any other continuum mechanics books that impresses you.

It’s no accident that the Wiki article on Flux [^] says that it

needs attention from an expert in Physics.

And then, more important for us, the text of the article itself admits that the formula it notes, for a definition of flux in differential terms, is

an abuse of notation

See the section here [^].

Also, ask yourself, why is a formula that is free of the abuse of notation not being made available? In spite of all those tomes having been written on higher mathematics?

Further, there were also other related things I wanted to write about, like an easy pathway to the idea of tensors in general, and to that of the stress tensor in particular.

So, I thought of writing it down it for once and for all, in one note. I possibly could convert some parts of it into a paper later on, perhaps. For the time being though, the note would be more in the nature of a tutorial.

I started writing down the note, I guess, from 17 August 2018. However, it kept on growing, and with growth came reorganization of material for a better hierarchy or presentation. It has already gone through some 4–5 thorough re-orgs (meaning: discarding the earlier LaTeX file entirely and starting completely afresh), and it has already become more than 10 LaTeX pages. Even then, I am nowhere near finishing it. I may be just about half-way through—even though I have been working on it for some 7–8 hours every day for the past fortnight.

Yes, writing something in original is a lot of hard work. I mean “original” not in the sense of discovery, but in the sense of a lack of any directly citable material whatsoever, on the topic. Forget copy-pasting. You can’t even just gather a gist of the issue so that you could cite it.

And, the trouble here is, this topic is otherwise so very mature. (It is some 150+ years old.) So, you know that if you go even partly wrong, the whole world is going to pile on you.

And that way, in my experience, when you write originally, there is at least 5–10 pages of material you typically end up throwing away for every page that makes it to the final, published, version. Yes, the garbage thrown out is some 5–10 times the material retained in—no matter how “simple” and “straightforward” the published material might look.

Indeed, I could even make a case that the simpler and the more straight-forward the published material looks, if it also happens to be original, then the more strenuous it has been, on the part of the author.

Few come to grasp this simple an observation, ever, in their entire life.

As a case in point, I wish to recall here my conference paper on diffusion. [To be added here soon enough.]

I have many times silently watched people as they were going through this paper for the first time.

Typically, when engineers read it, they invariably come out with a mild expression which suggests that they probably were thinking of something like: “isn’t it all so simple and straight-forward?” Sometimes they even explicitly ask: “And, what do you say was the new contribution here?” [Even after having gone through both the abstract and the conclusion part of it, that is.]

On the other hand, on the four-five rare occasions when I have had the opportunity to watch professional mathematicians go through this paper of mine, in each case, the expression they invariably gave at the end of finishing it was as if they still were very intently absorbed in it. In particular, they never do ask me what was new about it—they just remain deeply engaged in what looks like an exercise in “fault-finding”, i.e., in checking if any proof, theorem or lemma they had ever had come across could be used in order to demolish the new idea that has been presented. Invariably, they give the same argument by way of an objection. Invariably, I explain why their argument does not address the issue I have raised in the paper. Invariably they chuckle and then go back to the paper and to their intent thinking mode, to see if there is any other weakness to my basic argument…

Till date (even after more than a decade), they haven’t come back.

But in all cases, they were very ready to admit that they were coming across this argument for the first time. I didn’t have to explain it to them that though the language and the tone of the paper looked simple enough, the argument itself was not easy to derive originally.

No, the notes which I am currently working on are nowhere near as original as that. [But yes, original, these are.]

Yet, let me confess, even as I keep prodding through it for the better part of the day the way I have done over the past fortnight or so, I find myself dealing with a certain doubt: wouldn’t they just dismiss it all as being too obvious? as if all the time and effort I spent on it was, more or less, ill spent? that it was all meaningless to begin with?

Anyway, I want to finish this task before resuming blogging—simply because I’ve got a groove about it by now… I am in a complete and pure state of anti-procrastination.

… Well, as they say: Make the hay while the Sun shines…

A Song I Like:
(Marathi) “dnyaandev baaL maajhaa…”
Singer: Asha Bhosale
Lyrics: P. Savalaram
Music: Vasant Prabhu

# And to think…

Many of you must have watched the news headlines on TV this week; many might have gathered it from the ‘net.

Mumbai—and much of Maharashtra—has gone down under. Under water.

And to think that all this water is now going to go purely to waste, completely unused.

… And that, starting some time right from say February next year, we are once again going to yell desperately about water shortage, about how water-tankers have already begun plying on the “roads” near the drought-hit villages. … May be we will get generous and send not just 4-wheeler tankers but also an entire train to a drought-hit city or two…

Depressing!

OK. Here’s something less depressing. [H/t Jennifer Ouellette (@JenLucPiquant) ]:

“More than 2,000 years ago, people were able to create ice in the desert even with temperatures above freezing!” [^]

The write-up mentions a TED video by Prof. Aaswath Raman. Watched it out of idle interest, checked out his Web site, and found another TED video by him, here [^]. Raman cites statistics that blew me!

They spend “only” \$24 billion on supermarket refrigeration (and other food-related cooling), but they already spend \$42 billion on data-center cooling!!

But, any way, I did some further “research” and landed at a few links, like the Wiki on Yakhchal [^], on wind-catcher [^], etc.  Prof. Raman’s explanation in terms of the radiative cooling was straight-forwards, but I am not sure I understand the mechanism behind the use of a qanat [^] in Yakhchal/windcatcher cooling. It would be cool to do some CFD simulations though.

Finally, since I am once again out of a job (and out of all my saved money and in fact also into credit-card loans due to some health issue cropping up once again), I was just idly wondering about all this renewable energy business, when something struck me.

The one big downside of windmills is that the electricity they generate fluctuates too much. You can’t rely on it; the availability is neither 24X7 nor uniform. Studies in fact also show that in accommodating the more or less “random” output of windmills into the conventional grid, the price of electricity actually goes up—even if the cost of generation alone at the windmill tower may be lower. Further, battery technology has not improved to such a point that you could store the randomly generated electricity economically.

So, I thought, why not use that randomly fluctuating windmill electricity in just producing the hydrogen gas?

No, I didn’t let out a Eureka. Instead, I let out a Google search. After all, the hydrogen gas could be used in fuel-cells, right? Would the cost of packaging and transportation of hydrogen gas be too much? … A little searching later, I landed at this link: [^]. Ummm… No, no, no…. Why shoot it into the natural gas grid? Why not compress it into cylinders and transport by trains? How does the cost economics work out in that case? Any idea?

Addendum on the same day, but after about a couple of hours:

Yes, I did run into this link: “Hydrogen: Hope or Hype?” [^] (with all the links therein, and then, also this: [^]).

But before running into those links, even as my googling on “hydrogen fuel energy density” still was in progress, I thought of this idea…

Why at all transport the hydrogen fuel from the windmill farm site to elsewhere? Why not simply install a fuel cell electricity generator right at the windmill farm? That is to say, why not use the hydrogen fuel generated via electrolysis as a flywheel of sorts? Get the idea? You introduce a couple of steps in between the windmill’s electricity and the conventional grid. But you also take out the fluctuations, the bad score on the 24X7 availability. And, you don’t have to worry about the transportation costs either.

What do you think?

Addendum on 12th July 2018, 13:27 hrs IST

Further, I also browsed a few links that explore another,  solution: using compressed air: a press report [^], and a technical paper [^]. (PDF of the paper is available, but the paper would be accessible only to mechanical engineers though. Later Update: As to the press report, well, the company it talks about has already merged with another company, and has abandoned the above-ground storage of compressed air [^])

I think that such a design reduces the number of steps of energy conversions. However, that does not necessarily mean that the solution involving hydrogen fuel generation and utilization (both right at the wind-farm) isn’t going to be economical.

Economics determines (or at least must determine) the choice. Enough on this topic for now. Wish I had a student working with me; I could have then written a paper after studying the solution I have proposed above. (The idea is worth a patent too. Too bad I don’t have the money to file one. Depressing, once again!!)

OK. Enough for the time being. I may later on add the songs section if I feel like it. And, iterative modifications will always be done, but will be mostly limited to small editorial changes. Bye for now.

# Some suggested time-pass (including ideas for Python scripts involving vectors and tensors)

Actually, I am busy writing down some notes on scalars, vectors and tensors, which I will share once they are complete. No, nothing great or very systematic; these are just a few notings here and there taken down mainly for myself. More like a formulae cheat-sheet, but the topic is complicated enough that it was necessary that I have them in one place. Once ready, I will share them. (They may get distributed as extra material on my upcoming FDP (faculty development program) on CFD, too.)

While I remain busy in this activity, and thus stay away from blogging, you can do a few things:

1.

Think about it: You can always build a unique tensor field from any given vector field, say by taking its gradient. (Or, you can build yet another unique tensor field, by taking the Kronecker product of the vector field variable with itself. Or, yet another one by taking the Kronecker product with some other vector field, even just the position field!). And, of course, as you know, you can always build a unique vector field from any scalar field, say by taking its gradient.

So, you can write a Python script to load a B&W image file (or load a color .PNG/.BMP/even .JPEG, and convert it into a gray-scale image). You can then interpret the gray-scale intensities of the individual pixels as the local scalar field values existing at the centers of cells of a structured (squares) mesh, and numerically compute the corresponding gradient vector and tensor fields.

Alternatively, you can also interpret the RGB (or HSL/HSV) values of a color image as the x-, y-, and z-components of a vector field, and then proceed to calculate the corresponding gradient tensor field.

Write the output in XML format.

2.

Think about it: You can always build a unique vector field from a given tensor field, say by taking its divergence. Similarly, you can always build a unique scalar field from a vector field, say by taking its divergence.

So, you can write a Python script to load a color image, and interpret the RGB (or HSL/HSV) values now as the $xx$-, $xy$-, and $yy$-components of a symmetrical 2D tensor, and go on to write the code to produce the corresponding vector and scalar fields.

Yes, as my resume shows, I was going to write a paper on a simple, interactive, pedagogical, software tool called “ToyDNS” (from Toy + Displacements, Strains, Stresses). I had written an extended abstract, and it had even got accepted in a renowned international conference. However, at that time, I was in an industrial job, and didn’t get the time to write the software or the paper. Even later on, the matter kept slipping.

I now plan to surely take this up on priority, as soon as I am done with (i) the notes currently in progress, and immediately thereafter, (ii) my upcoming stress-definition paper (see my last couple of posts here and the related discussion at iMechanica).

Anyway, the ideas in the points 1. and 2. above were, originally, a part of my planned “ToyDNS” paper.

3.

You can induce a “zen-like” state in you, or if not that, then at least a “TV-watching” state (actually, something better than that), simply by pursuing this URL [^], and pouring in all your valuable hours into it. … Or who knows, you might also turn into a closet meteorologist, just like me. [And don’t tell anyone, but what they show here is actually a vector field.]

4.

You can listen to this song in the next section…. It’s one of those flowy things which have come to us from that great old Grand-Master, viz., SD Burman himself! … Other songs falling in this same sub-sub-genre include, “yeh kisine geet chheDaa,” and “ThanDi hawaaein,” both of which I have run before. So, now, you go enjoy yet another one of the same kind—and quality. …

A Song I Like:

[It’s impossible to figure out whose contribution is greater here: SD’s, Sahir’s, or Lata’s. So, this is one of those happy circumstances in which the order of the listing of the credits is purely incidental … Also recommended is the video of this song. Mona Singh (aka Kalpana Kartik (i.e. Dev Anand’s wife, for the new generation)) is sooooo magical here, simply because she is so… natural here…]

(Hindi) “phailee huyi hai sapanon ki baahen”
Music: S. D. Burman
Lyrics: Sahir
Singer: Lata Mangeshkar

But don’t forget to write those Python scripts….

Take care, and bye for now…