THE ELECTRIC TRACTION : Indian Railways

Reading Time: 6 minutes

Before I start with the topic, I want to discuss a concerning evil, the plagarism. As a team CEV promises to be authentic with its contents. The blogs published here are written by truly dedicated and passionate writers, hence we want you to be sure of ideas and facts presented here, they are not just copied and pasted, but articulated with sincere and dedicated effort. In every blog, the writer has a special interest and had gained knowledge through devoted study and exploration, enjoy reading!

This blog is intended to answer many of your questions which usually cruise in your mind whenever you travel by train if you are curious about how actually things work and have a sense of wonder. Indian Railways is really a masterpiece of engineering. From the diesel power to electric supply, from signalling to various megastructure required, it involves bright minds of mechanical, electrical, civil, electronics and communication and computer engineers to make a safe journey. It is basically an ecosystem of engineers where everyone shares an equal importance and significance.

So following are the question which you will find satisfactory rather thrilling answers,

HOW DOES ELECTRIC TRACTION WORK?

WHY ELECTRIC APPLIANCES LIKE FANS AND TUBELIGHTS OPERATE AT 110 V?

WHAT ARE RATING OF MOTOR USED?

WHICH TYPE OF MOTORS ARE USED AND WHY?

HOW AND IN WHICH PHASE ELECTRICITY IS PROVIDED TO LOCOS? and many more……..

Starting with some of most fascinating facts about our Indian railways

1. It is fourth largest railway network in world by size, 49% routes electified with 25 KVA, runs more than 20,000 passengers trains and more than 9200 frieght trains daily.

2. IR transports 8.26 billion passengers daily which is 1.9 % of Indian population!

3. It is world’s eight largest employer, it had 1.308 million employees as of March 2017.

4. Diamond crossing in Nagpur is one of its kind, only used by IR. Trains there go east, west, north and south.

THE ELECTRIC TRACTION : Indian Railways

5. World’s largest in IR are: Vivek Express has the longest route in India, which covers 4,286 km in about 82 hours and 30 minutes, the train runs between Dibrugarh and Kanyakumari. IR also has longest platform of Gorakhpur.

THE ELECTRIC TRACTION : Indian Railways

6. Srirampur and belapur are two stations in Maharastra situated at the same point on track, but located on opposite sides of track.

7. The mascot for IR is Bholu, the guard elephant.

So, aren’t you amazed and feel proud be one of its traveller.

Coming to the topic, we are now going to discuss about electric traction in trains. What we use in electric cars is battery because power involved there is much smaller, if we talk about trains, it involves transporting over 1000 passengers at overhauling speed of around 100 Kmph.

In general one of aspect of engineering is that it involves “LARGE”, it comes with raised magnitude of everything, like SMALL HUT doesnt involves that much considerations but if you go for something like BURJ KHALIFA then you cant go random, operation of BULLOCK CART is simple but if its mass, its velocity, its power is increased we approach to a BULLET TRAIN, which is not at all plain sailing.

Lets first talk about power supply system to these massive machines.

The power starts its journey from some thermal power plant, hydroelectric power plant or nuclear power plant, it travels through the three phase national power grid and reaches the power sub-station beside the railway stations. The supply available locally can be at 400 KV, 132 KV, or 3.3 KV, irrespective of that, supply fed to the over-head wire is at 25 KV, single phase, by using required voltage transformation.

Below is basic circuit diagram of an externally powered electric traction system.

THE ELECTRIC TRACTION : Indian Railways

Like most of device, a train is also one port system. One terminal connected to the over-head wire through element called pantograph, another terminal connects to the track through the wheels, hence completing the circuit. The grounding of rail-tracks is very-very imporant,  to maintain zero potential difference between track and ground. Sometimes return conductors are employed with boosters transformers instead of rail tracks for this purpose.

So we can break the whole power system into following components :

 

The overhead wire : You all know that any wire suspended between two poles will have a sag. These sags will cause discontinuous power and improper functioning. Clearly, we can not increase the no of poles to great number to check sag. Following technique is used:

First, the messengers wires are laid on poles and the contact wires are suspended through more no of droppers wire to minimise sag.

THE ELECTRIC TRACTION : Indian Railways                                                     

To help maintain proper tension in messenger wire due to seasonal changes we have an automatic tensioning device, many of you would have seen. 

THE ELECTRIC TRACTION : Indian Railways

Then comes the pantograph: It is made of low friction, conducting graphite mounted on the roof of trains to collect power from overhead line. These are prone to great wear and tear, especially in very high-speed trains. They are replaceable. But, they also present a technical glitch i.e. wear and tear occur only at single contact point, and whole rod becomes inoperable, engineers came with a very fascinating solution.

THE ELECTRIC TRACTION : Indian Railways

The over-head lines are arranged in zig-zag fashion so that the contact point on pantograph moves as trains moves on rail, hence undergo uniform erosion over the length, thus life expectancy of the pantograph is greatly increased by this simple arrangement of over head lines.

THE ELECTRIC TRACTION : Indian Railways

Once power recieved at 25 KV from pantograph, it is stepped down to a suitable level.

It’s a well-established fact that three-phase induction motors are superior to the single phase motor in every aspect, from the simplicity, self-starting, efficiency, power to weight ratio, starting and maximum torque and so on. On the other hand, it would also be very clear that we can not at all supply trains with three phase supply, it would make electrification of track greatly complicated.

We supply with 25 KV single phase but run the train with three phase induction motor, thanks to the micro-electronics of today’s world. From the step-down transformer to the induction motor everything in between inside the massive engine is there to get a three-phase supply with easily controlled voltage and frequency (for speed control) to drive three-phase hungry motors.

IGBT circuit: This technology is used for conversion of single-phase voltage to a three-phase balanced voltage supply. It follows following steps: AC rectified to upf DC supply using GTO thyristors, filtering of DC, then inverted and given required phase shift to get 3 phase balanced supply using multiple insulated gate bipolar transistors (IGBTs). Details would be described in the next blog THE IGBT TECHNOLOGY: INDIAN RAILWAYS.

THE ELECTRIC TRACTION : Indian Railways

Some questions left are:

Q. Why AC motors not DC motors used in electric traction?

Ans : There is no doubt that DC motor have very easy speed control compared to induction motors, but they are being phased out because of many reasons : Simple and rigid construction of AC motors makes it resistant to great vibrations and shocks whereas DC’s components are subject failure, easy regenerative braking makes induction motor highly desirable in the industry, greater power to weight ratio, better power factor, low maintenance, etc all these facts prove that three phase induction motor is ideal for high-powered traction systems.

Q.WHAT ARE RATING OF MOTOR USED?

Ans: The rating of traction motor used in WAG-9 series in IR engines: 850 kW, 2180V, 1283/2484 rpm, 270/310A, 2100 kg.

 

By-Rahul(2nd year)

Keep reading, keep learning!!

TEAM CEV!

Menlo Park’s Wizard Vs The Serbian American Inventor

Reading Time: 6 minutes

I, Rahul feel delighted to present to my dear readers an overview of a war which will bring to them the history of the modern power system in a nutshell.

Before we begin the analysis of battle between the Menlo park wizard and the Serbian American inventor, let me first introduce them.

Thomas Alva Edison known as wizard of Menlo park due to great deeds in field of electric power system, mass communication, sound recording, motion pictures, etc. His series of inventions include electric bulbs, phonographs and prominent work on batteries and rubbers. He is considered as greatest American inventor. Having his first laboratory in Menlo park, New Jersey, he is holder of a total of 1093 US patents in his name, as well as patents in other countries also. He was a man defined by persistence, patience and perseverance.

Menlo Park's Wizard Vs The Serbian American Inventor

Nikola Tesla the Serbian American inventor was a talented and enthusiast electrical and mechanical engineer. Best known for his alternating current motor, Tesla although have total patents of around 300 worldwide, many of his
patents were later discovered laid hidden in patent archives and some even not put into patent protection. He had a wide field of work that included wireless power, bladeless turbine, polyphase system, X-ray experiments, radio
remote control, the tesla coil, etc. Tesla was a man defined by his dreams and a genius inside to carry them out.

Menlo Park's Wizard Vs The Serbian American Inventor

The war of currents, soon you will get to know why currents, is the only war I think has bought something good to humans. Only with advent of technology it has been possible that we humans have developed such a large civilization in form of big cities that we know today. Imagine what would be the world without the biggest gift of technology, the electricity. No lights at night, no cooling system, no water in big buildings, without these three we don’t need to talk about anything else, but be happy humans are so smart that he would not let it happen.
So, let us again concentrate on how the battle between Menlo park wizard and Serbian American inventor had led to the world that we know now.
It was the year 1884 when a young enthusiast electrical engineer Nikola tesla hailed from Serbia to America to work in company of his idol Thomas Edison. Charles Batchelor had sent Nikola tesla with a letter of recommendation stating the great potential of this young genius to revolutionize the world with his ideas and
inventions. Nikola tesla in his first appearance to Edison committed to easily fix the dc generator in a ship installed by the Edison company and successfully did that. In no time, Nikola was able to win the position of distinguished engineer in the company. The company basically provided street lightening system including power required to operate them.

Now here comes technological part of this technical blog.
The electric power is carried by current which are either direct current, the dc or alternating current, the ac. In dc the electrons travel in a mean particular direction where as in ac the electron oscillates at a particular frequency at a position. The Edison company was dc power pioneer and was suffering from a serious technical problem, the dc which they utilized dissipated large amount of heat in transmission wires. So large number of power station and also in densely populated cities were required, close to the user. The solution to this problem was simple, increase the voltage and hence reduce the current and hence the heat loss. But at that time efficient voltage transformation was not there, we will talk about today’s scenario in the end. Nikola as expected came up with a futuristic solution to this problem, the alternating current system. And he just not came up with an idea he came up with whole layout of ac system, the transformer, the ac motors, ac generators, light, etc. Now these ac with help of a very lucid and efficient device transformer can be stepped up or down, hence reducing transmission loss and opening possibility of just one central power plant transmitting power to several thousand miles.

Now let us move back to war. Mr Edison ego and desire to be popular as Menlo park wizard led him to reject
the idea of his junior fellow, and asked him to just focus on improving dc generators, and promised him a handsome money for work after being done. Although tesla was dejected but he worked day and night on dc generators and came up with signifcant 10 improvements, but when time of reward came Edison said that Serbians don’t understand American humor.
Tesla immediately resigned and in coming few days had to work as trench diggers for Edison’s company. But diamonds and talented person don’t remain hidden for a long time. Tesla was able to impress some of investors and opened a lab in US, soon he completely developed his ac generators and motors. As expected, ac’s low loss during transmission gained it significant popularity in no time in market. Edison instead of trying to improve his dc system, focused to kill market for his new competitor.
He publicly displayed the fatal nature of ac by electrocuting dogs, cats and even bigger animals like elephants. His crummy experiments were not only limited to animals but he also electrocuted a prisoner, William Kemmler to death, which was very painful death for prisoner and shameful incident to human society. Nikola tesla had deep regret for all the barbaric experiments and havoc Edison caused by using his invention, but asked the mass to see the hopeful prospect of ac system.

Menlo Park's Wizard Vs The Serbian American Inventor

Edison’s public stunts could not stop tesla’s investors to get the great Niagara hydroelectric power plant contract, first of its kind. Westinghouse company agreed to license his patents for the sum of $60,000, plus 150 shares of stock and a $2.50 royalty per horsepower generated by his AC motor , the $60,000 lump sum was worth roughly $1.4 million in today’s dollar (10,10,59,000.00 INR), but in coming time company faced a bankruptcy due to the extravagant propagandas against Edison, thus again Nikola Tesla was left with nothing. To let the company provide customers the ac power he refused to accept the patent sum and from there the uncrowned genius of millennium followed a life facing a mental disorder called ODC till his death in New York hotel in 1943. It was the simplicity of ac machines that had led to victory in the battle and the great inventor outshined his hero and the world has got a beautiful gift, the modern power system.

But I want you to consider another point of view and want you to get a moral from this war. It may sound strange but it’s a proven fact that for long transmission dc system can outshine ac transmission. This technology is called HVDC (High voltage direct current). Menlo Park's Wizard Vs The Serbian American Inventor

If we use ac we have to consider two losses that are still occurring after reducing copper loss, the skin effect and electromagnetic waves emission.

Skin effect: It’s tendency of alternating current to become distributed within a conductor such that current density is maximum at the surface of conductor and decreases with depth in conductor. The skin efect causes the efective resistance of conductor to increase at higher frequency thus reducing the efective cross-section.

EM waves: The transmission cables itself act as large antennas emitting electromagnetic waves in radio frequency, hence contribute to losses. Both of these signifcant losses are not present in dc transmission, and by use
of modern semiconductor physics dc voltage levels can also be transformed efficiently.

So, both the systems had their own merits and flaws, either of the currents could have won the war. But Edison instead of having faith and working on his own idea tried to pull Nikola Tesla down. Drawbacks remained with dc system and ac system soon find its way all over the world. Had Edison worked on dc we could have had more efficient power system and he had been the greatest of greatest inventors on the earth.

Moral: Focus on yourself and your ability and respect others talent and work too.

Thanks a lot for your precoius time and patience to read the blog.

Rahul kumar(2nd year, EED, SVNIT)

#Objection accepted for copied images

Getting Started with Machine Learning with Python

Reading Time: 9 minutes

– BY AMAN PANDEY

 

In my previous tutorial Constructing a Simple Blockchain using PYTHON , I did promise on writing the further about Applications of Blockchain & their Implementation. I will soon post regarding the same. I wanted to make the next tutorial over Blockchain as simple as possible, so I will be needing some time to design my next Tutorial blog on Blockchain. So, keep patience :).

Now, alongside me learning the blockchain, I was also working on Machine Learning and Deep Learning, as if it is my core Learning subjects.

In my last blog on Blockchain, I received few comments that the terms were not easy to understand, thus making the blog difficult to read for the readers completely new to programming, which, is of course very true because these technologies have their own glossary.

I came up with an idea to give you guys the taste of the Machine Learning Models with the easiest way possible, to make my blog better, or you can say that I just trained myself ; P.

Getting Started with Machine Learning with Python

Machine Learning

“Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data, without being explicitly programmed.”

Does that help?

I guess not!

My belief for doing the things perfectly is by actually doing them.

I would love to dip my hands into something worthy rather than sitting and listening to some boring lectures (though they are not that boring, it’s my way of understanding things 😀 ;p).

So, here I present you the best way, that I think is well enough to get you guys a boost start in making and understanding machine learning models.

Getting Started

Before actually getting started, let’s get back to the definition and try to understand it,

“Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data, without being explicitly programmed.”

Few words to underline:

-statistical

-ability to “learn”

-without being explicitly programmed

Now in this tutorial, I will not be taking the names of any technical term except the ones that you need to know. Or better to say the ones which are extremely required. Because I think, for those who are having their first experience in Machine Learning, it becomes extremely confusing when such “Out of their Glossary” kind of terms starts bombarding on them.

So, now how can we start understanding above-underlined terms? How do we actually implement them? How a machine with zero IQ will learn? How will it answer to the problems that are new to them? And most importantly how will we train the machine?

I will try to explain it in very short as I can.

->Statistical means you have previously recorded data of Thousands or millions or even billions of records. E.g. the data of

  • Occurrences of words in emails marked as SPAM
  • Data of various houses & their degree of damage along with structural information of the houses etc.

These datasets are used to make a Mathematical Model, which will then be used to predict the answers for the test datasets.

->Ability to “learn” here is not that computer gets some human power or something and starts learning on its own. Naah. This the thing which we recently called the Mathematical Model.

We actually create a mathematical model using the previous datasets and train them on basis of them, or in other words to say we actually plot them using various techniques (in fancy words called as Machine Learning Algorithms ) based on features (another fancy term), which actually stands for various properties or information related to some object in which we are going to predict our results on.

E.g.

  • Linear Regression
  • Logistic Regression
  • Decision tree Classifier
  • Random Forest
  • Neural Networks etc. etc. etc.

😀 Haha.. none of them gives us clue what they mean. Right?

Now before moving forward I would love to illustrate you with some example, you’ll love the way it all works:

Suppose you want to distinguish between an “apple” and an “orange”.

Getting Started with Machine Learning with Python

Now what you have for information about them?

Ummm, maybe weight, or color may be different levels of its ripeness as it may be possible that apple or orange may have different weights and color at different ripeness level.

Isn’t it?

“Now, we have two features color and weight now.”

A mathematical model is created by plotting these properties on a 2d graph as shown. But that is possible if we have some numerical representation of a feature.

Getting Started with Machine Learning with Python

In this way, we plot them(intuitively), and ready to classify them.

So for the training data we will plot new inputs on this graph and the examples plotted on this graph having ordinates > line will be oranges and the ones having ordinates <line, are the apples.

This is an example of simple Linear regression, in which we plot a line to classify between two targets.

And this is how a computer performs without being explicitly programmed.

Why Python?

PYTHON being the most famous language of today, besides another like JAVASCRIPT, is extremely simple, ridiculously fast, and has a huge Library for various uses ranging from COMPUTATIONAL UTILITIES to CREATING A P2P network.

It may happen that you want to do Machine Learning, and you don’t need to take a full course on python. I know many of the sources where you can learn enough python to go on with machine learning.

Getting Started with Machine Learning with Python

Starting with Building a Machine Learning model.

Steps : –

    1. Installing required Libraries
      Pandas, scikit learn, numpy… that’s it for now
    2. Creating python file, importing required libraries and all
    3. Loading dataset
      we can do with any library but for now, we’ll just have Iris flower dataset, which is actually considered as “Hello world” dataset for python, you’ll find at many places
    4. Exploring our dataset
    5. Making our first model
    6. Printing the accuracy of our model
    7. Testing various models

**Note: Before starting anything I need you to clone the following repo from GitHub link to your local PC:

https://github.com/johnsoncarl/startingWithMachineLearning

1. Installing required Libraries

In the Github repo given above, you’ll find a file name required.txt, this file has all the requirements for the project, just run the following command into your terminal, being into repo directory to install required packages.

sudo apt-get -y install python3-pip
pip3 install -r required.txt

This will install all the required libraries for our model.

2. Creating a Python file, importing libraries and all

Create a python file of your desired name with .py extension in the repo directory, and open it into your favourite text editor and import required libraries as follows:

import pandas as pd
from sklearn import model_selection
from sklearn.metrics import accuracy_score
# these are various machine learning models already stored in the sklearn library
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.naive_bayes import GaussianNB
from sklearn.svm import SVC

 

3. Loading the Dataset

Here we shall use read_csv() function of pandas library to read our dataset as follows.

file = pd.read_csv("iris.data", header = None)
file.head(5)

file.head(5) will view the first 5 rows of the dataset.

And do notice, in read_csv we have header = None, this is used because our dataset does not contain any headings to define the columns. It will look something like this:

Getting Started with Machine Learning with Python

4. Exploring our dataset

Few things before building our model.

Run the following lines to print various information about the dataset we are going to use.

  1. Finding dimensions
print(file.shape)

 2. Describing data with analytics

print(file.describe())

3. Printing distribution of class(grouping according to column no 4, as we have seen in point 3.)

print(file.groupby(4).size())

 

5. Making our First model

Before making any Model and testing data on it, we have a very important step, that is to creating training & testing datasets separately. To train the model on and to test the model on.

For this purpose, we have already imported model_selection  from sklearn.

->  Splitting dataset into Training and Testing

Following code is to first change the dataset into a 2D array, then separating the target from it into Y, defining seed. And finally dividing our dataset into training and validation dataset.

array = file.values     # dataset to a 2d array
X = array[:,0:4]        # feature dataset
Y = array[:,4]          # target dataset
# validation size is used to take out 0.3 i.e 30% of our dataset into test dataset.
validation_size = 0.30
seed = 5                # why random seed is used its given
# finally slicing our dataset into training and testing
X_train, X_validation, Y_train, Y_validation = model_selection.train_test_split(X, Y, test_size=validation_size, random_state=seed)
# to test if its sliced properly
print(X_train[:3])

-> Defining and using our model

We will be using simple Logistic Regression classifier as our model and use to train our dataset and predict the outcomes.

Few steps, Define model, then fit model, then predict the output.

model = LogisticRegression()
# fitting our model
model.fit(X_train, Y_train)
# predicting outcomes
predictions = model.predict(X_validation)
print(predictions[:10])

 

print(predictions[:10])) will print the predictions on validation dataset after being train on the training dataset.

6. Printing the accuracy of our model

Now to rate our model we need to find its accuracy. For this, we need to compare our Validation data to our predicted data. And since we are using a library we don’t need to manually calculate it.  We have the following command to do this job as we have already imported accuracy_score from sklearn.metrics.

print(accuracy_score(Y_validation, predictions))

 

I had the following output when I ran this in my ipython notebook, which I have included in my Github repo.

Getting Started with Machine Learning with Python

It is 93.33% accurate.

And now, you are done with your first machine learning model.

7. Testing Various models

model = LogisticRegression()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("Logistic Regression: ", accuracy_score(Y_validation, predictions, "\n"))
model = DecisionTreeClassifier()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("DecisionTreeClassifier: ", accuracy_score(Y_validation, predictions, "\n"))
model = KNeighborsClassifier()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("KNeigbhorsClassifier: ", accuracy_score(Y_validation, predictions, "\n"))
model = SVC()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("SVC: ", accuracy_score(Y_validation, predictions, "\n"))
model = LinearDiscriminantAnalysis()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("LinearDiscriminantAnalysis: ", accuracy_score(Y_validation, predictions, "\n"))
model = GaussianNB()
model.fit(X_train, Y_train)
predictions = model.predict(X_validation)
print("GaussianNB: ", accuracy_score(Y_validation, predictions, "\n"))

 

My Output was as Follows:

Getting Started with Machine Learning with Python

Here are various accuracies of different models, we will be learning about in upcoming blogs.

**Please have a look at the ipython nb in the repository. Also, you can comment in the REPOSITORY itself.

So, that’s it with this tutorial blog.

My next blog on Machine Learning will be quite boring as I will be explaining some “Boring” terms of machine learning. And after reading this blog. You’ll have an easy understanding of those terms. And also An intuitive idea of every term if you want to learn good quality machine learning.

***Note. If you want then I’ll be providing some references about it in the blog.

# Please provide your suggestions and even if there’s any doubt regarding whatever you have learned from this blog or any other blog. Just get in touch with me @ my email aman0902pandey@gmail.com.

Or comment it on our FB page or insta page.

Happy Learning!

Cheers….

Artificial Intelligence boon or curse?????

Reading Time: 3 minutes

This debate on whether artificial intelligence is good or bad would be among most brainstorming debate in CEV history. At one time we were with the idea that artificial intelligence is an ultimate tool for human to make an earth full of good things and in next moment we felt that it is the last human invention. Debate was held on Friday evening, 31 August.

Points followed for increased exploration in this field were-

Artificial Intelligence boon or curse?????

 

 

 

  1. Artificial intelligence is tool for humanity that can prove to be his most ingenious technological advancement and have potential to help us in sustaining our civilisation much longer.
  2. With the aid of their superhuman capability of enormous computation we can employ them to find solutions to compelling questions like how to cure  AIDS/HIV, how to reduce global warming, alternative for fossil fuels, substitute for plastics,how to reduce ozone layer depletion, etc.
  3. We can exploit this technology in those field where there is great risk of human life like space exploration missions, utility and power linemen, firefighters, miners, search and rescue and so on.
  4.  Now since they are non living things we can use them in crummy works which in many cases lead to social indifferences in our society like slaughterhouse workers, sanitation workers, personal transport drivers, embalmer, garbage collector, sewage cleaner, etc.
  5. Artificial intelligence can play its greatest role in pharmaceutical industry like new methods to treat cancer which are less painful, epidemic control, new medicines with fast cure capability and very less side effects which otherwise will require tedious human labor and time.
  6. Technological change may eliminate specific jobs, but it has always created more in the process, we had witnessed it in past.

Points that indicated that artificial intelligence is the greatest threat to human being ever-

Artificial Intelligence boon or curse?????

  1. These machines are now so advanced that they too have feelings, and in case they feel offended by humans they might declare war against us.
  2. These machines are not subject to ageing so a particular machine can increase its capabilities to tremendous extent.
  3. Another big problem is that it will erase all the job opportunity for the middle class people like car drivers, etc.
  4. Facebook artificial robots were made to shut down forcefully as they were found talking to each other in strange language that was not understood by humans. So, this give us glimpses of what they could be capable of in future. A chunk of  communication they had with them-Bob: i can i i everything else . . . . . . . . . . . . . .Alice: balls have zero to me to me to me to me to me to me to me to me to

    Bob: you i everything else . . . . . . . . . . . . .

Conclusion: Currently in the world Artificial intelligence is still debated topic, there is no doubt that they have a great potential to serve human civilization and make life very convenient, like speech recognition, face recognition all these are features of it. Numerous tech-giants like Google, Amazon, Netflix, Facebook,  Pandora, Tesla are currently utilizing it for more user friendly services. But on the same time there have being events and prediction that uncontrolled and injudicious use will some day create danger for us, hence it should be taken care that artificial intelligence should be employed only in those field where their use are indispensable and that too under vigilant supervision.

Artificial Intelligence boon or curse?????

Minutes by-

Rahul, electrical engg.(2nd year), SVNIT.

(Images are copied randomly, objections are accepted!)

Nuclear Power In India

Reading Time: 5 minutes

By- Rahul Kumar

About this article:This blog intends to aware the mass about the potential of nuclear energy to power India.

So, it becomes necessary to start with some facts and figures.

India with 132.32 crore citizens had energy consumption of 753.7 Mtoe.

For reference, 1Mtoe = 10^6 Toe = 11.63 Megawatt-hour.

Out of total consumption percentage of energy from various fuels are coal (59.8%), crude oil (29.34%), natural gas (6.18%), hydroelectricity (4.07%), renewable sources (2.89%) and just 1.15% from nuclear fuel.

India currently is surplus in generating electricity and also marginally exports electricity to Nepal, Bhutan and Bangladesh. Up to this everything is fine for India.

WHAT THE PROBLEM IS?

Now consider the year 2017 data, India imported nearly 198.8 million tons of crude oil, 25.7 Mtoe of LNG and 129.8 Mtoe of coal hence totaling to 354.3 Mtoe of energy which is equal to 47% of total energy consumption. India’s 75% of electricity is generated by thermal power plants which uses various fossil fuels like coal, diesel and gas. A large percentage of fossils fuel is imported and this large dependency of India on fossils fuels puts it in on unsafe side. India’s overall energy self-sufficiency is 66% which is not that much impressing.

The problem worsens when we consider the fact that the countries with biggest share in exporting fossils fuel to India are facing critical problem of terrorism and it seems that it would increase in coming future and it may lead to decreased exports to us.                    Nuclear Power In India

Another severe problem is that fossils fuels are non-renewable sources, they are going to exhaust completely one day.

And yet another case to be noted is the global warming. It is known to all how global warming can make earth inhabitable.

THE SOLUTIONS

India can choose to switch to renewable sources like solar, wind, otec, biomass, etc. to reduce its dependency on the fossil fuels. But all these technologies are yet not that much efficient to meet the 753.7 Mtoe demand.

India can increase its electricity production to meet the transportation industry energy demands to reduce its dependence on crude oil but again to increase electricity production we have to dig our coal mines deeper.

Finally, India has another option to increase its nuclear power capacity. Currently 14% of world’s electricity is provided by nuclear power plants. USA the largest producer, relies on nuclear power for about 20% whereas countries like France have as high percentages as 75.2.

Nuclear power plant obtains its energy from splitting of uranium atom a process called fission, this chemical reaction generates heat to produce steam, which is used by turbine generators to generate electricity. They produce far more clean energy than fossil fuels and the used up nuclear fuel can be recycled reused and also can be safely disposed.

Nuclear Power In India

WHY INDIA NOT SWITCHING TO NUCLEAR POWER?

The very first reason is that people don’t support government’s any policy for it, most people in India staunchly believe that nuclear power is threatening mode of energy production and subject to impending blast always. There have been numerous protests against major nuclear power plant in India. This is the irrational Indian mindset I want hammer upon by this blog.

Nuclear Power In India

SAFETY OF NUCLEAR PLANTS

But in nuclear power as in other industries, the design, operation of nuclear power plants aims to minimize the likelihood of accidents.

Nuclear power kills far fewer people than any other energy sources according to a review by international energy agency (IAE).

In a report of 2002 by IAE claimed that considering the life cycle of fuel from extraction to post use and included deaths from accidents as well as long term exposure to radiation or emission, nuclear energy came out to be the best and coal was deadliest among energy sources.

There have been three major accidents in history of nuclear power-

# Three-mile island- in 1979 at Three Mile Island nuclear power plant in USA, a cooling malfunction caused part of the core to melt in reactor. Some radioactive gas was released a couple of days after the accident, but not enough to cause any dose above background levels to local residents.

# Chernobyl accident- The Chernobyl accident in 1986 was the result of a flawed reactor design that was operated with inadequately trained personnel. The resulting steam explosion and fires released at least 5% of the radioactive reactor core into the atmosphere. Around 4000 people died due to accident in 20 years from accidents.

# Fukushima nuclear accident- Following a major earthquake, a 15-metre tsunami disabled the power supply and cooling of three Fukushima Daiichi reactors, causing a nuclear accident on 11 March 2011. All three cores largely melted, till now around 2200 people have lost their lives.

Nuclear Power In India

These were 3 major accidents to have occurred in over 17000 reactors over 33 countries, and most were caused due worker’s improper management. The evidences over six decades shows that nuclear power is a safe mode of energy generation, the risk of accidents is very low or declining.

From coal and petroleum products we have steady death rates years after years as these are in form of heart attacks, lungs dysfunction, etc. hence they become invisible to us, whereas a large-scale nuclear meltdown with negligible probability is the event we are scared about.

If we can consider 1995 Chernobyl accidents with 4000 deaths then why we forget about the 230000 deaths from severe flooding due to failure of 30 dams in china in year 1975.

FROM ANOTHER POINT OF VIEW

By switching to nuclear power India can reduce greatly on relying on oil countries by increasing the electricity production to meet the needs of supply of power for electric cars in India. Hence decreasing the pollution and become a more better place to live.

Nuclear Power In India

Thanks for giving your precious time to read this blog.

References:

  • Wikipedia
  • IAE

A Revolutionary change to Next Gen Plastic – Edible or Biodegradable Plastic

Reading Time: 6 minutes

Can you imagine the world without plastic?

The controversy over the use of plastic has been an essential issue more than decades. However, though most of people know using plastic products like water bottles, polythene, cutlery etc is deleterious to our environment, unfortunately, it is still more convenient to buy a plastic container. Nevertheless, wastes generated from producing plastics are definitely over the expectation. Producing plastic is one of the major adversaries of Earth.

According to reports 564 billion plastic water bottles are consumed globally every year. Each year, an estimated 500 billion to 1 trillion plastic bags are consumed worldwide. That comes out to over one million per minute. On average we only recycle one plastic bag in every 200 we use.

50% of plastic is used once and then thrown away so I feel there is an urgent need to find ways to replace some of the unreal amount of plastic we make, use and throw away each day. The BPA (Bisphenol-A) substance can make it hazardous to human health. It also involves energy-intensive processes that use a lot of raw materials. Polyesters like PET can be broken down through hydrolytic degradation and the ester linkage can be cut by a water molecule, but this reaction proceed differently in case of acidic or alcoholic condition under temperature 200-300 °C. Based on this PET is considered as non-biodegradable material which will take more time to decompose such as 450 years. According to the National Association for PET Container Resources, the recycling rate for PET has held steady at 31%.

A Revolutionary change to Next Gen Plastic – Edible or Biodegradable Plastic

Using plastic bottles also produces negative effects on health and environment also. Plastic drinking bottles contain many chemicals, which are harmful to human and animals’ body. Even though plastic drinking bottles are recyclable, most end up in landfills or as litter.

With the advancement in the technology, researchers have now come up with an edible water bottle (water ball) which has capability to set an end to plastic packaging requirements. A water ball is new way of packaging a liquid, say water, that proposes an alternative to the plastic bottle. The edible or consumable water bottle is a blob or drop-like water container which is made from sodium alginate gel. The biodegradable blob is created to make a more environmentally friendly alternative to plastic bottles. The water ball encloses a small volume of water in a membrane which is made from brown algae and calcium chloride.

The water ball is prepared by dropping ice (frozen liquid) into separate solutions of calcium chloride and brown algae and membrane form around it. This process is called as spherification process. The technique of spherification, of shaping a liquid into spheres which visually and texturally resemble caviar born in 1946 is disclosed in US Patent 2403547. Using the culinary technique of spherification, the water is enclosed in a double jellylike membrane. The technique consists into apply sodium alginate (E-401) which is natural product of the brown algae and calcium chloride (E-509) in a concrete proportion in order to generate a jellification on the peripheral of the liquid. Calcium deposited on the membrane creates hardened membrane, and hard shell in the manner of an egg shell. The final package is simple, cheap resistant, hygienic, biodegradable and even eatable. The edible water ball is tasteless, although flavours can be added to it.


A Revolutionary change to Next Gen Plastic – Edible or Biodegradable Plastic

A Revolutionary change to Next Gen Plastic – Edible or Biodegradable Plastic

A seaweed-tech start-up based in London Skipping Rocks Lab has actually implemented this concept and come up with a bio-degradable, edible water bottle (water ball) and the ball is named as “Ooho“. The water ball is a spherical packaging made of seaweed, entirely natural and biodegradable. The edible container can be consumed directly. A layer of edible container can be unwrapped off to keep the peripheral clean for consumption. The water ball will replace millions of plastic bottles thrown away every year.

Another common ecological problem in the fast food industry- the use of plastic cutlery. The problem with use of plastic cutlery is the issue of disposability. People just throw them away and they get buried in landfill and do not degrade if it’s a normal plastic.

Chemicals such as bisphenol A and pthalates leaching into food and drinks. Among all the other plastic substances that get into our food, BPA stands out for its ability to disrupt the functions of hormones- especially estrogen. Pthalates have also been known for causing reproductive problems for men.

The interesting over here is not the facts about the harm of plastic leaching into food, it’s the fact that we all are aware of this but are not taking any action.

The most innovative, revolutionary alternative – Edible Cutlery!

 A Revolutionary change to Next Gen Plastic – Edible or Biodegradable PlasticYou can have the spoon and eat it too! The spoon is just not edible but also nutritious. Edible cutlery offers an interesting alternative to the non-biodegradable plastic ones. “Sale of plastic cutlery, growing at a rate of about 30 per cent, is generating significant non-biodegradable waste and contributing to overflowing landfills. Edible cutlery is the only solution that provides the same convenience of disposable forks, spoons and chopsticks,” says Narayana Peesapaty, managing director of the Hyderabad-based start-up BK Environmental Innovations Private Limited, which developed edible cutlery by baking a mix of sorghum (jowar), rice and wheat flour. A splash of colour is added to the cutlery by including spinach (green), beet root (red) or carrot (orange) pulp to the product mix.

Let’s compare:

Plastic CutleryEdible Cutlery
PriceLowLow
ConvenienceHighHigh
DisposalEasy from a personal point of view but with harmful consequences for the environmentEasy, one can eat the spoon or let it out to decompose, decomposes in 4-5 days
TasteLeaves a bad taste when used during food consumptionServes the purpose of a nutritious millet bread or biscuit added to your meal
HealthBecause of the chemicals it contains and which leach into food, it can lead to cancer, damages of the nervous tissue and hormonal disruptionsBeneficial when consumed after one finishes his/her meal as one spoon contains fibre, iron, protein, calcium, etc.
Consequences for the EnvironmentTakes more than 800 to decompose, polluting streets, landfills and oceans and poisoning marine life and stray animalsTakes 4-5 days to decompose.

Although, a need of lot of research is required in this field. There are people out there making efforts to lessen plastic’s detrimental effects on the environment. Above here are just few ideas that give us hope for a plastic-free future.

There is a huge realization today that we are damaging our planet in many ways, plastic being a main culprit. More and more efforts are being made by eco-conscious individuals and scientists to find alternatives. Anyone can easily create the difference and chances and the others will follow along.

“Plastic is ubiquitous in modern society and seemingly unavoidable. But is it worth risking the lives of marine species, the health of the oceans and our own future in the name of convenience? By taking steps to minimize everyday plastics in our lives, we can crush plastic at the source and give marine life a fighting chance,” said Nil Zacharias, Co-Founder and Editor-in-Chief of One Green Planet.

If we all try to identify where we use plastic and actively look for alternatives, we can drastically cut down on the amount of plastic pollution that finds its way.

You can also join hands to create a plastic free world for our succeeding generations.

 

 

Blog by:

Sanidhya Somani.

2nd Year, Electronics and Communications, SVNIT.

CEV - Handout