Fi ck law
Diffusion: random walk of an ensemble of particles from region of high “concentration” to region of small “concentration”.
Flow is proportional to the negative gradient of the “concentration”.
This slide completely describes you about the stuff include in it and also everything about chemical engineering. Fluid Mechanics. Thermodynamics. Mass Transfer Chemical Engineering. Energy Engineering, Mass Transfer 2, Heat Transfer,
quefaction of gasesiquefaction of gases ,adiabatic expansion ,mechanical work ,demagnetization of paramagnetic substance ,adiabatic demagnetization ,joule thomson effect
in this module all the relevant topics of thermodynamics and kinetics has been covered according to the engineering chemistry syllabus and also you can practice questions of thermodynamics and kinetics from this given module. this module is very easy to understand
as everything given is in simple language with figures
This slide completely describes you about the stuff include in it and also everything about chemical engineering. Fluid Mechanics. Thermodynamics. Mass Transfer Chemical Engineering. Energy Engineering, Mass Transfer 2, Heat Transfer,
quefaction of gasesiquefaction of gases ,adiabatic expansion ,mechanical work ,demagnetization of paramagnetic substance ,adiabatic demagnetization ,joule thomson effect
in this module all the relevant topics of thermodynamics and kinetics has been covered according to the engineering chemistry syllabus and also you can practice questions of thermodynamics and kinetics from this given module. this module is very easy to understand
as everything given is in simple language with figures
This presentation talks about the overview of the equations of state as part of behavior of gases chapter. It has equations about the gas laws and combined gas law. Also includes the ideal gas equations and some practice exercises.
This presentation related to molecular diffusion of molecules in gases and liquids. Also includes inter-phase mass transfer and various theories related to it like two film theory, penetration theory and surface renewal theory.
Excess property introduction
▪ Excess volume
▪ Excess gibbs free energy
▪ Entropy of mixing
▪ what is use of Residual property and Excess property
in thermodynamics
▪ Case study
▪ Thermo-calc demo
▪ conclusion
This presentation talks about the overview of the equations of state as part of behavior of gases chapter. It has equations about the gas laws and combined gas law. Also includes the ideal gas equations and some practice exercises.
This presentation related to molecular diffusion of molecules in gases and liquids. Also includes inter-phase mass transfer and various theories related to it like two film theory, penetration theory and surface renewal theory.
Excess property introduction
▪ Excess volume
▪ Excess gibbs free energy
▪ Entropy of mixing
▪ what is use of Residual property and Excess property
in thermodynamics
▪ Case study
▪ Thermo-calc demo
▪ conclusion
Fundamental principle of information to-energy conversion.Fausto Intilla
Abstract. - The equivalence of 1 bit of information to entropy was given by Landauer in 1961 as kln2, k the Boltzmann constant. Erasing information implies heat dissipation and the energy of 1 bit would then be (the
Landauer´s limit) kT ln 2, T being the ambient temperature. From a quantum-cosmological point of view the minimum quantum of energy in the universe corresponds today to a temperature of 10^-29 ºK, probably forming a cosmic background of a Bose condensate [1]. Then, the bit with minimum energy today in the Universe is a quantum of energy 10^-45 ergs, with an equivalent mass of 10^-66 g. Low temperature implies low energy per bit and, of course, this is the way for faster and less energy dissipating computing devices. Our conjecture is this: the possibility of a future access to the CBBC (a coupling/channeling?) would mean a huge
jump in the performance of these devices.
Information theory and statistical mechanicsChandanShah35
Focused on basic terminology used in Statistical Mechanics, Relation ship between Information Theory and Statistical Mechanics and few terms related to quantum mechanics
Nuclear Decay - A Mathematical PerspectiveErik Faust
Radioactivity as a phenomenon is often misunderstood: if one says ‘Radioactive’, most people will think about disastrous electrical plants, dangerous bombs and other forms of life-threatening details. In my native Germany, members of the Green party have been campaigning for a decade to put an end to nuclear energy. Only few think of the useful aspects of this unique actuality, although radiotherapy is most promising of tools in the fight against cancer, and radioactive dating allows us to identify the age of any historical item. But even fewer people see radioactivity as the natural process that it actually is: A spontaneous mechanism, in which one nucleus decays into another. As an aspiring Physicist and Engineer, Radioactivity is one my favourite topics in the realm of science. I am fascinated at how we are able to predict exactly how many Nuclei will decay in a certain amount of time, but not say for certain which Nuclei exactly will do so.
I am Samantha K. I am a Statistical Physics Assignment Expert at statisticsassignmenthelp.com. I hold a Masters in Statistics from, McGill University, Canada
I have been helping students with their homework for the past 8 years. I solve assignments related to Statistics.
Visit statisticsassignmenthelp.com or email info@statisticsassignmenthelp.com.
You can also call on +1 678 648 4277 for any assistance with Statistical Physics Assignments.
Kerala Engineering Architecture Medical is an entrance examination series for admissions to various professional degree courses in the state of Kerala, India. It is conducted by the Office of the Commissioner of Entrance Exams run by the Government of Kerala
Paleontology is the study of the history of life on Earth as based on fossils. Fossils are the remains of plants, animals, fungi, bacteria, and single-celled living things that have been replaced by rock material or impressions of organisms preserved in roc
The ways in which an element—or compound such as water—moves between its various living and nonliving forms and locations in the biosphere is called a biogeochemical cycle. Biogeochemical cycles important to living organisms include the water, carbon, nitrogen, phosphorus, and sulfur cycles.
The AC and DC bridge both are used for measuring the unknown parameter of the circuit. The AC bridge measures the unknown impedance of the circuit. The DC bridge measures the unknown resistance of the circuit.
The Wien bridge is a type of bridge circuit that was developed by Max Wien in 1891. The bridge consists of four resistors and two capacitors. At the time of the Wien bridge's invention, bridge circuits were a common way of measuring component values by comparing them to known values.
For most of us, our name existed even before we did.
In anticipation of our arrival, our parents went through an ultra stressful process of narrowing down dozens of potential names until they chose the perfect one.
Luckily they did, because whatever your name is, it has followed you throughout your entire life; and in some cases, people may have heard of your name before they’ve ever met you.
When it comes to how to name an app, it’s of similar importance as naming a child. The name of your app will follow your brand forever, and in many cases, potential users will hear the name before they ever actually use your app.
flora and fauna of himachal pradesh and keralaAJAL A J
flora and fauna of himachal pradesh and kerala
A green pearl in the Himalayan crown, Himachal Pradesh is blessed with a rich flora and fauna that graces the land with grandeur and majesty. Other animals that can be sighted in the wild include the ibex, wild yak, ghoral deer, musk deer, Himalayan black bear, brown bear, leopards and the Himalayan Thar. Also kerala is gods on country
Bachelor of Science in Cardio-vascular technology is an undergraduate course in cardiology. These technologists assist the physicians in the diagnosis and the treatment of cardiac (heart) and peripheral vascular conditions (blood vessels). The cardiovascular technologists are also responsible for preparing the patients for open-heart surgeries and pacemaker implantation surgeries. The technologists also monitor the patient’s cardiac parameters while they undergo the surgery. B. Sc. in Cardiovascular technology is a three years’ full-time undergraduate course and is an interesting and important course in medicine.
`Remove Unprofitable Products and Services. The products or services with the highest gross profit margin are the most important to your business. ...
Find New Customers. New customers can help grow your business. ...
Increase your Conversion Rate. ...
Review Current Pricing Structure. ...
Reduce your inventory. ...
Reduce your overheads.
Polycystic ovary syndrome (PCOS) is a hormonal disorder common among women of reproductive age. Women with PCOS may have infrequent or prolonged menstrual periods or excess male hormone (androgen) levels. The ovaries may develop numerous small collections of fluid (follicles) and fail to regularly release eggs
Are you an NRI and aiming to come back to India to pursue graduation from the top-tier colleges of India?
Then, you’re halfway there. Being an NRI, your top preference would be IITs and NITs of India. If that's the case, you must know the fee structure of both the IITs, NITs (under DASA scheme), Centrally Funded Institutions and State-Level Govt. Engineering Colleges.
Note: According to the latest update from DASA, from session 2021-22 onwards, JEE Rank is made mandatory for NRI/PIO/OCI Students to be eligible for DASA & CIWG Schemes. Hence, 2020-21 will be the last year when SAT 2 scores will be considered for DASA/CIWG Scheme.
Subjects to study if you want to work for a charityAJAL A J
The charity sector can be competitive and experience, volunteer or otherwise, can count for a lot. But there are ways to make that third sector CV stand out from the competition. Why not take some courses? A course can be a great way to make your application shine and an opportunity to learn new skills and ideas.
Joint Entrance Examination - Main or commonly known as JEE Main is a national level entrance exam conducted by the NTA to offer admission to BE/BTech, BPlan and BArch courses at the IIITs (Indian Institute of Information Technology), NITs (National Institute of Technology) and other Centrally Funded Technical Institutions (CFTIs) across the country.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
1. NEWTON: F=m a
LAPLACE:
Nous devons donc envisager l'état présent de l'universe comme
l'effet de son état antérieur et comme la cause de delui qui va suivre.
Une intelligence qui, pour un instant donné, connaîtrait toutes les
forces dont la nature est animée et la situation respective des êtres
qui las composent, si d'ailleurs elle était assez vaste pour soumettre
ces données à l'Analyse, embrasserait dans la même formule les
mouvements des plus grands corps de l'univers et ceux du plus lèger
atome : rien ne serait incertain pour elle, et l'avenir, comme le passé,
serait présent à ses yeux.
“Translation” In principle “Yes”.
Provided that we know the position, velocity and
interaction of all molecules, then the future behavior is
predictable,…BUT
3. Why Simulation?
1. Predicting properties of (new) materials
2. Understanding phenomena on a
molecular scale.
4. THE question:
“Can we predict the macroscopic
properties of (classical) many-body
systems?”
5. …. There are so many molecules.
This is why, before the advent of the computer, it was
impossible to predict the properties of real materials.
What was the alternative?
1. Smart tricks (“theory”)
Only works in special cases
2. Constructing model (“molecular lego”)…
8. J.D. Bernal constructs a
model of a liquid… (around
1950)..
I took a number of rubber balls
and stuck them together with rods
of a selection of different
lengths ranging from 2.75 to 4
in. I tried to do this in the
first place as casually as
possible, working in my own
office,
being interrupted every five
minutes or so and not remembering
what I had done before the
interruption. However, ...
9. The computer age (1953…)
Mary-Ann Mansigh
Berni Alder
Tom Wainwright
With computers we can follow the behavior of hundreds to
hundreds of millions of molecules.
10. A brief summary of:
Entropy, temperature, Boltzmann distributions
and the Second Law of Thermodynamics
11. The basics:
1. Nature is quantum-mechanical
2. Consequence:
Systems have discrete quantum states.
For finite “closed” systems, the number of
states is finite (but usually very large)
3. Hypothesis: In a closed system, every
state is equally likely to be observed.
4. C o n s e q u e n c e : ALL of equilibrium
Statistical Mechanics and Thermodynamics
12. First: Simpler example (standard statistics)
Draw N balls from an infinite vessel that contains an
equal number of red and blue balls
¥ ¥
13.
14. Now consider two systems with total energy E.
This function is very sharply peaked (for macroscopic systems)
17. This is the condition for thermal equilibrium (“no
spontaneous heat flow between 1 and 2”)
Normally, thermal equilibrium means: equal
temperatures…
18. Let us define:
Then, thermal equilibrium is
equivalent to:
This suggests that b is a function of T.
Relation to classical thermodynamics:
19. Conjecture: ln W = S
Almost right.
Good features:
•Extensivity
•Third law of thermodynamics comes for
free
Bad feature:
•It assumes that entropy is dimensionless
but (for unfortunate, historical reasons, it
is not…)
20. We have to live with the past, therefore
With kB= 1.380662 10-23 J/K
In thermodynamics, the absolute (Kelvin)
temperature scale was defined such that
But we found (defined):
21. And this gives the “statistical” definition of temperature:
In short:
Entropy and temperature are both related to
the fact that we can COUNT states.
22. How large is W?
For macroscopic systems, super-astronomically large.
For instance, for a glass of water at room temperature:
Macroscopic deviations from the second law of
thermodynamics are not forbidden, but they are
extremely unlikely.
23.
24. Consider a “small” system
(a molecule, a virus, a
mountain) in thermal
contact with a much larger
system (“bath”).
The total energy is fixed. The higher the energy of
the small system, the lower the energy of the bath.
What happens to the total number of
accessible states?
25. But, as b=1/kBT :
The probability that the small system is in a given (“labeled”)
state with energy ei is
26. This is the Boltzmann distribution:
“Low energies are more likely than high
energies”
27.
28. The probability to find the system in state I is:
Hence, the average energy is
30. This suggests that the partition sum
is related to the Helmholtz free energy through
31. Remarks
The derivation is not difficult
but it takes a few minutes…
We have assumed quantum mechanics (discrete states) but
often we are interested in the classical limit
ìï é ùïü - ® í- ê + úý
2
( E ) p U ( r
) exp 1 d d exp
å òò p r å
i i 3
i
N N i N
h N ! 2
m
i
b b
îï ë ûïþ
1
h
® Volume of phase space
3
1
N!
® Particles are indistinguishable
Integration over the momenta can be carried out for most systems:
3 3 2 2 2 2 d exp dp exp
ìï é p ùïü é ì í- b = í- b p üù æ p
m
ö ê úý ê ýú = ç ¸
îï ë 2 m ûïþ ë î 2
m
þû è ø
N N
N i
i
i
b
ò p å ò
32. Remarks
Define de Broglie wave length:
1
æ ö
h
2 b
2
2
p
m
L º ç ¸
è ø
Partition function:
, , 1 d exp
( ) ( ) 3
= éë-b ùû L ò r
!
N N
N Q N V T U r
N
33. Check: ideal gas
Thermo recall (3)
Helmholtz Free energy:
, , 1 d exp
( ) ( ) 3
= éë-b ùû L ò r
!
N N
N Q N V T U r
N
1 d 1
dF = -SdT - pdV
= L ò r
N
=
L V
N N
3 3
N
N N
! !
Pressure
Free energy:
Pressure:
F P
V
æ ¶ ö = - çè ¶ ø¸
æ
L
N
3 - L » ÷ ÷ø
ln 3
æ ¶ ö æ ¶ ö ç ¸= ç ¸= è ¶ ø è ¶ ø
F T F E
T
P F N
= -æ ¶ ö = çè ¶ ø¸
V bV
T
Energy:
(ln 1)
= æ ¶ ö = ¶L = ç ¶ ¸ L ¶ è ø
E b F 3 N 3
Nk T
2 B
b b
!
ö
ç çè
b = - N r
N
F T
VN
1
b
b
Energy:
45. i and j are dummy variable hence:
And we can write
46. But as action equals reaction (Newton’s 3rd law):
And hence
Inserting this in our expression for the pressure, we get:
Where
47. What to do if you cannot use the virial expression?
48. Other ensembles?
COURSE:
MD and MC
In the thermodynamic limit the thermodynamic properties are
independent of the ensemble: so buy a bigger computer …
different ensembles
However, it is most of the times much better to think and to carefully
select an appropriate ensemble.
For this it is important to know how to simulate in the various
ensembles.
But for doing this wee need to know the Statistical Thermodynamics
of the various ensembles.
49. Example (1):
vapour-liquid equilibrium mixture
Measure the composition of the
coexisting vapour and liquid
phases if we start with a
homogeneous liquid of two
different compositions:
– How to mimic this with the N,V,T
ensemble?
– What is a better ensemble?
composition
T
L
V
L+V
50. Example (2):
swelling of clays
Deep in the earth clay layers can
swell upon adsorption of water:
– How to mimic this in the N,V,T
ensemble?
– What is a better ensemble to use?
52. Constant pressure simulations:
N,P,T ensemble
-
- p/kBT Thermo recall (4)
First law of thermodynamics
Consider a small system that can exchange
volume and energy with a large reservoir
E E
V V
W - - = W - æ ¶ W ö - æ ¶ W ö + çè ¶ ø¸ èç ¶ ø¸
ln ln , ln ln i i i i
( ) ( ) ,
V V E E V E E V
E V
V E
L
( )
( )
æ ¶ ö
çè ¶ ø¸
E E ,
V V E pV
ln
i i i i
E ,
V k T k T
B B
W - -
= - -
W
1/kBT
S p
V T
æ ¶ ö = çè ¶ ø¸
Hence, the probability to find Ei,Vi:
( ) ( )
W E - E , V - V exp
E + pV
= =
éë- ùû ( )
( )
( )
å å
W - - éë- + ùû
, ,
( )
,
, exp
m exp
éë- + ùû
b
b
i i i i
i i
j k j k j k j k
i i
P E V
E E V V E pV
E pV
b
, i i V E , i
i
d d d + d i i i E = T S - p V å m N
Hence
T ,N
,
1 =
V N
S
T E
and
53. Grand-canonical simulations:
μ,V,T ensemble
-
- -μ/kBT Thermo recall (5)
First law of thermodynamics
Consider a small system that can exchange
particles and energy with a large reservoir
W - - = W - æ ¶ W ö - æ ¶ W ö + çè ¶ ø¸ çè ¶ ø¸
ln ln , ln ln i i i i
( ) ( ) ,
N N E E N E E N
E N
N E
L
( )
æ ¶ ö
çè ¶ ø¸
E E N N E N
W - ,
- m
i i i i i
( )
ln
= - +
E ,
N k T k T
B B
W
1/kBT
æ ¶ S
ö ç = - m è ¶ N ¸ ø
T
Hence, the probability to find Ei,Ni:
( ) ( )
W E - E , N - N exp
E - N
= =
éë- ùû ( )
( )
( )
å å
W - - éë- - ùû
, ,
( )
,
, exp
m exp
éë- - ùû
b m
b m
i i i i i
i i
j k j k j k j k k
i i i
P E N
E E N N E N
E N
b m
, i i N E , i
i
E E
N N
d d d + d i i i E = T S - p V å m N
Hence
,
i
i T V
,
1 =
V N
S
T E
and
54. Computing transport coefficients from an
EQUILIBRIUM simulation.
How?
Use linear response theory (i.e. study decay of fluctuations in
an equilibrium system)
Linear response theory in 3 slides:
55. Consider the response of an observable A due to an
external field fB that couples to an observable B:
For simplicity, assume that
For small fB we can linearize:
61. 62
HHWW 1144
More on Moderators
Calculate the moderating power and ratio for pure
D2O as well as for D2O contaminated with a) 0.25%
and b) 1% H2O.
Comment on the results.
In CANDU systems there is a need for heavy water
upgradors.
62. slowing down in hydrogeneous
material
63
More on Moderators
slowing down in large mass
number material
u u
7x
6x
5x
4x
3x
2x
x
3x
continuous slowing-down model
2x
x
0 1 2 3 4 5 6 7 n 0 1 2 3 n
63. 64
More on Moderators
A
= + - - úû
ln 1
1
u E
ln 1 ( 1)
2
2
ù
+
D = = é
êë
A
A
A
E
av
z
CCoonnttiinnuuoouuss sslloowwiinngg ddoowwnn mmooddeell oorr FFeerrmmii mmooddeell..
• The scattering of neutrons is isotropic in the CM
system, thus z is independent on neutron energy. z
also represents the average increase in lethargy per
collision, i.e. after n collisions the neutron lethargy
will be increased by nz units.
• Materials of low mass number z is large Fermi
model is inapplicable.
64. 65
More on Moderators
MMooddeerraattoorr--ttoo--ffuueell rraattiioo º Nm/Nu.
• Ratio leakage ¯ Sa of the moderator f ¯.
• Ratio ¯ slowing down time p ¯ leakage .
• Water
moderated
reactors, for
example, should
be under
moderated.
• T ratio ¯ (why).
65. 66
One-Speed Interactions
• Particular general.
Recall:
• Neutrons don’t have a chance to interact with each
other (review test!) Simultaneous beams, different
intensities, same energy:
Ft = St
(IA + IB + IC + …) = St
(nA + nB + nC + …)v
• In a reactor, if neutrons are moving in all directions
n = nA + nB + nC + …
Rt = St
nv = St
f
66. w
One-Speed Interactions
R r F r dF r vn r d v n r r
67
n
w ( r
, ) d W r
dW
º Neutrons per cm3 at r
whose velocity vector
lies within dW about w.
n(r ) = ò n(r , w
)d W
4
p
• Same argument as before
dI (r ,w ) = n(r ,w
)vdW ( , ) ( , )
= = = å W = å = å
( ) ( ) ( , ) ( , ) ( ) ( )
4
dF r dI r
t t t
t
w w f
w w
w p
= å
ò ò
where
(r ) = òvn(r , )dW
f w
p
4
67. n r n r E w d dE
Scalar
68
Multiple Energy Interactions
• Generalize to include energy
n
w ( r
, E , ) dEd W º Neutrons per cm3 at r with energy
interval (E, E+dE) whose velocity
vector lies within dW about w.
n(r , E)dE = ò n(r , E, )d W
dE ò ò
p
w
4
¥
= W
( ) ( , , )
p
0 4
R r E dE E n r E v E dE E r E dE t t ( , ) ( ) ( , ) ( ) ( ) ( , ) = å = å f
¥
= å
f
ò
R(r ) (E) (r , E)dE t
0
Thus knowing the material properties St and the neutron flux f as a
function of space and energy, we can calculate the interaction rate
throughout the reactor.
68. dI (r,w) = n(r ,w)vdW dI r = n r vdW
69
Neutron Current
¥
= å
f
ò
• Similarly R r S () E) r E)dE S
((, and so on …
0
Scalar
• Redefine as
( ,w) ( ,w)
J = òvn(r , )dW
(r ) = òvn(r , )dW
f w
p
4
4
w
p
NNeeuuttrroonn ccuurrrreenntt ddeennssiittyy
• From larger flux to smaller flux!
• Neutrons are not pushed!
J
• More scattering in one direction
than in the other.
x J · xˆ = J
69. Net flow of neutrons per second per unit area normal
to the x direction:
( , ) ( , ) ( ) ( , ) ( , ) ˆ f
a n r t d S r t d r r t d J r t ndA
t
70
· = = ò W
J xˆ J n(r , )v cos d x x
p
w q
4
In general: n J · nˆ = J
EEqquuaattiioonn ooff CCoonnttiinnuuiittyy
¶
ò " = ¶
ò "-òå "-ò ·
" " " A
Rate of change in
neutron density
Production
rate
Absorption
rate
“Leakage
in/out” rate
Volume Source
distribution
function
Surface
area
bounding "
Normal
to A
Equation of Continuity
70. B dA Bd 3r
( , ) ( , ) ( ) ( , ) ( , ) ˆ f
a n r t d S r t d r r t d J r t ndA
t
71
Using Gauss’ Divergence Theorem ò · = òÑ·
S V
( , ) ˆ ( , )
ò · = òÑ· "
J r t ndA J r t d
A
"
¶
ò " = ò "-òå "-ò ·
¶
" " " A
= -å -Ñ·
¶ f f
1 (r ,t) S(r ,t) (r ) (r ,t) J (r ,t)
v ¶
t a
Equation of Continuity
EEqquuaattiioonn ooff CCoonnttiinnuuiittyy
71. 72
Equation of Continuity
For steady state operation
Ñ· J (r ) + å (r ) f
(r ) - S(r ) = 0 a
For non-spacial dependence
¶
n(t) S(t) (t)
t a= -å f
¶
Delayed sources?
72. 73
Fick’s Law
Assumptions:
1.The medium is infinite.
2.The medium is uniform
å not å
(r ) 3.There are no neutron sources in the medium.
4.Scattering is isotropic in the lab. coordinate system.
5.The neutron flux is a slowly varying function of
position.
6.The neutron flux is not a function of time.
Restrictive! Applicability??
73. 74
Fick’s Law
Current Jx
x
dC/dx
x
f(x)
Negative Flux Gradient
Current Jx
High flux
More collisions
Low flux
Less collisions
• Diffusion: random walk of
an ensemble of particles
from region of high
“concentration” to region of
small “concentration”.
• Flow is proportional to the
negative gradient of the
“concentration”.
74. Number of neutrons ssccaatttteerreedd per
second from d" at rr and going
through dAz
r dAz r
Removed
(assuming no
buildup)
75
x
y
z
r
dAz
Fick’s Law
q
f
f q
( ) cos
å e-S d"
r
s
t
4 p
2
å å
not (r ) s s
Slowly varying
Isotropic
76. z z J dA dA r e t drd d
1
»
3
S
77
Fick’s Law
¥
- = S -S
ò ò ò [ ]
= =
s z r
=
p
f
p
q
f q q q f
p
2
0
/ 2
0 0
( ) cos sin
4 r
HHWW 1155
0
æ
S
= + - - = - å
s
z z z ¶
3 2
ö
ö çè
÷ø
æ
÷ ÷ø
ç çè
z
J J J
t
¶f
+ = ?
z z J dA
and show that
= - Ñf = å
J D D s
and generalize 3 S
2t
s
D
DDiiffffuussiioonn
ccooeeffffiicciieenntt
Fick’s law
The current density is proportional to the negative of the gradient
of the neutron flux.
87. Chapter 4 Fluid Flow, Heat Transfer, and Mass Transfer:
Similarities and Coupling
4.1 Similarities among different types of transport
4.1.1 Basic laws
The transfer of momentum, heat , and species A occurs in the direction of
decreasing vz, T, and wA, as summarized in Fig. 4.1-1. according to Eqs. [1.1-2],
[2.1-1], and [3.1-1]
[4.1-1] also
[1.1-2]
[4.1-2] also
[2.1-2]
[4.1-3] also
[3.1-1]
z
yz
d
dy
t = -m n
q k dT
y
dy
= -
A
j D dw
Ay A
dy
= -r
Newton’s law of viscosity
Fourier’s law of conduction
Fick’s law of diffution
88. The three basic laws share the same form as follows:
Or
[4.1-4]
[4.1-5]
Flux of gradient of
æ ö æ ö
ç ¸ æ proportonal
transport ö ¸=-ç ¸´ç ç transport
¸ ç ¸ è ç ¸ è cons t
ø ø è ç ø
¸ j d
f f dy
The three-dimensional forms of these basic laws are summarized in Table 4.1-1.
For constant physical properties, Eqs. [4.1-1] through [4.1-3] can be written
as follows:
[4.1-6]
tan
property property
y
=-G f
d v
dy
t = -n r
( ) yz z
89. [4.1-7]
[4.1-8]
q = -a d r
C T
( ) y v
dy
j D d
=- r
( ) Ay A A
dy
These equations share the same form listed as follows:
[4.1-9]
Flux of diffusivity gradient of
transport of transport transport property
property property concentration
æ ö æ ö æ ö
ç ¸=-ç ¸´ç ¸ ç ¸ ç ¸ ç ¸
çè ø¸ èç ø¸ èç ø¸
In other words, n, a, and DA are the diffusivities of momentum, heat, and mass,
respectively, and rvZ, rCvT, and rA are the concentration of z momentum, thermal
energy, and species mass, respectively.
4.1.2 Coefficients of Transfer
Fig. 4.1-2 shows the transfer of z momentum, heat, and species A from an
interface, where they are more abundant, to an adjacent fluid, and from an adjacent
fluid, where they are more abundant, to an interface. The coefficients of transfer,
according to Eqs. [1.1-35], [2.1-14], and [3.1-21], are defined as follows:
90. t - m ¶ ¶
= =
' 0 0 [4.1-10]
= =
0
( / )
0
yz y z y
f
- -
z z
v y
C
v v v
¥ ¥
(momentum
transfer coefficient)
91. [4.1-11]
[4.1-12]
q - k ( ¶ T / ¶
y
)
h = y y = =
y =
( heat transfer coefficient
) T - T T -
T
¥ ¥
j - D ¶ w ¶
y
( / )
Ay y = A A y
=
(mass transfer coefficient) = =
- -
As mentioned in Sec. 3.1.6, Eq. [4.1-12] is for low solubility of species A in the fluid.
These coefficients share the same form listed as follows:
[4.1-13]
[4.1-14]
[4.1-15]
or
Coefficient flux at the
of transfer difference in transport property
æ ö æ ö
ç ¸= ç ¸
è ø è ø
j -G ( ¶ f
/ ¶
y
)
k = f y = =
f
y =
(mass transfer coefficient) f
f - f f -
f
¥ ¥
It is common to divide Cf by rv/2 to make denominator appear in the form of the
kinetic energy rv2
∞/2. As shown in Eq. [1.1-36], the so-called friction coefficient is
defined by
0 0
0 0
0 0
0 0
m
A A A A
k
r w rw w w
¥ ¥
interface
0 0
0 0
'
0
f yz y
=
= =
1 1 2
2 2
f
C
C
t
rn rn
¥ ¥
92. 4.1.3 The Chilton-Colburn Analogy
The analogous behavior of momentum, heat, and mass transfer is apparent from
Examples 1.4-6, 2.2-5, and 3.2-4, where laminar flow over a flat plate was considered.
From Eqs. [1.4-67], [2.2-71], and [3.2-56], at a distance z from the leading edge of the
plate,
C = -
0.323Re (1 2)
fz
2
z
0.323Pr1 3 Re 1 2 z
hz
k
=
k z Sc
D
m 0.323 1 3 Re 1 2
z
A
=
[4.1-16]
[4.1-17]
[4.1-18]
where
Rez
zru
m
= ¥ (local Reynolds number)
Pr p v C
m
= = (Prandtl number)
k
a
Sc v
m
r
= = (Schmidt number)
D D
A A
[4.1-19]
[4.1-20]
[4.1-21]
and υ∞ is the velocity of the fluid approaching the flat plate.
93. Equations [4.1-16] through [4.1-18] can be rearranged as follows
C fz
= 0.323Re -
(1 2)
2
z
1 Pr2 3 0.323Re (1 2)
PrRe z
hz
k
= -
k z Sc
D Sc
1 2 3 0.323Re 1 2
Re
m
z
A z
=
[4.1-22]
[4.1-23]
[4.1-24]
Since these equations have the same RHS, we see
C hz k z Sc
1 Pr2 3 1 2 3
fz m
k D Sc
2 PrRe Re
A z
= =
Substituting Eqs. [4.1-19] through [4.1-21] into Eq. [4.1-25], we obtain
C fz h k m
Sc
Pr2 3 2 3
2
= =
u rC u ¥ ¥
p
[4.1-25]
[4.1-26]
94. This equation, known as the Chilton-Colburn analogy,1 is ofen written as follows
fz
2
H D
C
= j = j [4.1-27]
where the j factor for heat transfer
Pr2/3 H
p
j h
v rC ¥
=
[4.1-28]
And the j factor for mass transfer
j k Sc
m 2/3
D
= [4.1-29]
v¥
95. The Chilton –Colburn analogy for momentum, heat and mass transfer has been
derived here on the basis of laminar flow over a flat plate. However, it has been
observed to be a reasonable approximation in laminar and turbulent flow in
systems of other geometries provided no form drag is present . From drag, which
has no counterpart in heat and mass transfer, makes Cf/2 greater than jH and jD, for
example, in flow around (normal to) cylinders. However, when form drag is
present, the Chilton –Colburn analogy between heat and mass transfer can still be
valid, that is,
jH = jD
[4.1-30]
or
h k Sc
v rC v ¥ ¥
Pr2/3 m 2/3
p
= [4.1-31]
These equations are considered valid for liquid and gases within the ranges
0.6 < Sc < 2500 and 0.6 < Pr < 100 . They have been observed to be a reasonable
approximation for various geometries, such as flow over flat plates, flow around
cylinders, and flow in pipes.
96. The Chilton –Colburn analogy is useful in that it allows one unknown transfer
coefficient to be evaluated from another transfer coefficient which is known or
measured in the same geometry. For example, by use Eq. [4.1-26] the mass transfer
coefficient km(for low solubility of species A in the fluid) can be estimated from a heat
transfer coefficient h already measured for the same geometry.
It is worth mentioning that for the limiting case of Pr=1, we see that from Eq.[4.1-
26]
fz
2
= [4.1-32]
p
C h
u rC ¥
Which is known as the Reynolds analogy , in honor of Reynolds’ first
recognition of the analogous behavior of momentum and heat transfer in 1874.
97. 4.1.4 Integral-Balance Equations
The integral-balance equations governing momentum, heat , and species
transfer, according to Eq. [1.4-3], [2.2-6], and [3.2-4], respectively, are as follows
¶ òòò vd W = - òò ( vv ´ n ) dA - òò ´ ndA + òòò ( f -Ñ p ) d
W
[4.1-33]
¶ A A b
t
r r t
W W
(momentum transfer)
¶ òòò C Td W = - òò ( vC T ) ´ ndA - òò q ´ ndA + ¶ v v òòò
sd
W
A A
t
r r
W W
(heat transfer)
¶ òòò w W = - òò ( vw ) ´ ndA - òò j ´ ndA + òòò
r d
W
¶ A A A A A A
t
r r
W W
(species transfer)
[4.1-34]
[4.1-35]
98. In Eq. [4.1-33] the pressure term has been converted from a surface integral to
a volume integral using a Gauss divergence type theorem (i.e., Eq. [A.4-2]).
Furthermore, the body force fand pressure gradient b Ñp
can be considered as
the rate of momentum generation due to these force. In Eq. [4.1-34] the kinetic
and potential energy, and the pressure, viscous, and shaft work are not included
since they are either negligible or irrelevant in most materials processing
problems. In Eq. [4.1-35] ρw= ρ.
AA These integral balance equations share the same form as follows:
rate of net rate of
æ ö æ ö
Rate of rate of
æ ö ç ¸= ç ç inf
low by ¸ ç other
¸ æ ö accumulation ¸+ ç ¸+ ç ¸ è ø è ç convection ¸ ø è ç generation
net inf
low
è ø ø
¸ [4.1-36]
or
¶ W = - ¶ òòò òò v ´ ndA - òò j ´ ndA + òòò s d
W
[4.1-37]
rf ( r f
)
t W A A
f W
f
99. These equations are summarized in Table 4.1-2. The following integral mass-balance
equation ,Eq.[1.2-4], is also included in the table:
¶ òòò d Ωv =- nòò ( )
´
dA
[4.1-38]
¶ A
t
r r
W
100. 4.1.5 Overall Balance Equations
The overall balance equations for momentum, heat, and species transfer
according to Eqs.[1.4-9], [2.2-8], and [3.2-7], respectively, are as follows
P = v - v +F + F +F
d m m
dt
( ) ( ) ( ) in out v p b
d E T = ( mC T ) - ( mC T ) + Q +
S
dt
v in v out
(momentum transfer) [4.1.-39]
dM A W = ( mw ) - ( mw )
+ J +
R
dt
A in A out A A
(heat transfer) [4.1-
40]
(species transfer) [4.1-41]
These overall balance equations share the same form as follows
Rate of rate of inflow rate of outflow
accumulation by convection by convection
æ ö æ ö æ ö
ç ¸= ç ¸-ç ¸
è ø è ø è ø
rate of other net inflow rate of
+ +
from surroundings generation
æ ö æ ö
ç ¸ ç ¸
è ø è ø
[4.1-42]
or
101. d F =(m f ) -(m f
) +J +S
dt in out
f f [4.1-43]
Where the total momentum, thermal energy, or species A in the control
volume Ω is
F = òòò rfd
W
W
[4.1-44]
In Eq.[4.1-39] the viscous force Fv at the wall can be considered as the rate
of momentum transfer through the wall by molecular diffusion. The pressure
force Fp and the body force Fb , on the other hand, can be considered as the
rate of momentum generation due to the action of these forces. In Eq.[4.1-40 ]
Q is by conduction, which is similar to diffusion.
The above equations are summarized in Table 4.1-3. The following overall
mass balance equation (i.e. Eq [1.2-6]), is also included in the table
dM m m
dt
- [4.1-
=( ) ( ) in out
45]
102.
103. 4.1.6 Differential Balance Equations
The differential balance equations governing momentum, heat, and species
transfer, according to Eqs. [1.5-6], [2.3-5] and [3.3-5], respectively, are as
follows:
¶ r v -Ñ´r vv -Ñ´t f
-Ñ
¶
b p ( )= ( ) + ( )
t
¶ r = -Ñ´r v -Ñ´ q
+
¶
( ) ( ) v v C T C T s
t
¶ r = -Ñ´r v -Ñ´ j
+
¶
( ) ( ) A A A A w w r
t
(momentum transfer) [4.1-46]
(heat transfer) [4.1-47]
(species transfer) [4.1-48]
In Eq. [4.1-47] the viscous dissipation is neglected and in Eq. [4.1-48] ρwA =ρA
These differential balance equations share the same form as follows:
Rate of rate of net inflow rate of other rate of
æ ö æ ö æ ö æ ö
ç ¸= ç ¸ + ç ¸ +
accumulation ç ¸
è ø è by convection ø è net inflow ø è generation
ø [4.1-49]
or
104. ( ) ( ) s
t f f ¶ rf = -Ñ´r f -Ñ´ +
¶
v j
¶ r = -Ñ´r
¶
v
( ) ( )
t
[4.1-
These equations are summarized in Table 4.1-4. The following equation5 0o]f
continuity, Eq. [1.3-4], is also included in the table:
[4.1-
51]
Table 4.1-5 summarizes these equations for incompressible fluids.