This document provides an introduction to heat transfer in food processing. It defines key terms like convective heat transfer coefficient and overall heat transfer coefficient. It describes methods for estimating these values, such as empirical correlations for forced and free convection in pipes. Equations are provided for calculating heat transfer through tubular heat exchangers based on temperature differences, heat transfer rates, and surface areas. An example problem demonstrates using these equations to determine the exit temperature of a fluid in countercurrent and parallel flow heat exchange.
carnot cycle (a theoretical thermodynamic cycle).pptHafizMudaserAhmad
The Carnot cycle, a theoretical thermodynamic cycle, serves as a fundamental concept in the study of heat engines. Named after the French physicist Sadi Carnot, this cycle provides insight into the maximum efficiency achievable by any heat engine operating between two temperature reservoirs. It consists of four reversible processes: isothermal expansion, adiabatic expansion, isothermal compression, and adiabatic compression. During the isothermal expansion process, the working substance (often a gas) absorbs heat from a high-temperature reservoir, expanding and doing work on the surroundings. The adiabatic expansion follows, during which the gas continues to expand without heat exchange, resulting in a decrease in temperature and pressure. Subsequently, the isothermal compression occurs as the gas is brought into contact with a low-temperature reservoir, releasing heat and contracting. Finally, the adiabatic compression completes the cycle as the gas is compressed without heat exchange, leading to an increase in temperature and pressure. The efficiency of the Carnot cycle depends solely on the temperatures of the reservoirs, with the maximum efficiency achievable when operating between two reversible isothermal processes. Despite being an idealized model, the Carnot cycle provides valuable insights into the principles of thermodynamics and serves as a benchmark for real-world heat engines.
Effect of Wavy (Corrugated) Twisted Tape Inserts on Heat Transfer in a double...ijiert bestjournal
In the present work heat transfer and friction factor properties we re experimentally investigated by using copper wavy (corrugated) twisted tape inserts. The turbulent flow w as created by inserting the wavy twisted tape inserts into the inner tube of heat exchanger creating high rate of t urbulence in pipe,which results in increasing heat transfer enhancement and pressure drop. The tape consists of the cor rugations and the twisting with various twist ratios (TR=10.7,8.5,7.1). The length and width of insert was 1 meter an d 14 mm respectively. The outer tube of heat exchanger is made up of mild steel with outside diameter .0198 m & .0142 m inside diameter and the inner tube is made up of copper with .038 m outside diameter and .032 m inside di ameter. The length of pipe in pipe heat exchanger is 1.4 m. The bulk mean temperatures at various posit ions are used for different flow rate of water. From the obtained results the new Correlations for Nusselt number and friction factor are developed for twisted tape inserts. The Reynolds number is varied from 5000 to 17000. The results of varying twists in wavy twisted tape inserts with different pitches have been compared with the val ues for the smooth tube. It showed that the highest heat transfer rate was achieved for the wavy twis ted tape with twist ration 7.1. The Nusselt number value increased by 172 % and friction factor value increased by 32.11% as compared to the sm ooth tube values.
carnot cycle (a theoretical thermodynamic cycle).pptHafizMudaserAhmad
The Carnot cycle, a theoretical thermodynamic cycle, serves as a fundamental concept in the study of heat engines. Named after the French physicist Sadi Carnot, this cycle provides insight into the maximum efficiency achievable by any heat engine operating between two temperature reservoirs. It consists of four reversible processes: isothermal expansion, adiabatic expansion, isothermal compression, and adiabatic compression. During the isothermal expansion process, the working substance (often a gas) absorbs heat from a high-temperature reservoir, expanding and doing work on the surroundings. The adiabatic expansion follows, during which the gas continues to expand without heat exchange, resulting in a decrease in temperature and pressure. Subsequently, the isothermal compression occurs as the gas is brought into contact with a low-temperature reservoir, releasing heat and contracting. Finally, the adiabatic compression completes the cycle as the gas is compressed without heat exchange, leading to an increase in temperature and pressure. The efficiency of the Carnot cycle depends solely on the temperatures of the reservoirs, with the maximum efficiency achievable when operating between two reversible isothermal processes. Despite being an idealized model, the Carnot cycle provides valuable insights into the principles of thermodynamics and serves as a benchmark for real-world heat engines.
Effect of Wavy (Corrugated) Twisted Tape Inserts on Heat Transfer in a double...ijiert bestjournal
In the present work heat transfer and friction factor properties we re experimentally investigated by using copper wavy (corrugated) twisted tape inserts. The turbulent flow w as created by inserting the wavy twisted tape inserts into the inner tube of heat exchanger creating high rate of t urbulence in pipe,which results in increasing heat transfer enhancement and pressure drop. The tape consists of the cor rugations and the twisting with various twist ratios (TR=10.7,8.5,7.1). The length and width of insert was 1 meter an d 14 mm respectively. The outer tube of heat exchanger is made up of mild steel with outside diameter .0198 m & .0142 m inside diameter and the inner tube is made up of copper with .038 m outside diameter and .032 m inside di ameter. The length of pipe in pipe heat exchanger is 1.4 m. The bulk mean temperatures at various posit ions are used for different flow rate of water. From the obtained results the new Correlations for Nusselt number and friction factor are developed for twisted tape inserts. The Reynolds number is varied from 5000 to 17000. The results of varying twists in wavy twisted tape inserts with different pitches have been compared with the val ues for the smooth tube. It showed that the highest heat transfer rate was achieved for the wavy twis ted tape with twist ration 7.1. The Nusselt number value increased by 172 % and friction factor value increased by 32.11% as compared to the sm ooth tube values.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
2. Objectives
• Calculate convective heat transfer coefficient
• Calculate overall heat transfer coefficient
• Calculate heat transfer area in tubular heat exchanger
3. Estimation of Convective Heat-Transfer
Coefficient
• h is predicted from empirical correlation for
Newtonian fluids only
• Forced convection
4. Forced Convection
Pr
Re
Nu N
,
N
f
N
k
hD
NNu = Nusselt number
NRe = Reynold number
NPr = Prandtl number
μ
D
u
ρ
_
k
μcp
5. (4.
38)
100,
L
D
N
N Pr
Re
14
.
0
w
b
66
.
0
Pr
Re
Pr
Re
Nu
L
D
N
N
045
.
0
1
L
D
N
N
085
.
0
3.66
N
Larminar flow in pipes
NRe < 2100
For
b = bulk, w = wall
8. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
41)
imeter
wetted per
area
free
4
De
(4.
42)
70,000
N
1
400
N
6
.
0
3
1
Pr
0.5
Re
Nu
Re
Pr
for
N
0.60N
2
N
11. Example
• Water flowing at 0.02 kg/s is heated from 20 to 60 C
in a horizontal pipe (D = 2.5 cm). Inside T = 90 C.
Estimate h if the pipe is 1 m long.
– Average T = (20+60)/2 = 40 C
– = 992.2 kg/m3, cp = 4.175 kJ/kg C
– k = 0.633 W/m C, = 658.026 x 10-6 Pa.s
– NPr = cp/k = 4.3, w is at 90 C
12. D
m
D
u
N
.
_
Re
4
= 1547.9 laminar flow
)
025
.
0
)(
3
.
4
)(
9
.
1547
(
)
( Pr
Re
L
D
N
N
= 166.4 > 100
NNu = 11.2
14
.
0
6
6
Nu
10
909
.
308
10
026
.
658
33
.
0
)
4
.
166
(
86
.
1
N
16. • If temperature of fluid in pipe is higher
– Heat flows to outside
– Ti > T
Ui = overall heat transfer coefficient
based on inside area
T
-
T
A
U
q i
i
i
17. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
1
i
i
i T
-
T
A
h
q
1
2
2
1
lm
r
-
r
T
-
T
A
k
q
T
-
T
A
h
q 2
0
0
Convection from inside
Conduction
Convection to outside
18. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
48)
l
i
i
i
T
-
T
A
h
q
(4.
49)
2
l
lm
1
2
T
-
T
A
k
r
-
r
q
(4.
50)
T
-
T
A
h
q
2
0
0
19. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
51)
T
-
T
A
U
q
i
i
i
(4.
52)
0
0
lm
1
2
i
i
i
i A
h
q
A
k
r
-
r
q
A
h
q
A
U
q
(4.
53)
0
0
lm
1
2
i
i
i
i A
h
1
A
k
r
-
r
A
h
1
A
U
1
(4.
20. Example
• A steel pipe (k = 43 W/mC) inside D = 2.5 cm, 0.5
cm thick, conveys liquid food at 80 C. Inside h = 10
W/m2C. Outside temp = 20 C, outside h = 100
W/m2C. Calculate overall heat transfer coefficient
and heat loss from 1 m length of pipe.
0
0
lm
1
2
i
i
i
i A
h
1
A
k
r
-
r
A
h
1
A
U
1
o
o
i
lm
i
i
o
i
i r
h
r
kr
)r
r
(r
h
1
U
1
21. – ro = 0.0175 m
– Ri = 0.0125 m
– rlm = 0.01486 m
– 1/Ui = 0.10724 m2 C/W
– Ui = 9.32 W/m2 C
• Heat loss
– q = UiAi(80 – 20)
– = 43.9 W
• Uo = 6.66 W/m2 C
– q = 43.9 W
22. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
6.Role of Insulation in Reducing Heat Loss from
Process Equipment
(4.
55)
Lh
r
2
1
r
r
ln
Lk
2
l
T
-
T
q
0
0
i
0
i
(4.
56)
0
r
h
k
-
r
l
r
h
k
r
r
ln
T
-
T
kL
2
-
dr
dq
2
0
0
0
2
0
0
i
0
b
i
0
23. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
57)
0
r
h
k
-
r
l
2
0
0
0
(4.
58)
0
c
h
k
r
24. Design of a Tubular Heat Exchanger
• Determine desired heat-transfer area for a given
application. Assuming
– Steady-state conditions
– Overall heat-transfer coefficient is constant
throughout the pipe length
– No axial conduction of heat in metal pipe
– Well insulated, negligible heat loss
25. (4.
59)
i
overall
i dA
T
U
dq
(4.
60)
i
c
h
i
h
ph
h
c
pc
c
q dA
T
-
T
U
dT
c
m
dT
c
m
d
(4.
61)
q
T
-
T
dq
T
d l
2
Design of Tubular Heat Exchanger
• Heat transfer from one fluid to another
• Energy balance for double-pipe heat exchanger
27. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
62)
q
T
-
T
1 l
2
i
i dA
T
d
T
U
(4.
63)
i
2
l
A
0
i
l
2
T
T
i
dA
q
T
-
T
T
T
U
1
Slope of T line
28. CHAPTER 3 HEAT TRAMSFER IN FOOD PROCESSING
(4.
64)
l
2
l
2
i
i
T
T
ln
T
-
T
A
U
q
(4.
65)
difference
rature
mean tempe
log
T
T
ln
T
-
T
l
2
l
2
29. Example
• A liquid food (Cp = 4.0 kJ/kgC) flows in inner pipe
of heat exchanger. The food enters at 20 C and exits
at 60 C. Flow rate = 0.5 kg/s. Hot water at 90 C enters
and flows countercurrently at 1 kg/s. Average Cp of
water is 4.18 kJ/kgC.
– Calculate exit temp of water
– Calculate log-mean temperature difference
– If U = 2000 W/m2C and Di = 5 cm calculate L.
– Repeat calculations for parallel flow.