Centrifugal compressors use an impeller to impart centrifugal force on gases, increasing pressure. They have three main parts: an impeller, diffuser, and volute casing. The impeller increases gas velocity and converts it to pressure rise. Diffusers then slow gases while further raising pressure. Compressor performance is defined by efficiency curves showing how pressure, mass flow, and surge/choke lines vary with speed. Optimal design balances impeller inlet/outlet geometry, vane angles, and diffuser design to maximize pressure rise and efficiency.
SAIF ALDIN ALI MADIN
سيف الدين علي ماضي
S96aif@gmail.com
Presentation
on
Axial Flow Compressor
Introduction
Construction
Working
Design
Main Parts
Stalling
Surging
Stage Losses
Advantages - Disadvantages & Applications
SAIF ALDIN ALI MADIN
سيف الدين علي ماضي
S96aif@gmail.com
Presentation
on
Axial Flow Compressor
Introduction
Construction
Working
Design
Main Parts
Stalling
Surging
Stage Losses
Advantages - Disadvantages & Applications
Unit 5- balancing of reciprocating masses, Dynamics of machines of VTU Syllabus prepared by Hareesha N Gowda, Asst. Prof, Dayananda Sagar College of Engg, Blore. Please write to hareeshang@gmail.com for suggestions and criticisms.
Rotating equipment maintenance.
PUMPS
COMPRESSORS
AGITATORS
FANS / BLOWERS
TURBINES
VACUUM PUMPS
VALVES
Type of Seals
Stuffing
SINGLE MECHANICAL SEAL Pusher Type
Bellows Mechanical Seal
Double Mechanical Seal
Bearings are the simple machine components that used to constrain the rotational motion of rotational components of Thrust Bearingsa machine and reduce the friction between the stationary and movable parts. Copy the link given below and paste it in new browser window to get more information on Thrust Bearings:- http://www.transtutors.com/homework-help/mechanical-engineering/thrust-bearings.aspx
Unit 5- balancing of reciprocating masses, Dynamics of machines of VTU Syllabus prepared by Hareesha N Gowda, Asst. Prof, Dayananda Sagar College of Engg, Blore. Please write to hareeshang@gmail.com for suggestions and criticisms.
Rotating equipment maintenance.
PUMPS
COMPRESSORS
AGITATORS
FANS / BLOWERS
TURBINES
VACUUM PUMPS
VALVES
Type of Seals
Stuffing
SINGLE MECHANICAL SEAL Pusher Type
Bellows Mechanical Seal
Double Mechanical Seal
Bearings are the simple machine components that used to constrain the rotational motion of rotational components of Thrust Bearingsa machine and reduce the friction between the stationary and movable parts. Copy the link given below and paste it in new browser window to get more information on Thrust Bearings:- http://www.transtutors.com/homework-help/mechanical-engineering/thrust-bearings.aspx
ABSTRACT
Heat/light/electrical energy is out today’s necessity and has scarcity also. Energy conservation is key requirement of any industry at all times.
In general, industries use heat energy for conservation of raw material to finished product. The source of heat energy is generally saturated or super heated steam. The steam generation is common use one boiler with carity of fuels. Whatever may be the fuel the generation should be as economy as possible which adds to the product cost. Further the usage of steam and recycling steam condensate back to boiler is an art depending on plant layouts.
In this project the steam generator is water tube boiler fired with rice husk. The steam is transferred to the tyre/tube moulds where tyres/tubes are cured while the heat is rejected to the tyres the condensate forms and this condensate is put back to the boiler. While doing so the steam is also stopped back to boiler without rejecting complete heat to the product. This gets flashed into atmosphere at feed water tank. The science of separation of condensate from steam saves energy. Better the separation more the fuel conservation.
In the steam generator the fuel is burnt to heat the water and form steam. This fuel burnt flue gas carries lot of energy, out through chimney. Prior to exhausting through the heat left in flue need to be recovered, through heat recovery mechanisms’. In this project an air-preheater condensate heat recovery unit is the major energy consuming station.
Heat/light/electrical energy is out today’s necessity and has scarcity also. Energy conservation is key requirement of any industry at all times.
In general, industries use heat energy for conservation of raw material to finished product. The source of heat energy is generally saturated or super heated steam. The steam generation is common use one boiler with carity of fuels. Whatever may be the fuel the generation should be as economy as possible which adds to the product cost. Further the usage of steam and recycling steam condensate back to boiler is an art depending on plant layouts.
In this project the steam generator is water tube boiler fired with rice husk. The steam is transferred to the tyre/tube moulds where tyres/tubes are cured while the heat is rejected to the tyres the condensate forms and this condensate is put back to the boiler. While doing so the steam is also stopped back to boiler without rejecting complete heat to the product. This gets flashed into atmosphere at feed water tank. The science of separation of condensate from steam saves energy. Better the separation more the fuel conservation.
In the steam generator the fuel is burnt to heat the water and form steam. This fuel burnt flue gas carries lot of energy, out through chimney. Prior to exhausting through the heat left in flue need to be recovered, through heat recovery mechanisms’. In this project an air-preheater condensate heat recovery unit is the major energy consuming station.
Rudder Control Analysis / Hydraulic Pump AnalysisAndrè G. Odu
The objective of the lab is to analyze the performance of a hydraulic pump, responsible for the transfer of fluid between two tanks at a constant flow, in function of its rotational speed.
As the RPM vary from 0 to 4000 we are mainly interested in studying the speed, flow rate and pressures when entering and exiting the pump, the coefficient of head losses associated with the delivery duct, the required hydraulic power and the hydraulic power generated.
As the lab progresses, we find ourselves needing to solve the problem of cavitation that manifests itself in the aspiration duct, and are asked to calculate the plate angle of orientation when the cylinders are placed along a circumference with diameter of 60mm.
The objective of the lab is to analyze the operativity of an actuator used to control the movements of an Airbus A320 rudder.
The Airbus A320 uses three actuators with double redundancy, each of which is designed to control the mobile surface independently.
Given the opposing moment that must be overcome we can calculate the muscular force required to control the mobile surface, from which we can determine the dimensional specifics for the actuator that will be introduced, the equations of operation and the approximate time required to complete the movement.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
4. Introduction
• Slightly less efficient than axial-flow compressors
• Easier to manufacture
• Single stage can produce a pressure ration of 5 times that of a
single stage axial-flow compressor
• Application: ground-vehicle, power plants, auxiliary power units
• Similar parts as a pump, i.e. the impeller, the diffuser, and the
volute
• Main difference: enthalpy in place of pressure-head term
• Static enthalpy (h) and total (stagnation) enthalpy (ho)
4
8. Introduction
• For an ideal gas with constant specific heat
2
V
h0 = h +
2
kRT T0
V = 2( h0 − h ) = 2C p ( T0 − T ) = 2
− 1
k −1 T
2
c = kRT
2
8
9. Introduction
• For an ideal gas with constant specific heat
2
2c T0
V =
− 1
k −1 T
2
V
2 T0
2
=M =
− 1
2
c
k −1 T
T0
k −1 2
= 1+
M
T
2
2
9
10. Introduction
• For an isentropic process
T0
T
k ( k −1 )
T0
T
p0
= ,
p
p0 ( k − 1) 2
= 1 +
M
p
2
ρ 0 ( k − 1) 2
= 1 +
M
ρ
2
1 ( k −1 )
ρ0
=
ρ
k ( k −1 )
1 ( k −1 )
10
11. Introduction
• For the critical state (M=1)
*
T
2
=
T0 k + 1
*
p 2
=
p0 k + 1
ρ 2
=
ρ 0 k + 1
*
k ( k −1 )
1 ( k −1 )
11
15. Introduction
• Compressor Efficiency:
– The ratio of the useful increase of fluid energy divided by the
actual energy input to the fluid
– The useful energy input is the work of an ideal, or isentropic,
compression to the actual final pressure P3
15
16. Introduction
Ei = hi − h01 = C pT01 [ Ti T01 − 1]
p
03
= C pT01
p01
( k −1)
k
− 1
16
17. Introduction
• The Compressor Efficiency
Ei Ti − T01
ηc = =
E T03 − T01
• No external work or heat associated with the diffuser
flow, i.e.
h02 = h03 ,
T02 = T03
17
18. Introduction
• The Overall Pressure Ratio
p03 U 2Vt 2'η c
= 1 +
p01 C pT01η m
k k −1
• The compressor efficiency from experimental data
• Slip exists in compressor impeller
Vt 2 ' = µ sVt 2
18
19. Introduction
• The Slip Coefficient (Stanitz Equation)
0.63π
µ s = 1−
nB
1
1 − ϕ 2 cot β 2
• More relations in Appendix E
• But, Stanitz equation is more accurate for the practical
range of vane angle; i.e.
45 < β 2 < 90
0
0
19
20. Introduction
• Total pressure ratio from:
–
–
–
–
Ideal velocity triangle at the impeller exit
The number of vanes
The inlet total temperature
The stage and mechanical efficiencies
• Mechanical efficiency accounts for
– Frictional losses associated with bearing, seal, and disk
friction
– Reappears as enthalpy in the outflow gas
20
21. Impeller Design
• The impeller design starts with a number of
unshrouded blades (Pfleiderer)
• Flow is assumed axial at the inlet
• Favorable to have large tangential velocity at outlet
(Vt2’)
• Vanes are curved near the rim of the impeller ( β2 <90o)
• But, they are bent near the leading edge to conform to
the direction of the relative velocity Vrb1 at the inlet
21
22. Impeller Design
• The angle β1 varies over the leading edge, since V1
remains constant while U1 (and r) varies (V1 assumes
uniform at inlet)
• At D1S, the relative velocity Vrb1=(V12+U12)0.5 and the
corresponding relative Mach number MR1S are highest
• For a fixed set of, N, m,Po1, and To1, the relative Mach
number has its minimum where β1S is approximately
32o (Shepherd, 1956)
22
23. Impeller Design
• Choose a relative Mach number at the inlet
Vrb1S = M R1S a1
Acoustic Speed :
Static Temperature :
a1 = kRT1
T1 =
Absolute inlet Mach no :
T01
1 + ( k − 1) M 12 2
V1
M 1 = = M R1S sin β1S
a1
23
24. Impeller Design
• Calculation of V1 and U1S
V1 = Vrb1S sin 32
0
U1S = Vrb1S cos 32
0
• Calculation of the shroud diameter
2U1S
D1S =
N
24
25. Impeller Design
• Calculation of the hub diameter by applying the mass
flow equation to the impeller inlet
D1H
2
4m
= D1S −
πρ1V1
1
2
• Calculation of density from the equation of state of a
perfect gas
p1
ρ1 =
RT1
25
26. Impeller Design
• Calculation of static temperature and static pressure
T01
T1 =
2
1 + ( k − 1) M 1 2
p01
p1 =
2
1 + ( k − 1) M 1 2
k ( k −1)
26
27. Impeller Design
• The fluid angle at the hub
β1H
V1
= tan
U
1H
−1
• The vane speed at the hub
U 1H
ND1H
=
2
27
28. Impeller Design
• The outlet diameter D2
&
Inlet flow rate: Q1 = m ρ1
Output head H:
H = Ei g
1
Dimensional specific speed:
Ns =
NQ1 2
H
3
4
1
D2 =
DS Q1 2
H
1
4
(DS from Table 3 in appendix A)
28
29. Impeller Design
• The ideal and actual tangential velocities
From Table 3 in appendix A :
ηC
η m Ei
The Energy transfer :
E=
ηC
The actual tangential velocity : Vt 2 ' = E U 2
Vt 2 '
( µ s = 0.85 − 0.9)
The ideal tangential velocity : Vt 2 =
µs
29
30. Impeller Design
• The vane angle and the number of vanes
Vrb 2t = U 2 − Vt 2
( 0.23 ≤ ϕ 2 ≤ 0.35)
Vrb 2 n = ϕ 2U 2
Vrb 2 n
β 2 = tan
Vrb 2t
−1
0.63π
µs = 1 −
nB
1
1 − ϕ cot β
2
2
30
32. Impeller Design
• The static temperature T2 is used to determine density
at the impeller exit
2
2′
V
T2 = T02 −
2C p
&
m
b2 =
2πρ 2 r2V2 n
32
33. Impeller Design
• The optimal design parameters by Ferguson (1963)
and Whitfield (1990) from Table 5.1
• Table 5.1 Should be used to check calculated results
for acceptability during or after the design process
33
34. Diffuser Design
• A vaneless diffuser allows reduction of the exit Mach number
• The vaneless portion may have a width as large as 6 percent of
the impeller diameter
• Effects a rise in static pressure
• Angular momentum is conserved and the fluid path is
approximately a logarithmic spiral
• Diffuser vanes are set with the diffuser axes tangent to the
spiral paths with an angle of divergence between them not
exceeding 12o
34
36. Diffuser Design
• Vanes are preferred where size limitations matter
• Vaneless diffuser is more efficient
• Number of diffuser vanes should be less than the number of
impeller vanes to:
– Ensure uniformness of flow
– High diffuser efficiency in the range of φ2 recommended
36
37. Diffuser Design
• The mass flow rate at any r (in the vaneless diffuser)
( r2 ≤ r ≤ r3 )
Vr = Vn
&
m = 2πrbρVn
37
38. Diffuser Design
• For constant diffuser width b
ρrVn = constant
ρrVn = ρ 2 r2Vn 2
• The angular momentum is conserved in the vaneless space
rVt = r2Vt 2′
38
39. Diffuser Design
• Typically, the flow leaving the impeller is supersonic
M 2′ > 1
• Typically, the flow leaving the vaneless diffuser is subsonic
M 3 < 1.0
39
40. Diffuser Design
• Denote * for the properties at the radial position at which M=1
(The absolute gas angle, α, is the angle between V and Vr)
Vr = Vn = V cos α
• The continuity equation
ρrV cos α = ρ r V cos α
* *
*
*
40
41. Diffuser Design
• The angular momentum equation
rV sin α = r V sin α
*
*
*
• Dividing momentum by continuity relations
tan α tan α
=
*
ρ
ρ
*
41
42. Diffuser Design
• Assuming an isentropic flow in the vaneless region
T ρ
= *
*
ρ
T
• For M=1
k −1
,
T0
T=
k −1 2
1+
M
2
2T0
T =
k +1
*
42
43. Diffuser Design
• Substituting in the density relation
ρ 2 k − 1 2
=
M
1 +
*
ρ
2
k +1
1 ( k −1)
• Substituting in the absolute gas angle relation
2 k − 1 2
tan α = tan α
M
1 +
2
k +1
−1 ( k −1)
*
43
44. Diffuser Design
• The angle α* is evaluated by
α = α 2′
M = M 2′
r sin α
V V a
T
= *=
= M *
*
r sin α
V
aa
T
*
*
1
2
2 k − 1 2
r sin α
=M
M
1 +
r sin α
2
k +1
*
*
−1 2
44
45. Diffuser Design
• The radial position r* is determined by
2 k − 1 2
r sin α
= M 2′
M 2′
1 +
r2 sin α 2
2
k +1
*
*
−1 2
• The angle α3* is evaluated by
2 k − 1 2
tan α 3 = tan α
M 3
1 +
2
k +1
−1 ( k −1)
*
45
46. Diffuser Design
• Finally r3 is determined by
2 k − 1 2
r sin α
= M3
M 3
1 +
r3 sin α 3
2
k +1
*
*
−1 2
• The volute is designed by the same methods outlined in
chapter 4
46
48. Performance
• The sharp fall of the constant-speed curves at higher mass
flows is due to choking in some component of the machine
• The low flows operation is limited by the phenomenon of surge
• Smooth operation occurs on the compressor map at some point
between the surge line and the choke line
• Chocking is associated with the attainment of a Mach number
of unity
48
49. Performance
• In the stationary passage of the inlet The sharp fall of the
constant-speed curves at higher mass flows is due to choking in
some component of the machine
• The low flows operation is limited by the phenomenon of surge
• Smooth operation occurs on the compressor map at some point
between the surge line and the choke line
• Chocking is associated with the attainment of a Mach number
of unity
49
50. a=
Performance
• In the stationary passage of the inlet or diffuser for a Mach
number of unity
a = kRT
• The temperature at this point
( k − 1) 2
T = T0 1 +
M
2
50
51. a=
Performance
• By setting M=1
2
T = T0
= Tt
k + 1
*
• The chocking (maximum) flow rate
1
k
&
m = At pt
÷
RTt
2
51
52. a=
Performance
• The throat pressure (isentropic process)
k ( k −1)
Tt
pt = pin ÷
Tin
• The chocked flow rate in impeller (use relative velocity instead
of absolute velocity)
2
rb1
2
1
V
U
h01 = h +
−
2
2
52
53. a=
Performance
• The critical temperature
U 2 2T01
T * = 1 +
= Tt
÷
2C pT01 ÷( k + 1)
• The throat mass flow rate (isentropic process)
1
( k +1)
2( k −1)
2
2
k
U
&
m = At p01
1 +
÷
÷
RT01 k + 1 2C pT01 ÷
2
53
54. Performance
• The chocked mass flow rate in stationary components is
independent of impeller speed
• The point A in the characteristic curve represents a point of
normal operation
• An increase in flow resistance in the connected external flow
system results in decrease in
and increase in Vn 2
Vt 2
• Causes increase in head or pressure
• Further increase in external system produces a decrease in
impeller flow (beyond point C) and surge phenomena results
54
55. Performance
• The at some point in the impeller leads to change of direction of
Vrb 2
and an accompanying decrease in head.
• A temporary flow reversal in the impeller and the ensuing
buildup to the original flow condition is known as surging.
• Surging continues cyclically until the external resistance is
removed.
• Surging is an unstable and dangerous condition and must be
avoided by careful operational planning and system design.
55