This was the seminar presentation on my Project report for M.Sc. Degree.
This shows basic and application of Electric propulsion.Which also shows about how electric propulsion is better than chemical propulsion.
This was the seminar presentation on my Project report for M.Sc. Degree.
This shows basic and application of Electric propulsion.Which also shows about how electric propulsion is better than chemical propulsion.
Cryogenics is the study of the operations at very low temperature (below −150 °C, −238 °F or 123 K) and the behaviour of materials at these temperatures.
Cruise missiles form a major part of modern warfare and have spread extensively to all branches of the military. Their effective use in a modern conflict can change the outcome of war without resorting to nuclear weapons. Improvements in cruise missile technology will see more intelligent, self-manoeuvring and hypersonic missiles flood the world market. But whatever happens, cruise missiles will remain one of the most reliable weapons for the foreseeable future.
Unmanned Aerial Vehicles (UAVs) are aircrafts that fly without any humans being onboard. They are either remotely piloted, or piloted by an onboard computer. This kind of aircrafts can be used in different military missions such as surveillance, reconnaissance, battle damage assessment, communications relay, minesweeping, hazardous substances detection and radar jamming. However they can be used in other than military missions like detection of hazardous objects on train rails and investigation of infected areas. Aircrafts that are able of hovering and vertical flying can also be used for indoor missions like counter terrorist operations.
about scramjets, its components, function, its advantages and advantages, its applications with many references by reshmi.r , dinesh kumar and sandeep.
Cryogenics is the study of the operations at very low temperature (below −150 °C, −238 °F or 123 K) and the behaviour of materials at these temperatures.
Cruise missiles form a major part of modern warfare and have spread extensively to all branches of the military. Their effective use in a modern conflict can change the outcome of war without resorting to nuclear weapons. Improvements in cruise missile technology will see more intelligent, self-manoeuvring and hypersonic missiles flood the world market. But whatever happens, cruise missiles will remain one of the most reliable weapons for the foreseeable future.
Unmanned Aerial Vehicles (UAVs) are aircrafts that fly without any humans being onboard. They are either remotely piloted, or piloted by an onboard computer. This kind of aircrafts can be used in different military missions such as surveillance, reconnaissance, battle damage assessment, communications relay, minesweeping, hazardous substances detection and radar jamming. However they can be used in other than military missions like detection of hazardous objects on train rails and investigation of infected areas. Aircrafts that are able of hovering and vertical flying can also be used for indoor missions like counter terrorist operations.
about scramjets, its components, function, its advantages and advantages, its applications with many references by reshmi.r , dinesh kumar and sandeep.
This is an extended version of a talk given originally at the 2nd International Conference on Entrepreneurial Engineering: Commercialization of Research and Projects at IOBM, Karachi. Later an extended talk was given on several campuses in the city.
RPA (Robotic Process Automation), Current Job Market Situation, What exactly is RPA?, Why RPA?, Future is Now, Who are looking forward to hire you, Job orienetd course,RPA tools, Blur Prism, Uipath, Automation Anywhere
www.meritas.in
Applying Robotic Process Automation in Banking: Innovations in Finance and Riskaccenture
Robotics is quickly gaining traction in banks to automate their everyday finance and risk processes. Accenture's presentation covers the impact of Robotic Process Automation (RPA) on a bank's finance and risk function. Read Philippe Guyonnet’s blog to learn more about RPA in banking and finance and risk innovation:http://bit.ly/2dprACR
There are 5 types of jet propulsion engine such as turbojet, turbofan, turboprop, turbo-shaft, and ramjet.Some types of jet propulsive engine are not cover in this slide such as pulse engine and rocket.
RPA (Rey Performance Auditing) is an Excel templates for performance evaluation of boiler, gas turbine, pump, fan and air compressor base on ASME PTCs.
I'm not the author of this presentation, I'm just sharing it here for better accessibility.
This slideshow was given by Roger Shawyer to NSF (NASA spaceflight forum) member Mullerton for wider distribution.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
call for paper 2012, hard copy of journal, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Acutesoft is a best online center in Hyderabad. We are providing very best online training on Informatica.
Get(100$ off) on INFORMATICA Online Training at AcuteSoft Solutions For more information please contact us.
How to Automate Performance Tuning for Apache SparkDatabricks
Spark has made writing big data pipelines much easier than before. But a lot of effort is required to maintain performant and stable data pipelines in production over time. Did I choose the right type of infrastructure for my application? Did I set the Spark configurations correctly? Can my application keep running smoothly as the volume of ingested data grows over time? How to make sure that my pipeline always finishes on time and meets its SLA?
These questions are not easy to answer even for a handful of jobs, and this maintenance work can become a real burden as you scale to dozens, hundreds, or thousands of jobs. This talk will review what we found to be the most useful piece of information and parameters to look at for manual tuning, and the different options available to engineers who want to automate this work, from open-source tools to managed services provided by the data platform or third parties like the Data Mechanics platform.
conceptual design is a bridge between what is in our mind and what could be in market,the hybrid motor uses propellants in different physical phases and which is more advantageous than solid propellant engines.
Turbofan Engine Modelling and Control Design using Linear Quadratic Regulator...theijes
There are many applications in which gas turbine engine is used today, including aircraft propulsion for both commercial and military purposes, and power generation and in all these Control systems technology has played a fundamental role in enhancing performance. Modelling plays a significant role in the development of the entire engine system performance. This paper investigated Linear Quadratic Regulator (LQR) model-based control method to obtain estimates of performance parameters. The main control variable selected is the fuel flow to control the rotational speed of high-pressure spool speed of the turbofan engine. Firstly a suitable mathematical model of the engine is developed in MATLAB Simulink environment with both the intercomponent volume and the constant mass flow methods used. Equations of the mass flow rate and the torque balance are incorporated in the steady state and dynamic state of the thermodynamic engine model. This represents the engine model by a set of first-order differential and algebraic equations and a linearized model is extracted for the analysis and design of a controller by LQR. It is demonstrated that LQR based controllers can perform better than conventional PID controllers. The settling time, rise time and maximum overshoot for LQR based controller are all less than those for PID based controller. The input also changes more accurately for LQR than the PID controller compared.
AFT Arrow apresenta capacidades abrangentes para análise de fluxo de fluidos compressíveis e modelagem de sistemas, combinadas à sua facilidade de uso, desde a construção de modelos através do método drag-and-drop até a completa personalização dos dados de saída. Além da possibilidade de análise de sistemas abertos e fechados, o AFT Arrow inclui uma biblioteca de fluidos e componentes, capacidade de modelagem de ventilador/compressor, de válvula de controle e muito mais. O software vai além dos padrões das análises tradicionais de fluxo de fluido, com capacidades de análises térmicas, incluindo transferência de calor na tubulação, modelagem de trocadores de calor e variação das propriedades dos fluidos.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
2. Motivation
RPA is being developed to...
●
●
●
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Provide modern multi-platform tool for prediction of rocket
engine performance at the conceptual and preliminary
stages of design
Capture impacts on engine performance due to variation
of design parameters
Assess the parameters of main engine components
(thrust chamber, turbopump, gas generator/preburner) to
provide better data for detailed analysis/design
Assist in education of new generation of propulsion
engineers
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
3. RPA Overview
Main features of RPA (1)
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●
●
●
●
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Gibbs free energy minimization approach is used to
obtain the combustion composition
Expandable thermodynamic data library based on NASA
Glenn thermodynamic database (also used by CEA)
Analysis of nozzle performance with shifting and frozen
chemical equilibrium
Optimization of propellant components mixture ratio
Altitude performance analysis, over-expanded nozzle
performance analysis
Throttled engine performance analysis
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
4. RPA Overview
Main features of RPA (2)
●
●
●
Estimation of delivered (actual) nozzle performance
Determination of combustion chamber size for given
thrust, propellant mass flow rate, or throat diameter
Designing parabolic nozzle contour or truncated ideal
nozzle contour (TIC) using two-dimensional
(axisymmetric) method of characteristics
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
5. RPA Overview
Main features of RPA (3)
●
Thrust chamber thermal analysis
–
Calculation of heat transfer rate distribution
(convection and radiation)
–
Film cooling analysis
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Radiation cooling analysis
–
Regenerative cooling analysis
–
Thermal analysis of thrust chambers with combined
cooling: radiation + film + regenerative
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Estimation of hydraulic losses in the cooling passages
–
Estimation of friction thrust loss
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
6. RPA Overview
Main features of RPA (4)
●
●
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Multi-platform graphical user interface for Microsoft®
Windows™, as well as for Apple® Mac OS X and Linux
Parameters input and results output in SI or U.S.
customary units
Development tools and libraries are available:
–
Scripting Utility
–
C++ Wrapper
–
C++ SDK for development of commercial software
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
7. RPA Overview
Main features of RPA
Example of GUI:
altitude performance
analysis
1
2
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
8. RPA Overview
How RPA differs from other tools
●
Own implementation of thermodynamics analysis,
whereas many other tools use CEA
●
Availability of development libraries
●
Intended for conceptual and preliminary design
–
Steady-state analysis
–
Simplified model initialization with minimum of input
parameters
–
Wide usage of semi-empirical relations and
coefficients
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
9. RPA Overview
Areas where RPA is usually used
●
Conceptual and preliminary design of rocket engines and
propulsion systems
●
Education and academic research
●
Library for development of commercial software
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
10. Models and methods used in RPA
Rocket engine performance analysis
●
Method of minimization of Gibbs free energy is used
–
to obtain the equilibrium product concentrations from
combustion of two or more propellant components
–
to obtain the equilibrium product concentrations from
decomposition of monopropellant
–
to calculate the isentropic quasi-one-dimensional
nozzle flow for both shifting and frozen equilibrium flow
models
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
11. Models and methods used in RPA
Rocket engine performance analysis
●
●
Expandable thermodynamic data library based on NASA
Glenn thermodynamic database
The library includes data for such propellant components
as
–
–
●
liquid hydrogen H2(L), liquid methane CH4(L), RP-1,
RG-1, Synthine, monomethyl hydrazine (MMH),
unsymmetrical dimethyl hydrazine (UDMH)
Liquid oxygen O2(L), nitrogen tetra-oxide (N2O4),
hydrogen peroxide (H2O2)
User may define own propellant components with known
chemical formula and enthalpy of formation
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
12. Models and methods used in RPA
Rocket engine performance analysis
●
●
Quasi-one-dimensional nozzle flow model
Semi-empirical relations to obtain performance correction
factors, including:
–
Performance loss due finite rate kinetics in combustion
chamber and nozzle
–
Divergence loss
–
Performance loss due to finite-area combustion area
–
Multi-phase flow loss
–
Performance change due to nozzle flow separation
–
Performance change due to thrust throttling
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
13. Models and methods used in RPA
Rocket engine performance analysis
1
2
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
14. Models and methods used in RPA
Thrust chamber sizing
●
●
●
Sizing for required
thrust level at a
specific ambient
condition
Sizing at a specific
propellant mass flow
rate
Sizing for a specific
throat diameter
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
15. Models and methods used in RPA
Designing the nozzle contour
●
Cone nozzle with a specific exit half-angle
●
Parabolic nozzle
●
●
●
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Truncated ideal contour (TIC) with maximum thrust at
fixed expansion ratio
Two-dimensional (axisymmetric) method of
characteristics
Parametric specification of the nozzle inlet geometry
Export of nozzle contour in DXF (drawing interchange file)
format
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
16. Models and methods used in RPA
Design of nozzle contour
●
1
2
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
17. Models and methods used in RPA
Thrust chamber thermal analysis
●
Gas-side heat transfer
–
Convective heat transfer
Ievlev method
● Bartz method
● Boundary layer and film cooling
Loss in specific impulse due to friction in boundary
layer
●
–
–
●
Radiation heat transfer
RPA library for thermodynamic analysis is used to obtain
hot gas transport properties
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
18. Models and methods used in RPA
Thrust chamber thermal analysis
●
Thrust chamber outer cooling
–
Radiation cooling
–
Regenerative cooling
–
Coaxial-shell thrust chamber design
● Channel-wall thrust chamber design
● Tubular-wall thrust chamber Design
● Pressure loss across cooling passages
● Coolant properties are interpolated from 2D
properties file (can be obtained from REFPROP)
Thermal barrier coating layer
–
Balanced heat flux approach
●
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
19. Models and methods used in RPA
Thermal analysis:
example of input data
1
2
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
20. Models and methods used in RPA
Thermal analysis:
example of output data
3
4
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
21. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Steady-state analysis
●
Variety of cycles:
–
gas generator
–
staged combustion
–
full-flow staged combustion
–
expander
–
tap-off
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
22. Models and methods used in RPA
Engine cycle analysis (to be released)
●
General input parameters:
–
Number and type of combustion devices (fuel-rich or
oxidizer-rich)
–
Maximum turbine inlet temperature
–
Number and flow sequence of turbines
–
Inlet pressure of propellant components
–
Availability of booster pumps and their parameters
–
Type and parameters of turbine of booster pumps
–
Availability of kick pumps and their parameters
–
Availability of bypasses around turbines
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
23. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Design mode possible input parameters:
–
–
●
Thrust chamber pressure, mass flow rate and mixture
ratio
Pressure drop at valves, junctions, cooling jackets etc
Design mode possible results:
–
Operational parameters of combustion devices
(pressure, mass flow rate and mixture ratio)
–
Operational parameters of turbomachinery (mass flow
rate, inlet pressure, discharge pressure, shaft power)
–
Engine overall performance
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
24. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Off-design mode possible input parameters:
–
–
Operational parameters of turbomachinery (mass flow
rate, inlet pressure, discharge pressure, shaft power)
–
●
Operational parameters of combustion devices
(pressure, mass flow rate and mixture ratio)
Pressure drop at valves, junctions, cooling jackets etc
Off-design mode possible results:
–
Thrust chamber pressure, mass flow rate and mixture
ratio
–
Engine overall performance
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
25. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Analysis flowchart
Pc
Ae/At
thrust
Flow diagram
Decompose the diagram into
feed subsystems and
power subsystems
Obtain chamber
performance and size
Boundary conditions:
inlet/discharge pressure,
mass flow rate
Stop
Guess
controlling
parameters
Yes
Do
interface
parameters fit
to each
other?
Solve power subsystems:
find turbine parameters
to fit required pump power
No
Correct controlling
parameters
RPA – Tool for Rocket Propulsion Analysis
Solve feed subsystems:
find pump power required to
fit boundary conditions
Boundary conditions:
feed subsystems
discharge pressure and
mass flow rate
www.propulsion-analysis.com
26. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Example of flow diagram decomposition
SSME
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
27. Models and methods used in RPA
Engine cycle analysis (to be released)
●
Example of flow diagram decomposition
LOX feed and power subsystems
Solving feed subsystem:
find such pump power that
the required pressure is
achieved at exit port of
each branch
Solving power subsystem:
find such parameters of
combustion device and/or
turbine that produced
power is equal to required
total pump power of the
feed subsystem
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
28. Models and methods used in RPA
Engine cycle analysis (to be released)
●
RPA thermodynamics module is used to obtain
–
–
●
O/F ratio in combustion device to achieve required
combustion temperature
Parameters of gas turbine working fluid in all cycles
(GG, staged combustion and expander)
RPA thermal analysis module can be used to obtain
–
Pressure drop in coolant jacket
–
Amount of energy absorbed by the coolant (one of
controlling parameters in expander cycle)
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
29. Models and methods used in RPA
Engine weight estimation (to be released)
●
●
●
●
Based on the set of semi-empirical equations for each
major type of engines: gas generator, staged combustion
and expander cycles
Initially developed at Moscow Aviation Institute
RPA utilizes this method with slightly modified coefficients
to better fit the available data on historic engines
Results of chamber sizing and cycle analysis can be used
as an input parameters of engine weight estimation
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
30. Test cases
Chemical equilibrium properties
●
Comparison with a NASA equilibrium program CEA has
been performed for selected test cases:
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
31. Test cases
Chemical equilibrium properties
●
Comparison for Case #1 (LOX/LH2):
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
32. Test cases
Chemical equilibrium properties
●
Comparison for Case #2 (LOX/RP-1):
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
33. Test cases
Chemical equilibrium properties
●
Comparison for Case #3 (N2O4/UDMH):
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
34. Test cases
Chemical equilibrium properties
●
Comparison for Case #4 (N2H4):
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
35. Test cases
Chemical equilibrium properties
●
Comparison for Case #5 (H2O2 80%):
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
36. Test cases
Chemical equilibrium properties
●
●
●
A perfect agreement is obtained between the CEA and
PRA programs
Any percent differences in parameter values are in at
least the third decimal place and are negligibles
The maximum relative difference is 0.002% occurring for
Case #3
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
37. Test cases
Liquid propulsion performance analysis
●
Comparison with a performance data of selected historic
engines has been performed:
–
RD-170
–
RD-253
–
RL10A3-3A
–
SSME
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
42. Test cases
Liquid propulsion performance analysis
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An excellent agreement is obtained between the actual
performance and performance predicted by RPA program
The maximum relative difference occurring for RD-253
Comparison of ideal performance calculated by RPA with
ideal performance calculated by NASA CEA code (not
shown in this presentation) provides an excellent
agreement as well
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
43. Test cases
Solid and hybrid propulsion performance analysis
●
Comparison with a performance data of selected historic
engines has been performed:
–
P80 - first stage engine of VEGA Launcher
–
Hybrid rocket engine for Peregrine sounding rocket
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
44. Test cases
Solid and hybrid propulsion performance analysis
●
P80 - first stage engine of VEGA Launcher
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
45. Test cases
Solid and hybrid propulsion performance analysis
●
Hybrid rocket engine for Peregrine sounding rocket
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
46. Test cases
Solid and hybrid propulsion performance analysis
●
●
RPA obtains the proper combustion composition from any
type of solid/hybrid propellants, including metalized
The obtained agreement between the RPA prediction and
referenced data is sufficient for the tool used in
conceptual and preliminary design
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
47. Test cases
Thermal analysis
●
To verify the accuracy of thermal analysis, the
comparison between available reference data and RPA
prediction has been performed:
–
SSME 40k [1]
–
Aestus [2]
[1] Scaling Techniques for Design, Development, and Test.
Carol E. Dexter, Mark F. Fisher, James R. Hulka, Konstantin P. Denisov,
Alexander A. Shibanov, and Anatoliy F. Agarkov
[2] Simulation and Analysis of Thrust Chamber Flowfields: Storable Propellant Rockets.
Dieter Preclik, Oliver Knab, Denis Estublier, and Dag Wennerberg
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
50. Test cases
Thermal analysis
●
●
The obtained agreement between the RPA prediction and
referenced data is sufficient for the tool used in
conceptual and preliminary design
Quantitative and qualitative differences in results can be
explained by the following:
–
RPA does not simulate fuel atomization and
dispersion, as well as droplets burning
–
The hot gas properties for thermal analysis are
retrieved from quasi one-dimensional flow model
–
The heat transfer is simulated in RPA using semiempirical relations
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
51. Test cases
Cycle analysis and weight estimation
●
Validation to be performed
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
52. Architecture of RPA
Architecture of RPA
●
●
●
●
Written in C++
Can be compiled on MS Windows, Linux and Apple
MacOS X
Shared (Linux/MacOS X) and dynamic (Windows)
libraries provide functionality
Executable file provides GUI and is created with Qt
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
53. Architecture of RPA
Architecture of RPA
●
Available shared/dynamic libraries:
–
Libutils
Utility classes (exceptions, logging, etc)
–
Libmath
Classes for solving equations, linear
systems, etc.
–
Librpa
Thermodynamics
–
Libnozzle
Chamber and nozzle sizing and geometry
–
Libthermo
Thermal analysis
–
Libdesign
Cycle analysis and weight estimation
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
54. Architecture of RPA
Architecture of RPA
●
Third-party libraries:
–
–
–
–
Qt
Application and GUI framework
Qwt
http://qt-project.org
GUI components for 2D plotting
Eigen
http://qwt.sourceforge.net
C++ template library for linear algebra
Libconfig
http://eigen.tuxfamily.org
C++ library for processing structured
configuration files
http://www.hyperrealm.com/libconfig
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
55. Future development
Future development
●
●
Release of RPA 2.1 with cycle analysis and weight
estimation
Development of wrapper C++ classes to make the usage
of cycle analysis easier and release of the next version
RPA SDK
●
Solid-propellant grain design
●
Design of thrust-optimized nozzle contour (TOC)
●
Implement better integration of available RPA libraries
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com
56. References to RPA reports
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●
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Ponomarenko A. RPA: Tool for Liquid Propellant Rocket
Engine Analysis. 2010.
Ponomarenko A. RPA: Tool for Liquid Propellant Rocket
Engine Analysis. Thermal Analysis of Thrust Chambers.
2012.
Ponomarenko A. RPA: Tool for Liquid Propellant Rocket
Engine Analysis. Assessment of Delivered Performance
of Thrust Chamber. 2013.
Ponomarenko A. RPA: Tool for Liquid Propellant Rocket
Engine Analysis. Power Balance Analysis and Weight
Estimation of Liquid-Propellant Rocket Engine Cycles.
2013. DRAFT
RPA – Tool for Rocket Propulsion Analysis
www.propulsion-analysis.com