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This document provides specifications for a gas turbine engine, including a compressor inlet temperature of 27°K and pressure of 100 kPa, a combustor outlet temperature of 1750°K and pressure of 7.5 MPa, and a turbine inlet temperature of 450°C at 500 kPa pressure. The engine has a mass flow rate of 500 MW and a compressor pressure ratio of 16.
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Example 12.1
It's Specially for petroleum department
Refining
Condenser
Under supervision: Dr.Tarek Aboul Fotoh
Factores de conversión
This document provides conversion factors for various units of measurement related to mass and density, length, area, volume, force, pressure, energy, temperature, and specific volume. Some key conversions include:
1 kg = 2.20462 lbs, 1 m = 3.28084 ft, 1 cal = 4.1868 kJ, 1 kWh = 3412.14 Btu, 1 hp = 0.7457 kW, 1 kJ/kg = 0.42992 Btu/lb.
The document covers conversions between metric and imperial units for several physical quantities important for engineering such as force, pressure, power, heat, and temperature.
Probs5,11,17
The document provides details on two problems involving heat exchanger design and optimization. Problem 11 involves designing a condenser to condense 2000 kg/hr of vapor at 132°C using cooling water. The optimal solutions are a cooling water flow rate of 2284.58 kg/hr and an exit temperature of 106.54°C. Problem 17 requires determining the optimal exit temperature and optimal tube length but no other details are provided.
Open and closed thermodynamic system
A fluid enters a steady flow apparatus with a specific volume of 0.40 m3/kg, pressure of 550 kPa, and velocity of 20 m/s, and exits with a specific volume of 0.82 m3/kg, pressure of 100 kPa, and velocity of 280 m/s. The apparatus produces 140 kJ of work per kg and experiences 12 kJ/kg of heat loss. The change in internal energy is determined to be -58.32 kJ/kg.
CH EN 3453 Heat Transfer 2014 Fall Utah Homework HW 08 Assignment
Chemical Engineering CH EN 3453 Heat Transfer
from University of Utah, 2014 Fall
Homework HW 08 Assignment
Jean-Paul Gibson: Analysis Of An Open Feedwater Heater System
People often look surprised when I tell them that Thermodynamics was probably one of my favorite classes in school. This was the final project for my Thermo II class and was intended to be done in groups. I wanted to challenge myself to a near unnecessary limit by completing this entire project myself. The purpose of this project was to determine the optimum operating pressure for the feedwater heater for a power cycle (from a selected problem in the textbook). However the primary focus, and most difficult task, was writing a program in C++ to calculate multiple values for a selected problem in our textbook. I quite literally had to teach myself how to program in C++ well beyond the basics I had learned in an intro class. This program had to be capable of cross referencing multiple reference tables in the back of the book, each having dozens of values which had to be manually typed in. Which reference tables it pulled values from was dependent on the user inputted turbine efficiency and feedwater heater pressure. It easily took me over a month to debug and test this program to ensure it was always going to the correct reference tables to pull data when outputting the calculations it performed.
Update on 7/2/2016: I did attempt to make another program that would allow the user to type in any feedwater heater pressure rather than make a selection from values there was a reference table for in the back of the back. The program used a method of interpolation to obtain all the data needed to perform all the calculations that were outputted. I don't remember the last time I attempted to run that version of the program, but I seem to recall getting impossible answers outputted. This indicated to me that a more complicated method of interpolating values was required, or I just couldn't get it to work correctly. I ultimately decided against pursuing that version of the program any further. Just getting it work correctly with a predefined list of pressures to select from was difficult enough.
AP Physics B Test Exam Solutions
#1. Physics B Exam - 1998 contains multiple choice questions about physics concepts tested on the AP Physics B Exam in 1998.
#2. The document contains 20 questions with basic ideas, solutions, and answers related to mechanics, electricity and magnetism, thermodynamics, and other physics topics.
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Engineering thermodynamics-solutions-manual
SFEE:
W = m[(h2 - h1) - (KE2 - KE1) - (PE2 - PE1)]
State 1: 1 bar, 20°C
h1 = 293.9 kJ/kg
KE1 = 0
PE1 = 0
State 2: 3.5 bar
Use isentropic process with s1 = s2
h2 = 341.4 kJ/kg
KE2 = 0.5*m*(7)^2 = 24.5 kJ/kg
PE2 - PE1 = 0
W = m[(h2 - h1) - (KE2 - KE1)]
= (341.
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Example 12.1
It's Specially for petroleum department
Refining
Condenser
Under supervision: Dr.Tarek Aboul Fotoh
Factores de conversión
This document provides conversion factors for various units of measurement related to mass and density, length, area, volume, force, pressure, energy, temperature, and specific volume. Some key conversions include:
1 kg = 2.20462 lbs, 1 m = 3.28084 ft, 1 cal = 4.1868 kJ, 1 kWh = 3412.14 Btu, 1 hp = 0.7457 kW, 1 kJ/kg = 0.42992 Btu/lb.
The document covers conversions between metric and imperial units for several physical quantities important for engineering such as force, pressure, power, heat, and temperature.
Probs5,11,17
The document provides details on two problems involving heat exchanger design and optimization. Problem 11 involves designing a condenser to condense 2000 kg/hr of vapor at 132°C using cooling water. The optimal solutions are a cooling water flow rate of 2284.58 kg/hr and an exit temperature of 106.54°C. Problem 17 requires determining the optimal exit temperature and optimal tube length but no other details are provided.
Open and closed thermodynamic system
A fluid enters a steady flow apparatus with a specific volume of 0.40 m3/kg, pressure of 550 kPa, and velocity of 20 m/s, and exits with a specific volume of 0.82 m3/kg, pressure of 100 kPa, and velocity of 280 m/s. The apparatus produces 140 kJ of work per kg and experiences 12 kJ/kg of heat loss. The change in internal energy is determined to be -58.32 kJ/kg.
CH EN 3453 Heat Transfer 2014 Fall Utah Homework HW 08 Assignment
Chemical Engineering CH EN 3453 Heat Transfer
from University of Utah, 2014 Fall
Homework HW 08 Assignment
Jean-Paul Gibson: Analysis Of An Open Feedwater Heater System
People often look surprised when I tell them that Thermodynamics was probably one of my favorite classes in school. This was the final project for my Thermo II class and was intended to be done in groups. I wanted to challenge myself to a near unnecessary limit by completing this entire project myself. The purpose of this project was to determine the optimum operating pressure for the feedwater heater for a power cycle (from a selected problem in the textbook). However the primary focus, and most difficult task, was writing a program in C++ to calculate multiple values for a selected problem in our textbook. I quite literally had to teach myself how to program in C++ well beyond the basics I had learned in an intro class. This program had to be capable of cross referencing multiple reference tables in the back of the book, each having dozens of values which had to be manually typed in. Which reference tables it pulled values from was dependent on the user inputted turbine efficiency and feedwater heater pressure. It easily took me over a month to debug and test this program to ensure it was always going to the correct reference tables to pull data when outputting the calculations it performed.
Update on 7/2/2016: I did attempt to make another program that would allow the user to type in any feedwater heater pressure rather than make a selection from values there was a reference table for in the back of the back. The program used a method of interpolation to obtain all the data needed to perform all the calculations that were outputted. I don't remember the last time I attempted to run that version of the program, but I seem to recall getting impossible answers outputted. This indicated to me that a more complicated method of interpolating values was required, or I just couldn't get it to work correctly. I ultimately decided against pursuing that version of the program any further. Just getting it work correctly with a predefined list of pressures to select from was difficult enough.
AP Physics B Test Exam Solutions
#1. Physics B Exam - 1998 contains multiple choice questions about physics concepts tested on the AP Physics B Exam in 1998.
#2. The document contains 20 questions with basic ideas, solutions, and answers related to mechanics, electricity and magnetism, thermodynamics, and other physics topics.
#3. The questions cover a wide range of physics principles including kinematics, energy, momentum, electric fields, magnetic fields, waves, optics, and nuclear physics.
Engineering thermodynamics-solutions-manual
SFEE:
W = m[(h2 - h1) - (KE2 - KE1) - (PE2 - PE1)]
State 1: 1 bar, 20°C
h1 = 293.9 kJ/kg
KE1 = 0
PE1 = 0
State 2: 3.5 bar
Use isentropic process with s1 = s2
h2 = 341.4 kJ/kg
KE2 = 0.5*m*(7)^2 = 24.5 kJ/kg
PE2 - PE1 = 0
W = m[(h2 - h1) - (KE2 - KE1)]
= (341.
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- Phase shift keying (PSK) where the phase of the carrier signal is varied to represent data bits, including binary PSK and quadrature PSK (QPSK).
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This document discusses various digital-to-analog conversion techniques including:
- Amplitude shift keying (ASK) where the amplitude of the carrier signal is varied to represent data bits.
- Frequency shift keying (FSK) where the frequency of the carrier signal is varied to represent data bits.
- Phase shift keying (PSK) where the phase of the carrier signal is varied to represent data bits, including binary PSK and quadrature PSK (QPSK).
- Quadrature amplitude modulation (QAM) which combines ASK and PSK to maximize contrast between signal elements.
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Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Design and optimization of ion propulsion drone
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
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Diagrama
- 1. Wn = 500 Mw Tmax = T3 = 1750°K rp = 16/1 3 2 compresor 1 4 T5 = 723°k 5 Pa = 7.5 Mpa a Ta = 450° C b-1 b d c P = 500 Kpa combustor T1 = 27°k P1 = 100 kpa rp = 1/16 Wn = 500 Mw