scholarly journals HCCI Intelligent Rapid Modeling by Artificial Neural Network and Genetic Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
AbdoulAhad Validi ◽  
Jyh-Yuan Chen ◽  
Akbar Ghafourian
Keyword(s):  
Genetic Algorithm ◽  
Chemical Kinetics ◽  
National Laboratory ◽  
Sandia National Laboratory ◽  
Chemical Mechanism ◽  
Inlet Temperature ◽  
First Case ◽  
Crank Angle ◽  
Inlet Conditions ◽  
Rapid Modeling

A Dynamic model of Homogeneous Charge Compression Ignition (HCCI), based on chemical kinetics principles and artificial intelligence, is developed. The model can rapidly predict the combustion probability, thermochemistry properties, and exact timing of the Start of Combustion (SOC). A realization function is developed on the basis of the Sandia National Laboratory chemical kinetics model, and GRI3.0 methane chemical mechanism. The inlet conditions are optimized by Genetic Algorithm (GA), so that combustion initiates and SOC timing posits in the desired crank angle. The best SOC timing to achieve higher performance and efficiency in HCCI engines is between 5 and 15 degrees crank angle (CAD) after top dead center (TDC). To achieve this SOC timing, in the first case, the inlet temperature and equivalence ratio are optimized simultaneously and in the second case, compression ratio is optimized by GA. The model’s results are validated with previous works. The SOC timing can be predicted in less than 0.01 second and the CPU time savings are encouraging. This model can successfully be used for real engine control applications.

Sensitivity Study of the South Texas Project Power Plant Steady-State Simulations Using RELAP5-3D Coupled With Dakota

2012 ◽  
Author(s):  
O. A. Rodriguez ◽  
R. Vaghetto ◽  
Y. A. Hassan
Keyword(s):  
Steady State ◽  
Power Plant ◽  
Uncertainty Quantification ◽  
National Laboratory ◽  
Sandia National Laboratory ◽  
Sensitivity Study ◽  
South Texas ◽  
Normal Operation ◽  
Inlet Temperature ◽  
The South

A RELAP5-3D input deck of the South Texas Project (STP) power plant was created in order to study the thermal-hydraulic behavior of the plant during normal operation (steady-state) and during a Loss of Coolant Accident (LOCA). It is important to study the sensitivity of selected output parameters such as the total coolant mass flow rate, the peak clad temperature, the secondary pressure, as a function of specific input parameters (reactor nominal power, vessel inlet temperature, steam generators primary side heat transfer coefficient, primary pressure etc.) in order to identify the variables that play a role in the uncertainty of the thermal-hydraulic calculations. RELAP5-3D, one of the most used best estimate thermal-hydraulic system codes, was coupled with DAKOTA, developed by Sandia National Laboratory for Uncertainty Quantification and Sensitivity Analysis in order to simplify the simulation process and the analysis of the results. In the present paper, the results of the sensitivity study for selected output parameters of the steady-state simulations are presented. The coupled software was validated by repeating one set of simulations using the RELAP5-3D standalone version and by analyzing the simulation results with respect of the physical expectations and behavior of the power plant. The thermal-hydraulic parameters of interest for future uncertainty quantification calculations were identified.

Off Design Performance Map Similarity Study of Radial Type Turbomachinery in Supercritical CO2 Brayton Cycle

2015 ◽  
Author(s):  
Seong Kuk Cho ◽  
Jekyoung Lee ◽  
Jeong Ik Lee
Keyword(s):  
Critical Point ◽  
Pressure Ratio ◽  
National Laboratory ◽  
Sandia National Laboratory ◽  
Power Conversion ◽  
Design Tool ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Performance Map ◽  
The Future

A supercritical carbon dioxide (S-CO2) Brayton cycle has received attention as one of the future power conversion systems because of its high thermal efficiency at relatively low turbine inlet temperature. However, the design process of the S-CO2 compressor is known to be difficult because the fluid properties vary significantly near the critical point. This paper discusses about the design methodology of a S-CO2 compressor on the basis of the existing design practice and performance map of Sandia National Laboratory, which is the only reported experimental data for the S-CO2 compressor. Five parameters are mainly used for verifying the turbomachinery similarity. When all of 5 parameters coincide with the prototype and the conceptually designed turbomachinery, similar performance can be assumed. As a result, the data of SNL are insufficient to design a single stage compressor which is able to compress from near critical point to 20MPa. The optimum cycle pressure ratio is reported to be around 2.6∼2.7 in the previous S-CO2 Brayton cycle research works. The minimum number of stages is required at least two to utilize the existing data in the compressor design. So this study focuses on two main purposes. The first is to check whether the SNL data can be extended for the larger scale S-CO2 system. Second, the performance map obtained from KAIST_TMD, which is from an in-house code developed by the Korea Advanced Institute of Science and Technology (KAIST) research team, was compared to the SNL data, so that KAIST_TMD can be used as a design tool for a larger scale S-CO2 power conversion system in the future.

scholarly journals Thermal prediction of turbulent forced convection of nanofluid using computational fluid dynamics coupled genetic algorithm with fuzzy interface system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Meisam Babanezhad ◽  
Iman Behroyan ◽  
Ali Taghvaie Nakhjiri ◽  
Mashallah Rezakazemi ◽  
Azam Marjani ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Genetic Algorithm ◽  
Computational Fluid Dynamics ◽  
Kinetic Energy ◽  
Population Size ◽  
Turbulent Kinetic Energy ◽  
Forced Convection ◽  
Inlet Temperature ◽  
Fluid Temperature ◽  
Interface System

AbstractComputational fluid dynamics (CFD) simulating is a useful methodology for reduction of experiments and their associated costs. Although the CFD could predict all hydro-thermal parameters of fluid flows, the connections between such parameters with each other are impossible using this approach. Machine learning by the artificial intelligence (AI) algorithm has already shown the ability to intelligently record engineering data. However, there are no studies available to deeply investigate the implicit connections between the variables resulted from the CFD. The present investigation tries to conduct cooperation between the mechanistic CFD and the artificial algorithm. The genetic algorithm is combined with the fuzzy interface system (GAFIS). Turbulent forced convection of Al2O3/water nanofluid in a heated tube is simulated for inlet temperatures (i.e., 305, 310, 315, and 320 K). GAFIS learns nodes coordinates of the fluid, the inlet temperatures, and turbulent kinetic energy (TKE) as inputs. The fluid temperature is learned as output. The number of inputs, population size, and the component are checked for the best intelligence. Finally, at the best intelligence, a formula is developed to make a relationship between the output (i.e. nanofluid temperatures) and inputs (the coordinates of the nodes of the nanofluid, inlet temperature, and TKE). The results revealed that the GAFIS intelligence reaches the highest level when the input number, the population size, and the exponent are 5, 30, and 3, respectively. Adding the turbulent kinetic energy as the fifth input, the regression value increases from 0.95 to 0.98. This means that by considering the turbulent kinetic energy the GAFIS reaches a higher level of intelligence by distinguishing the more difference between the learned data. The CFD and GAFIS predicted the same values of the nanofluid temperature.

Simulation of HCCI Combustion Characteristics for Low RON Gasoline Surrogate Fuels

2014 ◽  
Vol 694 ◽  
pp. 54-58
Author(s):  
Ling Zhe Zhang ◽  
Ya Kun Sun ◽  
Su Li ◽  
Qing Ping Zheng
Keyword(s):  
Equivalence Ratio ◽  
Chemical Kinetic ◽  
Combustion Characteristics ◽  
Material Strength ◽  
Inlet Temperature ◽  
Compression Ignition Engine ◽  
Chemical Kinetic Model ◽  
Hcci Engine ◽  
Surrogate Fuels ◽  
Inlet Conditions

A reduced chemical kinetic model (103species and 468 reactions) for new low-RON(research octane number) gasoline surrogate fuels has been proposed. Simulations explored for ignition delay time have been compared with experimental data in shock tubes at pressure of 10atm-55 atm and temperatue of 600-1400 K (fuel/air equivalence ratio=0.5,1.0,2.0 and EGR rate=0, 20%). The simulation data presented 15% enlargement compared with experiments showed applicability of the new kinetic mode in this work. A combustion simulation model has been build for HCCI(homogeneous charge compression ignition) engine with Chemkin-pro. The effects of different air inlet temperature, inlet pressure, engine speed and the fuel air equivalence ratio on the combustion characteristics of the fuel were researched. The results indicated the combustion in an HCCI engine worked sufficiently with lean mixtures and low speed. Meanwhile the material strength could be influenced when the inlet conditions changed. This helps to promote the low-RON gasoline surrogate fuel application in the HCCI engine.

Optimization of Turbofan Propulsion Cycle Using a Genetic Algorithm

2010 ◽  
Author(s):  
Adel Ghenaiet
Keyword(s):  
Genetic Algorithm ◽  
Fuel Consumption ◽  
Pressure Ratio ◽  
Engine Performance ◽  
Optimization Procedure ◽  
Specific Fuel Consumption ◽  
High Mass ◽  
Design Parameters ◽  
Inlet Temperature ◽  
Simplifying Assumptions

This paper presents an evolutionary approach as the optimization framework to design for the optimal performance of a high-bypass unmixed turbofan to match with the power requirements of a commercial aircraft. The parametric analysis had the objective to highlight the effects of the principal design parameters on the propulsive performance in terms of specific fuel consumption and specific thrust. The design optimization procedure based on the genetic algorithm PIKAIA coupled to the developed engine performance analyzer (on-design and off-design) aimed at finding the propulsion cycle parameters minimizing the specific fuel consumption, while meeting the required thrusts in cruise and takeoff and the restrictions of temperatures limits, engine size and weight as well as pollutants emissions. This methodology does not use engine components’ maps and operates on simplifying assumptions which are satisfying the conceptual or early design stages. The predefined requirements and design constraints have resulted in an engine with high mass flow rate, bypass ratio and overall pressure ratio and a moderate turbine inlet temperature. In general, the optimized engine is fairly comparable with available engines of equivalent power range.

scholarly journals Computational Analysis of the Performance Characteristics of a Supercritical CO2 Centrifugal Compressor

Computation ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 54 ◽  
Author(s):  
Senthil Raman ◽  
Heuy Kim
Keyword(s):  
Centrifugal Compressor ◽  
Stokes Equations ◽  
National Laboratory ◽  
Sandia National Laboratory ◽  
Ideal Gas ◽  
Operating Conditions ◽  
Tip Clearance ◽  
Performance Characteristics ◽  
Supercritical Regime ◽  
Vaned Diffuser

A centrifugal compressor working with supercritical CO 2 (S-CO 2 ) has several advantages over other supercritical and conventional compressors. S-CO 2 is as dense as the liquid CO 2 and becomes difficult to compress. Thus, during the operation, the S-CO 2 centrifugal compressor requires lesser compression work than the gaseous CO 2 . The performance of S-CO 2 compressors is highly varying with tip clearance and vanes in the diffuser. To improve the performance of the S-CO 2 centrifugal compressor, knowledge about the influence of individual components on the performance characteristics is necessary. This present study considers an S-CO 2 compressor designed with traditional engineering design tools based on ideal gas behaviour and tested by SANDIA national laboratory. Three-dimensional, steady, viscous flow through the S-CO 2 compressor was analysed with computational fluid dynamics solver based on the finite volume method. Navier-Stokes equations are solved with K- ω (SST) turbulence model at operating conditions in the supercritical regime. Performance of the impeller, the main component of the centrifugal compressor is compared with the impeller with vaneless diffuser and vaned diffuser configurations. The flow characteristics of the shrouded impeller are also studied to analyse the tip-leakage effect.

Matching and Optimisation of Turbochargers for Upgradation of High Horse Power Diesel Electric Locomotives for Indian Railways

2005 ◽  
Author(s):  
Anirudh Gautam ◽  
Avinash Kumar Agarwal
Keyword(s):  
Engine Speed ◽  
Thermal Loading ◽  
Fuel Efficiency ◽  
Operating Point ◽  
Inlet Temperature ◽  
Test Bed ◽  
Optimum Configuration ◽  
Air Inlet ◽  
First Case ◽  
Brake Mean Effective Pressure

As a part of the upgradation program of its fleet of 1940 kW diesel electric locomotives, Indian Railways undertook evaluation, matching and optimization of different turbochargers. The objective was to increase engine output, improve fuel efficiency and limit thermal loading. Trials with different makes of turbochargers using different combinations of diffuser, nozzle rings and compressors were carried out for identifying the optimum configuration for an uprated engine rating of 2310 kW. Test bed evaluations have been carried out on Research Design & Standards Organization (RDSO) test beds for four different designs of turbochargers with different configurations. Two types of surge tests were carried out at each operating point i.e. constant brake mean effective pressure (BMEP) and constant power. In the first case, BMEP was kept constant and engine speed varied and in the second case, power was kept constant and engine speed was varied. The tests consisted of recording the parameters at various combinations of engine speed and power. With different combinations, the highest operating point for a test was governed by peak firing pressures. Some of the parameters, which were monitored, were the compressor air inlet temperature, representative peak firing pressures, turbine inlet temperature, average cylinder head temperature, brake specific fuel consumption (BSFC) and air manifold temperature. This paper discusses the methods adopted in carrying out these evaluations and optimizations and the results obtained thereof along with the decision criteria for making final selections.

IMPORTANCE OF 3D VEHICLE HEAT EXCHANGER MODELING

2021 ◽  
pp. 1-10
Author(s):  
Michal Schmid ◽  
Fatih Bozkurt ◽  
Petr Pašcenko ◽  
Pavel Petržela
Keyword(s):  
Fluid Flow ◽  
Heat Exchanger ◽  
Fluid Velocity ◽  
Coolant Temperature ◽  
Inlet Temperature ◽  
Vehicle Simulation ◽  
Velocity Magnitude ◽  
Primary Fluid ◽  
The Difference ◽  
Inlet Conditions

Abstract The work demonstrates, via a comprehensive study, the necessity of using a 3D CFD approach for heat exchanger (HTX) modelling within underhood vehicle simulation. The results are presented as the difference between 1D and 3D CFD approaches with a focus on auxiliary fluid (e.g. coolant) temperature prediction as a function of primary fluid (e.g. air) inlet conditions. It has been shown that the 1D approach could significantly underpredict auxiliary fluid inlet temperature due to neglecting the spatial distribution of primary fluid velocity magnitude. The resultant difference in the auxiliary fluid flow HTX inlet temperature is presented and discussed as a function of the Uniformity Index (UI) of the primary fluid flow velocity magnitude. Additionally, the 3D HTX model's importance is demonstrated in an industrial example of full 3D underhood simulation.

Mechanical Design and Testing of a 2.5 MW sCO2 Compressor Loop

2021 ◽  
Author(s):  
Stefan D. Cich ◽  
J. Jeffrey Moore ◽  
Chris Kulhanek ◽  
Meera Day Towler ◽  
Jason Mortzheim
Keyword(s):  
High Efficiency ◽  
Mechanical Design ◽  
Guide Vane ◽  
Operating Conditions ◽  
Inlet Guide Vane ◽  
Inlet Temperature ◽  
Design Changes ◽  
Wide Range ◽  
Inlet Conditions ◽  
Design And Testing

Abstract An enabling technology for a successful deployment of the sCO2 close-loop recompression Brayton cycle is the development of a compressor that can maintain high efficiency for a wide range of inlet conditions due to large variation in properties of CO2 operating near its dome. One solution is to develop an internal actuated variable Inlet Guide Vane (IGV) system that can maintain high efficiency in the main and re-compressor with varying inlet temperature. A compressor for this system has recently been manufactured and tested at various operating conditions to determine its compression efficiency. This compressor was developed with funding from the US DOE Apollo program and industry partners. This paper will focus on the design and testing of the main compressor operating near the CO2 dome. It will look at design challenges that went into some of the decisions for rotor and case construction and how that can affect the mechanical and aerodynamic performance of the compressor. This paper will also go into results from testing at the various operating conditions and how the change in density of CO2 affected rotordynamics and overall performance of the machine. Results will be compared to expected performance and how design changes were implanted to properly counter challenges during testing.

Computations by Means of Macroscopic Chemical Kinetics

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Chemical Kinetics ◽  
Reaction Mechanisms ◽  
Parallel Machines ◽  
Electronic Device ◽  
Chemical Mechanism ◽  
Chemical Systems ◽  
Universal Turing Machine ◽  
Sequential Machines ◽  
Logic Functions

The topic of this chapter may seem like a digression from methods and approaches to reaction mechanisms, but it is not; it is an introduction to it. We worked on both topics for some time and there is a basic connection. Think of an electronic device and ask: how are the logic functions of this device determined? Electronic inputs (voltages and currents) are applied and outputs are measured. A truth table is constructed and from this table the logic functions of the device, and at times some of its components, may be inferred. The device is not subjected to the approach toward a chemical mechanism described in the previous chapter, of taking the device apart and testing its simplest components. (That may have to be done sometimes but is to be avoided if possible.) Can such an approach be applicable to chemical systems? We show this to be the case by discussing the implementation of logic and computational devices, both sequential machines such as a universal Turing machine (hand computers, laptops) and parallel machines, by means of macroscopic kinetics; by giving a brief comparison with neural networks; by showing the presence of such devices in chemical and biochemical reaction systems; and by presenting some confirming experiments. The next step is clear: if macroscopic chemical kinetics can carry out these electronic functions, then there are likely to be new approaches possible for the determination of complex reaction mechanisms, analogs of such determinations for electronic components. The discussion in the remainder of this chapter is devoted to illustrations of these topics; it can be skipped, except the last paragraph, without loss of continuity with chapter 5 and beyond. A neuron is either on or off depending on the signals it has received. A chemical neuron is a similar device.

Sign in / Sign up

Export Citation Format

Share Document