CATEGORY: ETHANE
Ind. Eng. Chem. Res., 2014, 53 (15), pp 6358–6371, DOI: 10.1021/ie500391b
Influence of the Reactor Material Composition on Coke Formation
during Ethane Steam Cracking
Andrés E. Muñoz Gandarillas , Kevin M. Van Geem
, Marie-Françoise Reyniers *, and Guy B. Marin
Laboratory for Chemical Technology, Ghent University, Technologiepark 914,
B-9052 Gent, Belgium
MarieFrancoise.Reyniers@UGent.be
Abstract
Researchers studied the coking tendency of nine distinct
materials in a quartz electrobalance setup with a jet stirred reactor (JSR)
under industrially relevant ethane steam cracking conditions: Tmaterial
= 1159 K, Ptot = 0.1 MPa, χethane = 73%, dilution
δ = 0.33 kgH2O/kgHC.
They observed a strong influence of the
composition of the materials on the coking rate as a function of time
on-stream. The initial coking rate varied from 5 × 10–4 g·m–2·s–1
to 27 × 10–4 g·m–2·s–1, while the asymptotic
coking rate changed in the range of 2 × 10–4 g·m–2·s–1
to 6 × 10–4 g·m–2·s–1. SEM and EDX analyses of
coked and uncoked coupons revealed that the composition of the oxide layer in
contact with the cracked gas, formed after the initial preoxidation or
decoking, has an important influence on the amount of coke deposited. Materials
that formed a thin Al2O3 layer on the coupon surface exhibited
a higher coking resistance.
Full Text Source (Subscription or Fee): http://pubs.acs.org/doi/abs/10.1021/ie500391b
Monday, May 12, 2014
dOpenCL: Towards Uniform Programming for Distributed Systems with Multi-Cores and GPUs
CATEGORY: DISTRIBUTED SYSTEMS
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
dOpenCL: Towards Uniform Programming for Distributed Systems with Multi-Cores and GPUs
Philipp Kegel and Sergei Gorlatch
gorlatch@uni-muenster.de
Institute of Computer Science, University of Muenster, 48149 Muenster, Germany.
Abstract
Modern computer systems are becoming distributed and heterogeneous by comprising multi-core CPUs, GPUs, and other accelerators. However, to program such systems, the user currently has to use a combination of several programming models (e.g., MPI with OpenCL or CUDA), which is difficult and error-prone. We present dOpenCL (distributed OpenCL) – a uniform approach to programming distributed systems with accelerators.
Our approach is based on the OpenCL standard and it allows the user to run existing OpenCL applications unmodified in a heterogeneous distributed environment. The dOpenCL system also supports transparent execution of multiple OpenCL applications in one distributed, multi-user environment. We describe dOpenCL as an implementation of the OpenCL programming model on distributed systems, and we experimentally compare the performance of dOpenCL with MPI+OpenCL and standard OpenCL implementations.
INTRODUCTION
MODERN systems increasingly comprise heterogeneous processing devices, e.g., multi-core CPUs, GPUs, and other accelerators. The state-of-the-art approaches to program such systems usually employ several programming models in combination. For example, let us consider programming a cluster where each node contains a multicore CPU and a GPU. First, the programmer has to distribute the data to all compute nodes, e.g., using MPI [1] or explicit, low-level network programming. Second, to exploit the GPU at each node, another appropriate model, e.g., CUDA [2] is needed, which requires the programmer to explicitly transfer data between the node’s main memory and GPU. Furthermore, in order to use all cores of the CPU, a thread programming model, e.g., Pthreads [3] is usually employed. The main drawback of combining programming models is that the programmer has to master several different models, and he also has to take into account their possible interference when used together in a single program.
We present dOpenCL (distributed OpenCL) – a uniform programming approach for heterogeneous, distributed systems. It is based on OpenCL [4] – an open, widely accepted standard for heterogeneous systems. However, the original OpenCL is limited to stand-alone systems and has to be augmented by other programming models to create applications for distributed systems. The dOpenCL approach transparently implements the OpenCL programming model for distributed systems, such that the programmer no longer has to combine it with other programming models.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp184-188.pdf
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
dOpenCL: Towards Uniform Programming for Distributed Systems with Multi-Cores and GPUs
Philipp Kegel and Sergei Gorlatch
gorlatch@uni-muenster.de
Institute of Computer Science, University of Muenster, 48149 Muenster, Germany.
Abstract
Modern computer systems are becoming distributed and heterogeneous by comprising multi-core CPUs, GPUs, and other accelerators. However, to program such systems, the user currently has to use a combination of several programming models (e.g., MPI with OpenCL or CUDA), which is difficult and error-prone. We present dOpenCL (distributed OpenCL) – a uniform approach to programming distributed systems with accelerators.
Our approach is based on the OpenCL standard and it allows the user to run existing OpenCL applications unmodified in a heterogeneous distributed environment. The dOpenCL system also supports transparent execution of multiple OpenCL applications in one distributed, multi-user environment. We describe dOpenCL as an implementation of the OpenCL programming model on distributed systems, and we experimentally compare the performance of dOpenCL with MPI+OpenCL and standard OpenCL implementations.
INTRODUCTION
MODERN systems increasingly comprise heterogeneous processing devices, e.g., multi-core CPUs, GPUs, and other accelerators. The state-of-the-art approaches to program such systems usually employ several programming models in combination. For example, let us consider programming a cluster where each node contains a multicore CPU and a GPU. First, the programmer has to distribute the data to all compute nodes, e.g., using MPI [1] or explicit, low-level network programming. Second, to exploit the GPU at each node, another appropriate model, e.g., CUDA [2] is needed, which requires the programmer to explicitly transfer data between the node’s main memory and GPU. Furthermore, in order to use all cores of the CPU, a thread programming model, e.g., Pthreads [3] is usually employed. The main drawback of combining programming models is that the programmer has to master several different models, and he also has to take into account their possible interference when used together in a single program.
We present dOpenCL (distributed OpenCL) – a uniform programming approach for heterogeneous, distributed systems. It is based on OpenCL [4] – an open, widely accepted standard for heterogeneous systems. However, the original OpenCL is limited to stand-alone systems and has to be augmented by other programming models to create applications for distributed systems. The dOpenCL approach transparently implements the OpenCL programming model for distributed systems, such that the programmer no longer has to combine it with other programming models.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp184-188.pdf
Influence of impurities on corrosion products behavior in feedwater conditions
CATEGORY: CORROSION
Proceedings of International Conference on Heat Exchanger Fouling and Cleaning, June 9-14, 2013, Budapest, Hungary
Influence of impurities on corrosion products behavior in feedwater conditions
S. Delaunay (1), C. Mansour (1), A. Bescond1 and J-L. Bretelle (2)
1 EDF R&D/MMC, Moret-Sur-Loing, France
2 EDF Power Generation Div., Saint-Denis, France
Abstract
Fouling and tube support plat (TSP) blockage in steam generators are major problems in the secondary circuit of pressurized water reactor plants. The identification of deposit formation mechanisms contributes to limit these phenomena. Although the deposit is mainly composed of magenetite, some impurities, in particular aluminum and silicon, may lead to its consolidation.
This paper presents the results of tests performed in a specific experimental device named FORTRAND. The aim of these tests was to evaluate the impact of the presence of impurities, (Al. Si) on iron behavkior in the secondary circuit feedwater conditions. Tests were performed in single phase flow at 150 L/h and 220° C in a morpholine/ammonia/hydrazine medium.
The injection of aluminum and silicon separately presents no influence on speciation of these species and iron species in the loop, as well in the bulk as in the oxide layer. But the injection of both species at the same time induces both a sligh increas in wt% of Al in oxides layer formed on carbon steel tubes and an increase of the Al concentration in solution. Other tests need to be conducted in order to improve the knowledge of the interaction between Al, Si and iron species.
Free Full Text Source: http://www.heatexchanger-fouling.com/papers/papers2013/14_Delaunay_F.pdf
Proceedings of International Conference on Heat Exchanger Fouling and Cleaning, June 9-14, 2013, Budapest, Hungary
Influence of impurities on corrosion products behavior in feedwater conditions
S. Delaunay (1), C. Mansour (1), A. Bescond1 and J-L. Bretelle (2)
1 EDF R&D/MMC, Moret-Sur-Loing, France
2 EDF Power Generation Div., Saint-Denis, France
Abstract
Fouling and tube support plat (TSP) blockage in steam generators are major problems in the secondary circuit of pressurized water reactor plants. The identification of deposit formation mechanisms contributes to limit these phenomena. Although the deposit is mainly composed of magenetite, some impurities, in particular aluminum and silicon, may lead to its consolidation.
This paper presents the results of tests performed in a specific experimental device named FORTRAND. The aim of these tests was to evaluate the impact of the presence of impurities, (Al. Si) on iron behavkior in the secondary circuit feedwater conditions. Tests were performed in single phase flow at 150 L/h and 220° C in a morpholine/ammonia/hydrazine medium.
The injection of aluminum and silicon separately presents no influence on speciation of these species and iron species in the loop, as well in the bulk as in the oxide layer. But the injection of both species at the same time induces both a sligh increas in wt% of Al in oxides layer formed on carbon steel tubes and an increase of the Al concentration in solution. Other tests need to be conducted in order to improve the knowledge of the interaction between Al, Si and iron species.
Free Full Text Source: http://www.heatexchanger-fouling.com/papers/papers2013/14_Delaunay_F.pdf
Optimal Condition-Based Maintenance Replacement based on Logical Analysis of Data (LAD)
CATEGORY: CONDITION BASED MAINTENANCE
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol II, IMECS 2013, March 13 - 15, 2013, Hong Kong
Optimal Condition-Based Maintenance Replacement based on Logical Analysis of Data (LAD)
Alireza Ghasemi, Sasan Esameili
A. Ghasemi is an Assistant Professor with Department of Industrial Engineering of Dalhousie University, Halifax, NS, Canada (alireza.ghasemi@dal.ca ).
S. Esmaeili is a graduated Master’s student form Department of Industrial Engineering of Dalhousie University. Abstract
This paper develops equipment optimal condition based replacement model, using Logical Analysis of Data (LAD). LAD is a powerful classification method that does not relying on any statistical theory which enables LAD to overcome the usual problems concerning the statistical properties of the data. LAD profits from a straightforward procedure and self-explanatory results.
In this paper, our objective is to develop an optimal replacement method by taking its working condition (condition monitoring data) into consideration using LAD. Using equipment’s survival probability and associated costs of scheduled and non-scheduled replacements, an optimal replacement method is introduced. The proposed method is applied on a hypothetical problem and its easy to understand approach and its high performance is shown. Analysis of performance of the proposed methods reveals that the methods provide self-explanatory results that are greatly beneficial to maintenance practitioners.
Introduction
Since its introduction, LAD has been applied for the analysis of data in different fields such as medicine, biotechnology, economics, finance, politics, properties, oil exploration, manufacturing and maintenance . Recently LAD was used for diagnosis of equipment failure. LAD has proved to be a promising technique that provides interpretable results that are comparable to most pioneer techniques in the field of diagnostics in CBM. improved LAD methodology to predict equipment’s chance of survival at each observation moment when new data on attributes of the equipment is available. It showed that LAD provides comprehensible results that are greatly beneficial to maintenance practitioners in prognosticating fault in machinery. In this work, we will introduce an optimal replacement model that minimizes the maintenance cost of equipment considering its condition monitoring data, using LAD.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp830-833.pdf
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol II, IMECS 2013, March 13 - 15, 2013, Hong Kong
Optimal Condition-Based Maintenance Replacement based on Logical Analysis of Data (LAD)
Alireza Ghasemi, Sasan Esameili
A. Ghasemi is an Assistant Professor with Department of Industrial Engineering of Dalhousie University, Halifax, NS, Canada (alireza.ghasemi@dal.ca ).
S. Esmaeili is a graduated Master’s student form Department of Industrial Engineering of Dalhousie University. Abstract
This paper develops equipment optimal condition based replacement model, using Logical Analysis of Data (LAD). LAD is a powerful classification method that does not relying on any statistical theory which enables LAD to overcome the usual problems concerning the statistical properties of the data. LAD profits from a straightforward procedure and self-explanatory results.
In this paper, our objective is to develop an optimal replacement method by taking its working condition (condition monitoring data) into consideration using LAD. Using equipment’s survival probability and associated costs of scheduled and non-scheduled replacements, an optimal replacement method is introduced. The proposed method is applied on a hypothetical problem and its easy to understand approach and its high performance is shown. Analysis of performance of the proposed methods reveals that the methods provide self-explanatory results that are greatly beneficial to maintenance practitioners.
Introduction
Since its introduction, LAD has been applied for the analysis of data in different fields such as medicine, biotechnology, economics, finance, politics, properties, oil exploration, manufacturing and maintenance . Recently LAD was used for diagnosis of equipment failure. LAD has proved to be a promising technique that provides interpretable results that are comparable to most pioneer techniques in the field of diagnostics in CBM. improved LAD methodology to predict equipment’s chance of survival at each observation moment when new data on attributes of the equipment is available. It showed that LAD provides comprehensible results that are greatly beneficial to maintenance practitioners in prognosticating fault in machinery. In this work, we will introduce an optimal replacement model that minimizes the maintenance cost of equipment considering its condition monitoring data, using LAD.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp830-833.pdf
Improvement of Multicomponent Batch Reactive Distillation under Parameter Uncertainty by Inferential State with Model Predictive Control
CATEGORY: BATCH REACTIVE DISTILLATION
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I,
IMECS 2013, March 13 - 15, 2013, Hong Kong
Improvement of Multicomponent Batch Reactive Distillation under Parameter Uncertainty by Inferential State with Model Predictive Control
W. Weerachaipichasgul, is with Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, THAILAND.
P. Kittisupakorn, is with Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, THAILAND(corresponding author to provide phone: +66-02-2186878; fax.: +66-02-2186877; e-mail: Paisan.K@chula.ac.th .
I. M. Mujtaba, is with School of Engineering Design and Technology, University of Bradford, EDT 3, West Yorkshire BD7 1DP, UK.
Abstract
Batch reactive distillation is aimed at achieving a high purity product, therefore, there is a great deal to find an optimal operating condition and effective control strategy to obtain maximum of the high purity product. An off-line dynamic optimization is first performed with an objective function to provide optimal product composition for the batch reactive distillation: maximum productivity. An inferential state estimator (an extended Kalman filter, EKF) based on simplified mathematical models and on-line temperature measurements, is incorporated to estimate the compositions in the reflux drum and the reboiler. Model Predictive Control (MPC) has been implemented to provide tracking of the desired product compositions subject to simplified model equations. Simulation results demonstrate that the inferential state estimation can provide good estimates of compositions.
Therefore, the control performance of the MPC with the inferential state is better than that of PID. In addition, in the presence of unknown/uncertain parameters (forward reaction rate constant), the estimator is still able to provide accurate concentrations. As a result, the MPC with the inferential state is still robust and applicable in real plants.
I. INTRODUCTION
The modeling of batch reactive distillation [2- 5] have been applied to achieve the high quality of product by the optimization technique. An objective function in the optimization problem depends on the nature of the problem maximum profit, minimum time, maximum conversion, and maximum product concentration. To obtain the product purity, the controller can be employed directly by using on-line measured composition but this measurement is expensive, difficult to maintain, necessitating frequent calibrations and it introduces measurement delay. Although the temperature measurement is suitable than the composition measurement, the product quality maybe off-spec and it can be known only at the end of the batch by using a direct temperature control. The tray temperature in distillation column does not correspond exactly to the compositions. Thus inferential state control is one of the solutions that can be applied.
For the batch distillation with/without reaction processes, there are many techniques to infer compositions from the temperature data and then the estimated states are fed back to the controller; for example, an extended Luenberger Observer (ELO) with a conventional PI controller , an extended Kalman filter (EKF) , a Kalman filter based on multiple reduced order models with a model predictive control based on reduced order model , and an artificial neural network (ANN) estimator. When composition control for batch reactive distillation is focused, it has not been much addressed.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I,
IMECS 2013, March 13 - 15, 2013, Hong Kong
Improvement of Multicomponent Batch Reactive Distillation under Parameter Uncertainty by Inferential State with Model Predictive Control
W. Weerachaipichasgul, is with Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, THAILAND.
P. Kittisupakorn, is with Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, THAILAND(corresponding author to provide phone: +66-02-2186878; fax.: +66-02-2186877; e-mail: Paisan.K@chula.ac.th .
I. M. Mujtaba, is with School of Engineering Design and Technology, University of Bradford, EDT 3, West Yorkshire BD7 1DP, UK.
Abstract
Batch reactive distillation is aimed at achieving a high purity product, therefore, there is a great deal to find an optimal operating condition and effective control strategy to obtain maximum of the high purity product. An off-line dynamic optimization is first performed with an objective function to provide optimal product composition for the batch reactive distillation: maximum productivity. An inferential state estimator (an extended Kalman filter, EKF) based on simplified mathematical models and on-line temperature measurements, is incorporated to estimate the compositions in the reflux drum and the reboiler. Model Predictive Control (MPC) has been implemented to provide tracking of the desired product compositions subject to simplified model equations. Simulation results demonstrate that the inferential state estimation can provide good estimates of compositions.
Therefore, the control performance of the MPC with the inferential state is better than that of PID. In addition, in the presence of unknown/uncertain parameters (forward reaction rate constant), the estimator is still able to provide accurate concentrations. As a result, the MPC with the inferential state is still robust and applicable in real plants.
I. INTRODUCTION
The modeling of batch reactive distillation [2- 5] have been applied to achieve the high quality of product by the optimization technique. An objective function in the optimization problem depends on the nature of the problem maximum profit, minimum time, maximum conversion, and maximum product concentration. To obtain the product purity, the controller can be employed directly by using on-line measured composition but this measurement is expensive, difficult to maintain, necessitating frequent calibrations and it introduces measurement delay. Although the temperature measurement is suitable than the composition measurement, the product quality maybe off-spec and it can be known only at the end of the batch by using a direct temperature control. The tray temperature in distillation column does not correspond exactly to the compositions. Thus inferential state control is one of the solutions that can be applied.
For the batch distillation with/without reaction processes, there are many techniques to infer compositions from the temperature data and then the estimated states are fed back to the controller; for example, an extended Luenberger Observer (ELO) with a conventional PI controller , an extended Kalman filter (EKF) , a Kalman filter based on multiple reduced order models with a model predictive control based on reduced order model , and an artificial neural network (ANN) estimator. When composition control for batch reactive distillation is focused, it has not been much addressed.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/
Optimal High Purity Acetone Production in a Batch Extractive Distillation Column
CATEGORY: BATCH EXTRACTIVE DISTILLATION
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
Optimal High Purity Acetone Production in a Batch Extractive Distillation Column
P. Kittisupakorn is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand (corresponding author to provide phone: +66-02-2186878; fax.: +66-02-2186877; e-mail: Paisan.K@chula.ac.th ).
K. Jariyaboon is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
W. Weerachaipichasgul is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
Abstract
A waste solvent mixture of acetone-methanol in a pharmaceutical plant which is minimum-boiling azeotrope properties, it is difficult tasked to separate this liquid mixtures by conventional batch distillation. To achieve higher purity, a batch extractive distillation, combining the extraction and separation into a single stage, is widely carried out to separate this waste solvent mixture.
The objective of this work is to study an approach to produce acetone with the purity of 94.0% by mole by a batch extractive distillation column.
In the column operation, semi-continues mode has been proposed to improve purity of acetone. The total reflux start-up period is finished when the unit reaches its steady state and/or maximum purity. Water has been used as solvent. Dynamic optimization strategy is proposed after the total reflux start-up period is ended. The optimization problem is formulated to maximize the weight of distillate product for a given product specification, reboiler heat duty, and batch operating time. Simulation results show that 94.0% purity of the distillate product can be produced by the dynamic optimization programming with two or more time intervals. Besides, the higher time intervals results in the higher distillate product.
Index Terms—Minimum-boiling azeotrope, Batch extractive distillation, Dynamic optimization, High purity acetone
I. INTRODUCTION
Batch distillation is widely applied mostly for the fine and specialty chemical and pharmaceutical industries for the purification of solvent and reagents, and for pollutants elimination from wastewaters. Moreover, the operation of the batch distillation is very attractive; the flexibility in purifying different mixtures under a variety of operational condition, and the separation multicomponent mixture in a single batch column. However, the mainly weakness of batch distillation is that the mixture can form an azeotrope; it cannot be separated by conventional distillation. As a result, alternative distillation methods must be used: azeotropic, extractive, salted and pressure-swing distillations. In industrial applications, extractive and azeotropic distillations are most frequently used but the extractive distillation is generally more flexible than azeotropic distillation, a greater variety of solvents and a wider range of operation conditions.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp143-147.pdf
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
Optimal High Purity Acetone Production in a Batch Extractive Distillation Column
P. Kittisupakorn is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand (corresponding author to provide phone: +66-02-2186878; fax.: +66-02-2186877; e-mail: Paisan.K@chula.ac.th ).
K. Jariyaboon is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
W. Weerachaipichasgul is with the Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
Abstract
A waste solvent mixture of acetone-methanol in a pharmaceutical plant which is minimum-boiling azeotrope properties, it is difficult tasked to separate this liquid mixtures by conventional batch distillation. To achieve higher purity, a batch extractive distillation, combining the extraction and separation into a single stage, is widely carried out to separate this waste solvent mixture.
The objective of this work is to study an approach to produce acetone with the purity of 94.0% by mole by a batch extractive distillation column.
In the column operation, semi-continues mode has been proposed to improve purity of acetone. The total reflux start-up period is finished when the unit reaches its steady state and/or maximum purity. Water has been used as solvent. Dynamic optimization strategy is proposed after the total reflux start-up period is ended. The optimization problem is formulated to maximize the weight of distillate product for a given product specification, reboiler heat duty, and batch operating time. Simulation results show that 94.0% purity of the distillate product can be produced by the dynamic optimization programming with two or more time intervals. Besides, the higher time intervals results in the higher distillate product.
Index Terms—Minimum-boiling azeotrope, Batch extractive distillation, Dynamic optimization, High purity acetone
I. INTRODUCTION
Batch distillation is widely applied mostly for the fine and specialty chemical and pharmaceutical industries for the purification of solvent and reagents, and for pollutants elimination from wastewaters. Moreover, the operation of the batch distillation is very attractive; the flexibility in purifying different mixtures under a variety of operational condition, and the separation multicomponent mixture in a single batch column. However, the mainly weakness of batch distillation is that the mixture can form an azeotrope; it cannot be separated by conventional distillation. As a result, alternative distillation methods must be used: azeotropic, extractive, salted and pressure-swing distillations. In industrial applications, extractive and azeotropic distillations are most frequently used but the extractive distillation is generally more flexible than azeotropic distillation, a greater variety of solvents and a wider range of operation conditions.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp143-147.pdf
Development for a Series Hydraulic Hybrid Vehicle
CATEGORY: ADVANCED ENGINE DESIGN
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
Development for a Series Hydraulic Hybrid Vehicle
C. K. Chen is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (corresponding author to provide phone: 886-935-658-801; e-mail: ckchen@mail.dyu.edu.tw ).
T. V. Vu is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (e-mail: vutrivien@gmail.com ).
C. W. Hung is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (e-mail: c.w.lclsea@gmail.com ).
Abstract
With the flexibility of engine management and regenerative braking characteristics, Series Hydraulic Hybrid Vehicle (SHHV) has been an important research object of institutions and automotive manufacturers all over the world. In this work the series hydraulic hybrid model of a Truck Class II is established for both forward and backward simulation.
Dynamic Programming methodology is applied to estimate an optimal-benchmark solution, in which fuel consumption of the vehicle is selected as the objective function, for the proposed system over a pre-selected driving cycle. A rule-based control strategy is utilized for a physical forward-facing Simulink model to predict the fuel economy improvement of the SHHV system. With different rules, the improvement can be up to 80% in comparing with a traditional hydrostatic control strategy and up to 60% in comparing with a high quality standard; while as, the results with Dynamic Programming technique are 112% and 88% respectively.
Introduction
In all types of hybrid vehicle, the main function of supervisory controller is to coordinate multiple power sources to satisfy the power demand of the driveline with the minimum fuel consumption in the most convenient way. In general, control strategies of the hybrid propulsion systems can be classified into three categories included rule-based, semi-optimal, and global optimal. Among of them, the rule-based control strategy is a real-time implementable power management. In this kind of control strategy, several rules are used to determine the control output according to pre-set conditions. Most papers regarding rule-based control strategy for HHV have been used the State-Of-Charge (SOC) of accumulator as the sole state variable for engine power determination.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp177-183.pdf
Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
Development for a Series Hydraulic Hybrid Vehicle
C. K. Chen is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (corresponding author to provide phone: 886-935-658-801; e-mail: ckchen@mail.dyu.edu.tw ).
T. V. Vu is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (e-mail: vutrivien@gmail.com ).
C. W. Hung is with the Department of Mechanical and Automation Engineering, Dayeh University, Changhua 51591, Taiwan (e-mail: c.w.lclsea@gmail.com ).
Abstract
With the flexibility of engine management and regenerative braking characteristics, Series Hydraulic Hybrid Vehicle (SHHV) has been an important research object of institutions and automotive manufacturers all over the world. In this work the series hydraulic hybrid model of a Truck Class II is established for both forward and backward simulation.
Dynamic Programming methodology is applied to estimate an optimal-benchmark solution, in which fuel consumption of the vehicle is selected as the objective function, for the proposed system over a pre-selected driving cycle. A rule-based control strategy is utilized for a physical forward-facing Simulink model to predict the fuel economy improvement of the SHHV system. With different rules, the improvement can be up to 80% in comparing with a traditional hydrostatic control strategy and up to 60% in comparing with a high quality standard; while as, the results with Dynamic Programming technique are 112% and 88% respectively.
Introduction
In all types of hybrid vehicle, the main function of supervisory controller is to coordinate multiple power sources to satisfy the power demand of the driveline with the minimum fuel consumption in the most convenient way. In general, control strategies of the hybrid propulsion systems can be classified into three categories included rule-based, semi-optimal, and global optimal. Among of them, the rule-based control strategy is a real-time implementable power management. In this kind of control strategy, several rules are used to determine the control output according to pre-set conditions. Most papers regarding rule-based control strategy for HHV have been used the State-Of-Charge (SOC) of accumulator as the sole state variable for engine power determination.
Free Full Text Source: http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp177-183.pdf
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