28 results on '"Jingqi Yuan"'
Search Results
2. Online estimation approach of the steam specific enthalpy for wet steam turbines in nuclear power plants
- Author
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Xinyu Sun, Fei Song, and Jingqi Yuan
- Subjects
Energy Engineering and Power Technology ,Industrial and Manufacturing Engineering - Published
- 2023
3. ESO-based adaptive event-triggered load following control design for a pressurized water reactor with samarium–promethium dynamics
- Author
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Jiuwu Hui, Yi-Kuen Lee, and Jingqi Yuan
- Subjects
General Energy ,Mechanical Engineering ,Building and Construction ,Electrical and Electronic Engineering ,Pollution ,Industrial and Manufacturing Engineering ,Civil and Structural Engineering - Published
- 2023
4. Neural network-based adaptive fault-tolerant control for load following of a MHTGR with prescribed performance and CRDM faults
- Author
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Jiuwu Hui and Jingqi Yuan
- Subjects
General Energy ,Mechanical Engineering ,Building and Construction ,Electrical and Electronic Engineering ,Pollution ,Industrial and Manufacturing Engineering ,Civil and Structural Engineering - Published
- 2022
5. Load following control of a pressurized water reactor via finite-time super-twisting sliding mode and extended state observer techniques
- Author
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Jiuwu Hui and Jingqi Yuan
- Subjects
General Energy ,Mechanical Engineering ,Building and Construction ,Electrical and Electronic Engineering ,Pollution ,Industrial and Manufacturing Engineering ,Civil and Structural Engineering - Published
- 2022
6. A dynamic heat transfer model to estimate the flue gas temperature in the horizontal flue of the coal-fired utility boiler
- Author
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Jingcheng Wang, Zhang Xiang, Chen Zhenxing, Jingqi Yuan, and Zhen Tian
- Subjects
Flue gas ,Convective heat transfer ,020209 energy ,Nuclear engineering ,Boiler (power generation) ,Energy Engineering and Power Technology ,Thermal power station ,02 engineering and technology ,Industrial and Manufacturing Engineering ,020401 chemical engineering ,Heat transfer ,Heat exchanger ,0202 electrical engineering, electronic engineering, information engineering ,Working fluid ,Environmental science ,0204 chemical engineering ,Flue - Abstract
The flue gas temperature is an important parameter for safe and economic operation of thermal power plants. However, in high temperature areas, it is difficult to measure the temperature directly because the sensors are subject to flying ash erosion. This paper establishes a dynamic heat transfer model for the furnace and the semi-radiative heat exchangers, and proposes an estimation approach of the flue gas temperature in the boiler’s horizontal flue. The boiler-side heat absorption models, which cover the heat exchangers, the metal wall and the heat losses are established to calculate the heat absorption rate of the working fluid in the boiler. By solving the optimization problems which are developed based on the dynamic heat transfer models, the flue gas temperature at the outlet of the furnace and the semi-radiative heat exchangers are obtained. Pseudo-online simulations are performed with the history data of an ultra-supercritical unit to verify the approach. The relative errors between the calculated and the designed flue gas temperature with both designed and calibrated feed coal are found less than 3.5%. Additionally, the proportion of the convective heat in the total heat absorption for each semi-radiative heat exchanger is obtainable with the same approach.
- Published
- 2018
7. Pseudo-online optimization of condenser pressure for the cold-end system with variable speed pumps
- Author
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Jingqi Yuan, Zhen Tian, Jingcheng Wang, Zhang Xiang, and Liang Xu
- Subjects
Engineering ,business.industry ,020209 energy ,Energy balance ,Energy Engineering and Power Technology ,Context (language use) ,02 engineering and technology ,Industrial and Manufacturing Engineering ,Power (physics) ,Variable (computer science) ,020401 chemical engineering ,Control theory ,Thermal ,0202 electrical engineering, electronic engineering, information engineering ,Mass flow rate ,0204 chemical engineering ,Constant (mathematics) ,business ,Condenser (heat transfer) - Abstract
The operation conditions of the cold-end system have significant impact on the unit thermal economy. However, due to the difficulty of online determination of some key parameters, the condenser pressure optimization has been a challenging task for a long time. This paper proposes an online applicable approach to optimize the condenser pressure with variable speed pumps, taking the mass flow rate of the circulating water as the manipulating variable, to achieve better thermal economy. After the exhaust steam wetness fraction is online identified, the condenser thermodynamic characteristics under varying working conditions are investigated based on the effectiveness and steady-state energy balance of the condenser. By maximizing the net power benefit, defined as the difference between the unit power increment and the pump power consumption increment, the optimal mass flow rate of the circulating water is derived. To validate the approach, pseudo-online simulations are conducted with the history data from an ultra-supercritical unit. The retention time during which the set value of the mass flow rate of the circulating water remains constant is studied in context with the implementation of the manipulation strategy under on-site scenario. Simulation results reveal the energy-saving potential of condenser pressure optimization with the proposed approach.
- Published
- 2017
8. Chattering-free higher order sliding mode controller with a high-gain observer for the load following of a pressurized water reactor
- Author
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Jingqi Yuan and Jiuwu Hui
- Subjects
Lyapunov stability ,Observer (quantum physics) ,Computer science ,020209 energy ,Mechanical Engineering ,Load following power plant ,PID controller ,02 engineering and technology ,Building and Construction ,Pollution ,Sliding mode control ,Industrial and Manufacturing Engineering ,General Energy ,020401 chemical engineering ,Exponential stability ,Control theory ,Backstepping ,0202 electrical engineering, electronic engineering, information engineering ,0204 chemical engineering ,Electrical and Electronic Engineering ,Civil and Structural Engineering - Abstract
The load following of nuclear power plants (NPPs) has been a contentious issue in the control field. In this paper, we propose a chattering-free higher order sliding mode control scheme with a high-gain observer for the load following of a pressurized water reactor (PWR) in the presence of lumped disturbances owing to model uncertainties and external disturbances. The mathematical model of the PWR system is first set up in the form of an affine nonlinear equation. Subsequently, a high-gain observer, which achieves accurate estimations of the unmeasured state and lumped disturbances, is designed. Based on the outputs of the high-gain observer, we develop a chattering-free higher order sliding mode controller to improve the load-following performance while dealing with lumped disturbances and estimation errors of the high-gain observer. In contrast to some previous sliding mode controllers for the load following of NPPs, the proposed controller is completely free from chattering effects because the control input is obtained after integration. The asymptotic stability of the overall control scheme is demonstrated by combining the Lyapunov stability theory with backstepping technology. Finally, the simulation results reveal that the maximum absolute power error is less than 1 × 10 4 W with the proposed control scheme, 5 × 10 5 W with a PID controller, and 4 × 10 5 W with a conventional sliding mode controller. In addition, in contrast to the conventional sliding mode controller, the proposed control scheme produces smooth control input without the chattering phenomenon. Thus, the proposed chattering-free higher order sliding mode control scheme with a high-gain observer provides smoother control input, higher load-following accuracy, and stronger robustness against lumped disturbances than the PID controller and the conventional sliding mode controller.
- Published
- 2021
9. Online performance monitoring platform based on the whole process models of subcritical coal-fired power plants
- Author
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Liang Xu, Zhang Xiang, Zhen Tian, Jingcheng Wang, and Jingqi Yuan
- Subjects
Engineering ,State variable ,Process modeling ,Power station ,business.industry ,Process (engineering) ,020209 energy ,Energy Engineering and Power Technology ,Thermal power station ,Control engineering ,02 engineering and technology ,Industrial and Manufacturing Engineering ,Power (physics) ,0202 electrical engineering, electronic engineering, information engineering ,Double check ,Distributed control system ,business - Abstract
Online performance monitoring is crucial for the safe and economical operation of thermal power plants. In this study, dynamic models of the whole process are established for the subcritical coal-fired power plant in terms of thermodynamic balances, which covers both boiler-side and turbine-side processes. Based on the whole process models, a monitoring platform is constructed with the functions of online estimation of key state variables and performance evaluation of the unit. The evaluation results of the unit efficiency with the time period of every 5 s may be provided. Model validations are carried out with the history operation data derived from the distributed control system (DCS) of a real 300 MW power plant. Comparisons between the simulation results and designed values of the unit demonstrate the high accuracy of the whole process models. The monitoring platform may also play the role as an offline simulator for the purpose of double check of the unit’s operation during specific time period and accidental cases.
- Published
- 2017
10. Thermodynamic properties calculation of the flue gas based on its composition estimation for coal-fired power plants
- Author
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Jingqi Yuan and Liang Xu
- Subjects
Flue gas ,Petroleum engineering ,business.industry ,Fossil fuel ,Energy Engineering and Power Technology ,Boiler design ,Thermal power station ,Industrial and Manufacturing Engineering ,Dew point ,Working fluid ,Environmental science ,Coal ,business ,Energy source - Abstract
Thermodynamic properties of the working fluid and the flue gas play an important role in the thermodynamic calculation for the boiler design and the operational optimization in power plants. In this study, a generic approach to online calculate the thermodynamic properties of the flue gas is proposed based on its composition estimation. It covers the full operation scope of the flue gas, including the two-phase state when the temperature becomes lower than the dew point. The composition of the flue gas is online estimated based on the routinely offline assays of the coal samples and the online measured oxygen mole fraction in the flue gas. The relative error of the proposed approach is found less than 1% when the standard data set of the dry and humid air and the typical flue gas is used for validation. Also, the sensitivity analysis of the individual component and the influence of the measurement error of the oxygen mole fraction on the thermodynamic properties of the flue gas are presented.
- Published
- 2015
11. Modeling of Mass Transfer in an Internal Loop Airlift Reactor
- Author
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Jingqi Yuan and Lijia Luo
- Subjects
Materials science ,Control theory ,General Chemical Engineering ,Scientific method ,Mass transfer ,Numerical analysis ,Nuclear engineering ,Internal loop ,Airlift reactor ,General Chemistry ,Physics::Chemical Physics ,Industrial and Manufacturing Engineering - Abstract
A complete mass transfer model was established for an internal loop airlift reactor. All sections of the reactor, including bottom, riser, top, and downcomer, were taken into account. A numerical method was developed to solve the mass transfer model. The effectiveness of the model was validated by experimental measurements. Based on numerical results of the model, the dynamical mass transfer process in the reactor was analyzed in detail. Some mass transfer characteristics of the airlift reactor were revealed. The results indicated that the proposed model well predicted the mass transfer in the internal loop airlift reactor.
- Published
- 2015
12. Online application oriented calculation of the exhaust steam wetness fraction of the low pressure cylinder in thermal power plant
- Author
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Jingqi Yuan and Liang Xu
- Subjects
Engineering ,Petroleum engineering ,business.industry ,Combined cycle ,Superheated steam ,food and beverages ,Energy Engineering and Power Technology ,Thermal power station ,Surface condenser ,Steam-electric power station ,complex mixtures ,humanities ,Industrial and Manufacturing Engineering ,law.invention ,Steam turbine ,Heat recovery steam generator ,law ,Feedwater heater ,Process engineering ,business - Abstract
Online performance monitoring of the steam turbine system is very important for the economic and safe operation of a power plant. For a subcritical steam turbine system, the wet saturated steam in the last few stages of the low pressure cylinder (LPC) increases the heat loss and threatens the unit safety. Unfortunately, online measurement of the exhaust steam wetness fraction of the LPC has been a difficult task for a long time. This paper proposes an online applicable approach based on two equivalent overall efficiency models to monitor the exhaust steam wetness fraction. Firstly, to estimate the total energy entering the steam turbine system, the lumped models of the evaporation system and the heat exchangers are established. Then two equivalent overall efficiency models of the steam turbine system are presented. Based on the same overall efficiency, the exhaust steam wetness fraction is therefore identified. The effectiveness of the proposed approach is validated through the comparison between the calculated and the designed operation data of a subcritical coal-fired unit. As the extension of the applications, the calculated wetness fraction is further used to estimate the thermal economic indices for the purpose of assessing the operation performance of the steam turbine system.
- Published
- 2015
13. Batch Process Monitoring with GTucker2 Model
- Author
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Lijia Luo, Zengliang Gao, Jingqi Yuan, and Shiyi Bao
- Subjects
Computer science ,General Chemical Engineering ,Synchronization (computer science) ,Process (computing) ,Benchmark (computing) ,Batch processing ,General Chemistry ,Fault (power engineering) ,Algorithm ,Industrial and Manufacturing Engineering ,Fault detection and isolation - Abstract
In this paper, the GTucker2 model is proposed for monitoring both even-length and uneven-length batch processes. The GTucker2 model has two prominent advantages. The first one is that it performs tensor decomposition on the three-way data array and thus avoids potential problems of information loss and “curse of dimensionality” induced by data unfolding. The second one is that it solves the uneven-length problem in a “natural” way without using batch trajectory synchronization, which prevents distorting data and fault patterns and guarantees higher modeling and monitoring precisions. An online batch process monitoring method is then developed by integrating GTucker2 with the moving data window technique. Three monitoring statistics named Q, R2, and T2 statistics are constructed for fault detection and diagnosis. The effectiveness and advantages of the GTucker2-based monitoring method are illustrated by two case studies in a benchmark fed-batch penicillin fermentation process.
- Published
- 2014
14. Tensor Global-Local Preserving Projections for Batch Process Monitoring
- Author
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Lijia Luo, Shiyi Bao, Jingqi Yuan, and Zengliang Gao
- Subjects
Basis (linear algebra) ,Computer science ,General Chemical Engineering ,Tensor (intrinsic definition) ,Principal component analysis ,Batch processing ,General Chemistry ,Tensor ,Algorithm ,Industrial and Manufacturing Engineering ,Plot (graphics) ,Statistic ,Fault detection and isolation - Abstract
A novel data projection algorithm named tensor global-local preserving projections (TGLPP) is proposed for three-way data arrays. TGLPP is able to preserve global and local structures of data simultaneously. TGLPP builds a unified framework for global structure preserving and local structure preserving. Tensor principal component analysis (TPCA) and tensor locality preserving projections (TLPP) are unified in the TGLPP framework. They are proved to be two limiting cases of TGLPP. A batch process monitoring method is then developed on the basis of TGLPP. The SPD statistic and R2 statistic are used for fault detection. The contribution plot is applied for fault identification. Two case studies are carried out to validate the efficiency of TGLPP-based monitoring method.
- Published
- 2014
15. Batch Process Monitoring with Tensor Global–Local Structure Analysis
- Author
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Lijia Luo, Jingqi Yuan, Zengliang Gao, and Shiyi Bao
- Subjects
Computer science ,General Chemical Engineering ,General Chemistry ,computer.software_genre ,Industrial and Manufacturing Engineering ,Fault detection and isolation ,Tensor (intrinsic definition) ,Principal component analysis ,Benchmark (computing) ,Batch processing ,Data mining ,Tensor ,Projection (set theory) ,computer ,Statistic - Abstract
A novel method named tensor global–local structure analysis (TGLSA) is proposed for batch process monitoring. Different from principal component analysis (PCA) and locality preserving projections (LPP), TGLSA aims at preserving both global and local structures of data. Consequently, TGLSA has the ability to extract more meaningful information from data than PCA and LPP. Moreover, the tensor-based projection strategy makes TGLSA more applicable for the three-dimensional data than multiway-based methods, such as MPCA and MLPP. A TGLSA-based online monitoring approach is developed by combining TGLSA with a moving window technique. Two new statistics, i.e., SPD and R2 statistics, are constructed for fault detection and diagnosis. In particular, the R2 statistic is a novel monitoring statistic, which is proposed based on a support tensor domain description method. The effectiveness and advantages of the TGLSA-based monitoring approach are illustrated by a benchmark fed-batch penicillin fermentation process.
- Published
- 2013
16. Time–Frequency Analysis Based Flow Regime Identification Methods for Airlift Reactors
- Author
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Lijia Luo, Yuanyuan Xu, Ying Yan, and Jingqi Yuan
- Subjects
Identification methods ,Physics ,Chromatography ,General Chemical Engineering ,Airlift ,Wavelet transform ,General Chemistry ,Mechanics ,Signal ,Industrial and Manufacturing Engineering ,Radio spectrum ,Time–frequency analysis ,Distribution (mathematics) ,Flow (mathematics) - Abstract
The flow regime transitions in an airlift reactor were investigated based on pressure fluctuation signals. Two time–frequency analysis methods, i.e., Wigner–Ville distribution and wavelet transform, were used to extract flow regime characteristics from pressure signals. The main frequency derived from the smoothed pseudo-Wigner–Ville distribution of the pressure signal was used to quantify flow regime transitions in the reactor. Two flow regime transition points were successfully detected from the evolution of main frequencies of pressure signals. In addition, the local dynamic characteristics of the pressure signal at different frequency bands were analyzed by use of the wavelet transform. A new flow regime identification method based on the wavelet entropy of the pressure signal was proposed. This method was confirmed to be reliable and efficient to detect flow regime transitions in the reactor.
- Published
- 2012
17. Hilbert–Huang transform, Hurst and chaotic analysis based flow regime identification methods for an airlift reactor
- Author
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Ying Yan, Jingqi Yuan, Yuanyuan Xu, Lijia Luo, Junwei Sun, and Ping Xie
- Subjects
Physics ,Hurst exponent ,Correlation dimension ,General Chemical Engineering ,Mathematical analysis ,Autocorrelation ,Wavelet transform ,Thermodynamics ,General Chemistry ,Lyapunov exponent ,Industrial and Manufacturing Engineering ,Hilbert–Huang transform ,symbols.namesake ,symbols ,Detrended fluctuation analysis ,Environmental Chemistry ,Hilbert spectrum - Abstract
The flow regimes and their transitions in an internal loop airlift reactor were investigated. The Hilbert–Huang transform (HHT) was applied to analyze the energy–frequency–time distribution of the pressure signal. It was found that the Hilbert spectrum of the pressure signal was closely related to the superficial gas velocity. The stochastic behaviors of intrinsic mode functions (IMFs) extracted from the pressure signal were studied using the Hurst analysis. Two different Hurst exponents were obtained for each pressure signal: one was smaller than 0.5, while the other was larger than 0.5, representing the anti-persistent and persistent hydrodynamic behaviors, respectively. The evolution of the larger Hurst exponent clearly indicated flow regime transitions in the downcomer. The wavelet transform combined with the autocorrelation analysis were applied to extract chaotic components of the pressure signal. Two flow regime transition points were successfully detected from the evolution of chaotic parameters, i.e. the largest Lyapunov exponent, correlation dimension and Kolmogorov entropy.
- Published
- 2012
18. Identification of flow regime transitions in an annulus sparged internal loop airlift reactor based on higher order statistics and Winger trispectrum
- Author
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Jingqi Yuan, Yuanyuan Xu, and Lijia Luo
- Subjects
Physics ,Applied Mathematics ,General Chemical Engineering ,Multiphase flow ,Higher-order statistics ,Astrophysics::Cosmology and Extragalactic Astrophysics ,General Chemistry ,Mechanics ,Industrial and Manufacturing Engineering ,Moment (mathematics) ,Nonlinear system ,Classical mechanics ,Flow (mathematics) ,Annulus (firestop) ,Trispectrum ,Bispectrum - Abstract
Higher order statistics and Wigner higher order moment spectra were used to extract useful flow regime characteristics from wall pressure fluctuation signals in an annulus sparged internal loop airlift reactor. It is found that the pressure fluctuation in the airlift reactor is a typical nonlinear and non-stationary process, which exhibits different frequency characteristics depending on flow regimes. Analysis methods based on bispectrum and Wigner trispectrum are powerful tools to reveal frequency characteristics of pressure signals. To identify flow regime transitions in the reactor, two new characteristic quantities, namely average bispectrum and generalized average frequency, are defined from bispectrum and Wigner trispectrum of the pressure signal, respectively. Two flow regime transition points corresponding to three flow regimes in the reactor are successfully detected by using these two characteristic quantities.
- Published
- 2011
19. Prediction of the Profit Function for Industrial 2-Keto-L-Gulonic Acid Cultivation
- Author
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Jingqi Yuan, Yuanyuan Xu, Lei Cui, Hongtao Wu, and Qian Jia
- Subjects
Engineering ,Mathematical optimization ,business.industry ,General Chemical Engineering ,Mean squared prediction error ,Scheduling (production processes) ,General Chemistry ,Industrial and Manufacturing Engineering ,Profit (economics) ,2-keto-L-gulonic acid ,Support vector machine ,Optimal scheduling ,Batch processing ,business ,Simulation - Abstract
The profit function is the generic criterion to describe the cost effect of a batch process. To focus on the prediction of the profit function for 2-keto-L-gulonic acid (2-KGA) cultivation, which is potentially applicable for process monitoring and optimal scheduling, rolling learning-prediction (RLP) based on a support vector machine (SVM) is applied. The RLP implies that the SVM training database is rolling updated as the batch of current interest proceeds, and the SVM learning is then repeated for the prediction. The database is further updated after termination of a batch. The updating procedures are investigated in detail. Pseudo-online prediction is carried out using the data from industrial-scale 2-KGA cultivation under actual and hypothetical inoculation sequences. The results indicate that the average relative prediction error is less than 5 % in the later phase of fermentation in all inoculation sequences.
- Published
- 2011
20. Computational Approach to Characterize the Mass Transfer between the Counter-Current Gas-Liquid Flow
- Author
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S. Paschke, Jingqi Yuan, Jens-Uwe Repke, Günter Wozny, and Yuanyuan Xu
- Subjects
Pressure drop ,Chemistry ,business.industry ,General Chemical Engineering ,Momentum transfer ,Thermodynamics ,General Chemistry ,Mechanics ,Penetration (firestop) ,Computational fluid dynamics ,Industrial and Manufacturing Engineering ,law.invention ,Physics::Fluid Dynamics ,chemistry.chemical_compound ,law ,Propane ,Mass transfer ,Volume of fluid method ,business ,Distillation - Abstract
Structured packed columns are widely used in the chemical industry for distillation and absorption. However, the understanding of the transfer mechanism behind the counter-current gas-liquid flow in structured packed columns is still limited. In this work, a three-dimensional CFD model that considers the local absorption and the local momentum transfer mechanism is developed for a film flow on a small plate with a counter-current gas flow. The model, based on the Volume of Fluid (VOF) method, is built up on the basis of a pressure drop model and the penetration theory to quantitatively investigate the instantaneous hydrodynamics and mass transfer characteristics of the liquid phase. Simulations and experiments are carried out for a system consisting of propane and toluene. A comparison of the simulation results with the experimental data for the outlet concentrations shows good agreement.
- Published
- 2009
21. On-line application oriented optimal scheduling for penicillin fed-batch fermentation
- Author
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K.L. Hu, Jingqi Yuan, H.T. Wu, Q. Jia, and Y.F. Xue
- Subjects
Engineering ,Mathematical optimization ,Batch fermentation ,business.industry ,Process Chemistry and Technology ,General Chemical Engineering ,Scheduling (production processes) ,Energy Engineering and Power Technology ,General Chemistry ,Industrial engineering ,Industrial and Manufacturing Engineering ,Profit (economics) ,Original data ,Penicillin ,Optimal scheduling ,medicine ,business ,medicine.drug - Abstract
An on-line application oriented scheduling approach for cultivation periods of penicillin fed-batch fermentation is proposed to maximize the economic profit of the whole workshop. The approach consists of profit function calculation, profit potential prediction, on-line batch classification and scheduling decision-making. The objective function is to maximize the total economic profit of those batches in parallel operation by repeated updating of the termination sequence while without significant disturbance on upstream and downstream work sections. Pseudo-on-line simulations of re-scheduling on industrial penicillin cultivations demonstrate the potential benefits of the approach. The original data is from a Chinese pharmaceutical company which consists of 58 industrial batches of penicillin fed-batch cultivation under empirical operation. Re-scheduling is carried out under three different inoculation sequences and the simulation results indicate that 2–3% of total profit increase could be generally achieved, compared with the empirical one.
- Published
- 2009
22. Batch process monitoring with tensor factorization
- Author
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Kunlun Hu and Jingqi Yuan
- Subjects
Mathematical optimization ,Locality ,Space (mathematics) ,Industrial and Manufacturing Engineering ,Data matrix (multivariate statistics) ,Computer Science Applications ,Matrix (mathematics) ,Control and Systems Engineering ,Modeling and Simulation ,Tensor (intrinsic definition) ,Principal component analysis ,Benchmark (computing) ,Batch processing ,Algorithm ,Mathematics - Abstract
A batch process monitoring method using tensor factorization, tensor locality preserving projections (TLPP), is proposed. In many existing vector-based methods on batch process monitoring such as MPCA and MLPP, a batch data is represented as a vector in high-dimensional space. But vectorizing batch data will lead to information loss. Essentially, a batch data is presented as a second order tensor, or a matrix. In this case, tensor factorization may be used to deal with the two-way batch data matrix directly instead of performing vectorizing procedure. Furthermore, tensor representation has some advantages such as low memory and storage requirements and less estimated parameters for normal operating condition (NOC) model. On the other hand, different from principal component analysis (PCA) which aims at preserving the global Euclidean structure of the data, the TLPP aims to preserve the local neighborhood information and to detect the intrinsic manifold structure of the data. Consequently, TLPP may be used to find more meaningful intrinsic information hidden in the observations. The effectiveness and advantages of the TLPP monitoring approach are tested with the data from a benchmark fed-batch penicillin fermentation and two industrial fermentation processes, penicillin and cephalosporin, respectively.
- Published
- 2009
23. Portraying the Countercurrent Flow on Packings by Three-Dimensional Computational Fluid Dynamics Simulations
- Author
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S. Paschke, Jingqi Yuan, Jens-Uwe Repke, G. Wozny, and Yuanyuan Xu
- Subjects
Engineering ,business.industry ,Countercurrent exchange ,General Chemical Engineering ,General Chemistry ,Mechanics ,Computational fluid dynamics ,Industrial and Manufacturing Engineering ,Volumetric flow rate ,Open-channel flow ,Physics::Fluid Dynamics ,Hele-Shaw flow ,Flow (mathematics) ,Drag ,Volume of fluid method ,business ,Simulation - Abstract
The design of packed columns requires the detailed description of the hydrodynamics on the surface of the packings. To analyze the local flow behavior of the liquid phase, a three-dimensional Computational Fluid Dynamics (CFD) model was developed that applies to the two-phase countercurrent flow on an inclined and flat plate. This model, based on the volume-of-fluid (VOF) method, considers the gravity, the surface tension and the drag force between the two phases. The development of such a model allows investigation of the influences of the liquid and gas flow rates on the flow behavior such as the film flow and the rivulet flow. A validation of the model was performed using data from the literature and from experiments conducted in this work. Simulation and experimental results demonstrate that the specific wetted area on the plate decreases with decreasing liquid load. Moreover, CFD simulations reveal that the presence of the countercurrent gas phase tends to increase the fluctuation and the thickness of the film flow, which is in accordance with experimental data. It also affects the flow behavior of the rivulet flow and changes the velocity profiles for both film and rivulet flow behavior. On the other hand, the simulation results indicate that CFD is a potent tool for analyzing and investigating the flow phenomena in chemical engineering.
- Published
- 2008
24. Multivariate statistical process control based on multiway locality preserving projections
- Author
-
Jingqi Yuan and Kunlun Hu
- Subjects
Computer science ,business.industry ,Dimensionality reduction ,Mean squared prediction error ,Statistical index ,Locality ,Moving window ,Pattern recognition ,Industrial and Manufacturing Engineering ,Computer Science Applications ,Multivariate statistical process control ,Control and Systems Engineering ,Robustness (computer science) ,Modeling and Simulation ,Artificial intelligence ,business ,Statistic - Abstract
An approach for multivariate statistical process control based on multiway locality preserving projections (LPP) is presented. The recently developed LPP is a linear dimensionality reduction technique for preserving the neighborhood structure of the data set. It is characterized by capturing the intrinsic structure of the observed data and finding more meaningful low-dimensional information hidden in the high-dimensional observations compared with PCA. In this study, LPP is used to extract the intrinsic geometrical structure of the process data. Hotelling’s T 2 ( D ) and the squared prediction error (SPE or Q ) statistic charts for on-line monitoring are then presented, and the contribution plots of these two statistical indices are used for fault diagnosis. Moreover, a moving window technique is used for the implementation of on-line monitoring. Case study was carried out with the data of industrial penicillin fed-batch cultivations. As a comparison, the results obtained with the MPCA are also presented. It is concluded that the Multiway LPP (MLPP) outperforms the conventional MPCA. Finally, the robustness of the MLPP monitoring is analyzed by adding noises to the original data.
- Published
- 2008
25. Scheduling Model for a Multi-Product Batch Plant Using a Pre-Ordering Approach
- Author
-
Jingqi Yuan and Yaofeng Xue
- Subjects
Mathematical optimization ,Computer science ,General Chemical Engineering ,Scheduling (production processes) ,Multicomponent systems ,Binary number ,General Chemistry ,Multi product ,Industrial and Manufacturing Engineering ,Effective solution - Abstract
A scheduling model for a multi-product, multistage batch plant with parallel units is presented. The objective is to maximize the weighted completion times of orders in every processing stage while imposing a penalty on the slower orders. The proposed model uses the continuous-time representation mode and describes the allocations of tasks, units and stages by a set of binary variables. In order to reduce the model size and provide a more effective solution to the model, a pre-ordering approach that sorts the processing sequence of orders is developed. The pre-ordering approach identifies the infeasible assignments through which the number of binary variables is significantly reduced. Illustrative examples are provided to show that the size of the proposed model is small, and therefore, needs much less computational effort in comparison with the existing models in the literature.
- Published
- 2008
26. A model-based estimation of the profit function for the continuous fermentation of baker's yeast
- Author
-
L. Jia, N.S. Luo, and Jingqi Yuan
- Subjects
Engineering ,State variable ,Profit (accounting) ,Operations research ,business.industry ,Process Chemistry and Technology ,General Chemical Engineering ,media_common.quotation_subject ,Energy Engineering and Power Technology ,Biomass ,General Chemistry ,Industrial and Manufacturing Engineering ,Yeast ,Continuous production ,Scientific method ,Production (economics) ,Biochemical engineering ,business ,Function (engineering) ,media_common - Abstract
A profit function is established to evaluate the economic performance of baker's yeast continuous production. A structured kinetic model for baker's yeast Saccharomyces cerevisiae is applied to estimate the key state variables of the process, such as biomass and ethanol concentration. Taking possible time variant dynamics into account, a rolling identification approach is used to identify several key model parameters online so as to adapt the changing dynamics of the process. The well predicted biomass concentration makes the profit function online predictable very well. This investigation may benefit the study on profit optimization of the process.
- Published
- 2007
27. Prediction of Key State Variables using Support Vector Machines in Bioprocesses
- Author
-
Yunfeng Li and Jingqi Yuan
- Subjects
State variable ,Engineering ,Artificial neural network ,Property (programming) ,business.industry ,General Chemical Engineering ,Process (computing) ,General Chemistry ,Machine learning ,computer.software_genre ,Industrial and Manufacturing Engineering ,Support vector machine ,Key (cryptography) ,Process control ,Artificial intelligence ,Bioprocess ,business ,computer - Abstract
Support vector machines (SVM) are applied to the prediction of key state variables in bioprocesses, such as product concentration and biomass concentration, which commonly play an important role in bioprocess monitoring and control. A so-called rolling learning-prediction procedure is used to deal with the time variant property of the process, and to establish the training database for the SVM predictor, which is characterized with the rolling update of the training database. As an example, product concentration in industrial penicillin production is predicted, and a comparison is also made with three different artificial neural network architectures (FBNN, RBFN, and RNN). The test results indicate that a prediction accuracy of 1-3 % can be obtained for 4-40h ahead prediction using the SVM, which is better than the best of the three artificial neural networks (ANNs). Moreover, for noise-added training highly noisy data or small-sample learning, the SVM also clearly outper-forms FBNN, RBFN, and RNN.
- Published
- 2006
28. Switching stabilisation and pole placement of uncertain switched systems
- Author
-
Jingqi Yuan and Ke Hu
- Subjects
Block cipher mode of operation ,Computer Networks and Communications ,Efficient algorithm ,Linear matrix inequality ,Pole location ,Linear matrix ,Industrial and Manufacturing Engineering ,Computer Science Applications ,Quadratic equation ,Control theory ,Full state feedback ,Electrical and Electronic Engineering ,Robust control ,Software ,Information Systems ,Mathematics - Abstract
Robust controllers that ensure closed-loop pole placement are designed for uncertain discrete-time switched systems. A robust switching rule is proposed combined with the switched static output feedback controllers to ensure 1) quadratic stabilisation of the resulting closed-loop system, 2) pole location inside a circle for each linear mode of operation. The switching rule is state-dependent and does not rely on any uncertainties. All the results are expressed in terms of linear matrix inequalities (LMIs), which can be easily tested with efficient algorithms.
- Published
- 2011
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