Search results for: Batch Reactor

Authors: Chin-Hung Li, Te-Ming Chen, Ying-Chuan Chen, Shuen-Tai Wang

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This paper proposes a new approach to offer a private cloud service in HPC clusters. In particular, our approach relies on automatically scheduling users- customized environment request as a normal job in batch system. After finishing virtualization request jobs, those guest operating systems will dismiss so that compute nodes will be released again for computing. We present initial work on the innovative integration of HPC batch system and virtualization tools that aims at coexistence such that they suffice for meeting the minimizing interference required by a traditional HPC cluster. Given the design of initial infrastructure, the proposed effort has the potential to positively impact on synergy model. The results from the experiment concluded that goal for provisioning customized cluster environment indeed can be fulfilled by using virtual machines, and efficiency can be improved with proper setup and arrangements.

Keywords: Cloud Computing, HPC Cluster, Private Cloud, Virtualization

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Authors: B. K. Kim, D. Chang, D. J. Son, D. W. Kim, J. K. Choi, H. J. Yeon, C. Y. Yoon, Y. Fan, S. Y. Lim, K. H. Hong

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Intermittent aeration process can be easily applied on the existing activated sludge system and is highly reliable against the loading changes. It can be operated in a relatively simple way as well. Since the moving-bed biofilm reactor method processes pollutants by attaching and securing the microorganisms on the media, the process efficiency can be higher compared to the suspended growth biological treatment process, and can reduce the return of sludge. In this study, the existing intermittent aeration process with alternating flow being applied on the oxidation ditch is applied on the continuous flow stirred tank reactor with advantages from both processes, and we would like to develop the process to significantly reduce the return of sludge in the clarifier and to secure the reliable quality of treated water by adding the moving media. Corresponding process has the appropriate form as an infrastructure based on u- environment in future u- City and is expected to accelerate the implementation of u-Eco city in conjunction with city based services. The system being conducted in a laboratory scale has been operated in HRT 8hours except for the final clarifier and showed the removal efficiency of 97.7 %, 73.1 % and 9.4 % in organic matters, TN and TP, respectively with operating range of 4hour cycle on system SRT 10days. After adding the media, the removal efficiency of phosphorus showed a similar level compared to that before the addition, but the removal efficiency of nitrogen was improved by 7~10 %. In addition, the solids which were maintained in MLSS 1200~1400 at 25 % of media packing were attached all onto the media, which produced no sludge entering the clarifier. Therefore, the return of sludge is not needed any longer.

Keywords: Municipal wastewater treatment, Biological nutrient removal, Alternating flow intermittent aeration system, Reversal flow intermittent aeration system, Moving-bed biofilm reactor, CFSTR, u-City, u-Eco city

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: S. H. Mirhossaini, H. Godini, A. Jafari

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Biological Ammonia removal (nitrification), the oxidation of ammonia to nitrate catalyzed by bacteria, is a key part of global nitrogen cycling. In the first step of nitrification, chemolithoautotrophic ammonia oxidizer transform ammonia to nitrite, this subsequently oxidized to nitrate by nitrite oxidizing bacteria. This process can be affected by several factors. In this study the effect of influent COD on biological ammonia removal in a bench-scale biological reactor was investigated. Experiments were carried out using synthetic wastewater. The initial ammonium concentration was 25mgNH4 +-N L-1. The effect of COD between 247.55±1.8 and 601.08±3.24mgL-1 on biological ammonia removal was investigated by varying the COD loading supplied to reactor. From the results obtained in this study it could be concluded in the range of 247.55±1.8 to 351.35±2.05mgL-1, there is a direct relationship between amount of COD and ammonia removal. However more than 351.35±2.05 up to 601.08±3.24mgL-1 were found an indirect relationship between them.

Keywords: Ammonia biological removal, Nitrification, InfluentCOD.

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Authors: N. Messaadia, D. Harzallah

Abstract:

The effects of divers carbon substrates were investigated for the tabtoxin production of an isolated pathogenic Pseudomonas syringae pv. tabaci, the causal agent of wildfire of tobacco and are discussed in relation to the bacterium growth. The isolated organism was grown in batch culture on Woolley's medium (28°C, 200 rpm, during 5 days). The growth has been measured by the optical density (OD) at 620 nm and the tabtoxin production quantified by Escherichia coli (K-12) bioassay technique. The growth and the tabtoxin production were both influenced by the substrates (sugars, amino acids, organic acids) used, each, as a sole carbon source and as a supplement for the same amino acids. The most significant quantities of tabtoxin were obtained in presence of some amino acids used as sole carbon source and/or as supplement.

Keywords: Amino acid supplement, carbon substrates, batch culture, Pseudomonas syringae pv. tabaci.

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Authors: Janhavi Inamdar, S.K. Singh

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Laboratory experiments have been performed to investigate photocatalytic detoxification by using TiO2 photocatalyst for treating dairy effluent. Various operational parameters such as catalyst concentration, initial concentration, angle of tilt of solar flat plate reactor and flow rate were investigated. Results indicated that the photocatalytic detoxification process can efficiently treat dairy effluent. Experimental runs with dairy wastewater can be used to identify the optimum operational parameters to perform wastewater degradation on large scale for recycling purpose. Also effect of two different types of reactors on degradation process was analyzed.

Keywords: Photocatalytic detoxification, TiO2 photocatalyst, solar flat plate reactor, Zero effluent discharge.

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Authors: P. Georgieva, S. Feyo de Azevedo

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This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: H.A. Gasim, S.R.M. Kutty, M.H. Isa, M.P.M. Isa

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Petroleum refineries discharged large amount of wastewater -during the refining process- that contains hazardous constituents that is hard to degrade. Anaerobic treatment process is well known as an efficient method to degrade high strength wastewaters. Up-flow Anaerobic Sludge Blanker (UASB) is a common process used for various wastewater treatments. Two UASB reactors were set up and operated in parallel to evaluate the treatment efficiency of petroleum refinery wastewater. In this study four organic volumetric loading rates were applied (i.e. 0.58, 0.89, 1.21 and 2.34 kg/m3·d), two loads to each reactor. Each load was applied for a period of 60 days for the reactor to acclimatize and reach steady state, and then the second load applied. The chemical oxygen demand (COD) removals were satisfactory with the removal efficiencies at the loadings applied were 78, 82, 83 and 81 % respectively.

Keywords: Petroleum refinery wastewater, anaerobic treatment, UASB, organic volumetric loading rate

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Authors: Sheng-Ming Huang, Nan-Chyuan Tsai, Chih-Che Lin, Chun-Chi Lin

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An innovative design for intelligent Chemical Mechanical Polishing (CMP) system is proposed and verified by experiments in this report. On-line measurement and real-time feedback are integrated to eliminate the shortcomings of traditional approaches, e.g., the batch-to-batch discrepancy of required polishing time, over consumption of chemical slurry, and non-uniformity across the wafer. The major advantage of the proposed method is that the finish of local surface roughness can be consistent, no matter where the inner-ring region or outer-ring region is concerned. Secondly, it is able to eliminate the Edge effect. Conventionally, the interfacial induced stress near the wafer edge is generally much higher than that near the wafer center. At last, by using the proposed intelligent chemical mechanical polishing strategy, the cost of the entire machining cycle can be much reduced while the quality of the finished goods certainly upgraded.

Keywords: Chemical Mechanical Polishing, Active Magnetic Actuator, On-Line Measurement.

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Authors: Shilpi Kushwaha, Suparna Sodaye, P. Padmaja

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Palm shell obtained from coastal part of southern India was studied for the removal for the adsorption of Hg (II) ions. Batch adsorption experiments were carried out as a function of pH, concentration of Hg (II) ions, time, temperature and adsorbent dose. Maximum removal was seen in the range pH 4.0- pH 7.0. The palm shell powder used as adsorbent was characterized for its surface area, SEM, PXRD, FTIR, ion exchange capacity, moisture content, and bulk density, soluble content in water and acid and pH. The experimental results were analyzed using Langmuir I, II, III, IV and Freundlich adsorption isotherms. The batch sorption kinetics was studied for the first order reversible reaction, pseudo first order; pseudo second order reaction and the intra-particle diffusion reaction. The biomass was successfully used for removal Hg (II) from synthetic and industrial effluents and the technique appears industrially applicable and viable.

Keywords: Biosorbent, mercury removal, borassus flabellifer, isotherms, kinetics, palm shell.

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Authors: W. E. Igwegbe, B. C. Okoro, J. C. Osuagwu

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The study assessed the effectiveness of Pawpaw (Carica papaya) wood in reducing the concentrations of heavy metals in wastewater acting as a bio-sorbent. The following heavy metals were considered; Zinc, Cadmium, Lead, Copper, Iron, Selenium, Nickel and Manganese. The physiochemical properties of Carica papaya stem were studied. The experimental sample was sourced from the trunk of a felled matured pawpaw tree. Wastewater for experimental use was prepared by dissolving soil samples collected from a dump site at Owerri, Imo state of Nigeria in water. The concentration of each metal remaining in solution as residual metal after bio-sorption was determined using Atomic absorption Spectrometer. The effects of pH and initial heavy metal concentration were studied in a batch reactor. The results of Spectrometer test showed that there were different functional groups detected in the Carica papaya stem biomass. There was increase in metal removal as the pH increased for all the metals considered except for Nickel and Manganese. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml solution of bio-sorbent. The results of the study showed that the treated wastewater is fit for irrigation purpose based on Canada wastewater quality guideline for the protection of Agricultural standard. This approach thus provides a cost effective and environmentally friendly option for treating wastewater.

Keywords: Biomass, bio-sorption, Carica papaya, heavy metal, wastewater.

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Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and Validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) where in the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation & Control design team. This paper discusses about the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), Steady State, Transient State.

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Authors: H. Godini, A. Rezaee, A. Jafari, S. H. Mirhousaini

Abstract:

A Laboratory-scale packed bed reactor with microbial cellulose as the biofilm carrier was used to investigate the denitrification of high-strength nitrate wastewater with specific emphasis on the effect the nitrogen loading rate and hydraulic retention time. Ethanol was added as a carbon source for denitrification. As a result of this investigation, it was found that up to 500 mg/l feed nitrate concentration the present system is able to produce an effluent with nitrate content below 10 ppm at 3 h hydraulic retention time. The highest observed denitrification rate was 4.57 kg NO3-N/ (m3 .d) at a nitrate load of 5.64 kg NO3- N/(m3 .d), and removal efficiencies higher than 90% were obtained for loads up to 4.2 kg NO3-N/(m3 .d). A mass relation between COD consumed and NO3-N removed around 2.82 was observed. This continuous-flow bioreactor proved an efficient denitrification system with a relatively low retention time.

Keywords: Biological nitrate removal, Denitrification, Microbial cellulose, Packed-bed reactor.

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

Abstract:

Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modeling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modeled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: Flow Coastdown, Loop Coolant Inertia, Modeling, Research Reactor.

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Authors: Sallem F., Dahhou B., Kamoun A.

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In this work, the main problem considered is the  detection and the isolation of the actuator fault. A new formulation of  the linear system is generated to obtain the conditions of the actuator  fault diagnosis. The proposed method is based on the representation  of the actuator as a subsystem connected with the process system in  cascade manner. The designed formulation is generated to obtain the  conditions of the actuator fault detection and isolation. Detectability  conditions are expressed in terms of the invertibility notions. An  example and a comparative analysis with the classic formulation  illustrate the performances of such approach for simple actuator fault  diagnosis by using the linear model of nuclear reactor.

 

Keywords: Actuator fault, Fault detection, left invertibility, nuclear reactor, observability, parameter intervals, system inversion.

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Authors: S.Shokri, S.Zahedi, M.Ahmadi Marvast, B. Baloochi, H.Ganji

Abstract:

In this research, a systematic investigation was carried out to determine the optimum conditions of HDS reactor. Moreover, a suitable model was developed for a rigorous RTO (real time optimization) loop of HDS (Hydro desulfurization) process. A systematic experimental series was designed based on CCD (Central Composite design) and carried out in the related pilot plant to tune the develop model. The designed variables in the experiments were Temperature, LHSV and pressure. However, the hydrogen over fresh feed ratio was remained constant. The ranges of these variables were respectively equal to 320-380ºC, 1- 21/hr and 50-55 bar. a power law kinetic model was also developed for our further research in the future .The rate order and activation energy , power of reactant concentration and frequency factor of this model was respectively equal to 1.4, 92.66 kJ/mol and k0=2.7*109 .

Keywords: Statistical model, Multiphase Reactors, Gas oil, Hydrodesulfurization, Optimization, Kinetics

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Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb

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In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination.

Keywords: Adaptive Learning rate, Adaptive momentum, Autoregressive, Modeling, Neural Network.

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Authors: H. A. Gasim, S. R. M. Kutty, M. Hasnain Isa

Abstract:

Anaerobic treatment has many advantages over other biological method particularly when used to treat complex wastewater such as petroleum refinery wastewater. In this study two Up-flow Anaerobic Sludge Blanket (UASB) reactors were operated in parallel to treat six volumetric organic loads (0.58, 1.21, 0.89, 2.34, 1.47 and 4.14 kg COD/m3·d) to evaluate the chemical oxygen demand (COD) removal efficiency. The reactors were continuously adapting to the changing of operation condition with increase in the removal efficiency or slight decrease until the last load which was more than two times the load, at which the reactor stressed and the removal efficiency decreased to 75% with effluent concentration of 1746 mg COD/L. Other parameters were also monitored such as pH, alkalinity, volatile fatty acid and gas production rate. The UASB reactor was suitable to treat petroleum refinery wastewater and the highest COD removal rate was 83% at 1215 kg/m3·d with COD concentration about 356 mg/L in the effluent.

Keywords: Petroleum refinery wastewater, anaerobic digestion, UASB, organic volumetric loading rate

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Heather Wyman-Pain, Yuankai Bian, Furong Li

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The decreasing use of fossil fuel power stations has a negative effect on the stability of the electricity systems in many countries. Nuclear power stations have traditionally provided minimal ancillary services to support the system but this must change in the future as they replace fossil fuel generators. This paper explains the development of the four most popular reactor types still in regular operation across the world which have formed the basis for most reactor development since their commercialisation in the 1950s. The use of nuclear power in four countries with varying levels of capacity provided by nuclear generators is investigated, using the primary frequency response provided by generators as a measure for the electricity networks stability, to assess the need for nuclear generators to provide additional support as their share of the generation capacity increases.

Keywords: Frequency control, nuclear power generation, power system stability, system inertia.

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio D. Grieco, Emanuela Guerriero

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Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from a real-life pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: Constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries.

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Authors: I. Moraitopoulos, Z. Ioannou, J. Simitzis

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The present study examines the adsorption of phenol, 3-nitrophenol and dyes (methylene blue, alizarine yellow), from aqueous solutions onto a commercial activated carbon. Two different operations, semi-batch and continuous with reflux, were applied. The commercial activated carbon exhibits high adsorption abilities for phenol, 3-nitrophenol and dyes (methylene blue and alizarin yellow) from their aqueous solutions. The adsorption of all adsorbates after 1 h is higher by the continuous operation with reflux than by the semibatch operation. The adsorption of phenol is higher than that of 3-nitrophenol for both operations. Similarly, the adsorption of alizarin yellow is higher than that of methylene blue for both operations. The regenerated commercial activated carbon regains its adsorption ability due to the removal of the adsorbate from its pores during the regeneration.

Keywords: Activated carbon, adsorption, phenols, dyes.

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Authors: Petia Georgieva, Sebastião Feyo de Azevedo

Abstract:

This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.

Keywords: Feed forward neural network, process modelling, model predictive control, crystallization process.

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Authors: Renzo Carta, Francesco Desogus

Abstract:

Variations in the growth rate constant of the Listeria monocytogenes bacterial species were determined at 37°C in irradiated environments and compared to the situation of a nonirradiated environment. The bacteria cells, contained in a suspension made of a nutrient solution of Brain Heart Infusion, were made to grow at different frequency (2.30e2.60 GHz) and power (0e400 mW) values, in a plug flow reactor positioned in the irradiated environment. Then the reacting suspension was made to pass into a cylindrical cuvette where its optical density was read every 2.5 minutes at a wavelength of 600 nm. The obtained experimental data of optical density vs. time allowed the bacterial growth rate constant to be derived; this was found to be slightly influenced by microwave power, but not by microwave frequency; in particular, a minimum value was found for powers in the 50e150 mW field.

Keywords: Growth rate constant, irradiated environment, Listeria monocytogenes, microwaves, plug flow reactor.

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Authors: Mingtao Ding, Zheng Tian, Haixia Xu

Abstract:

The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

Keywords: adaptive method, kernel principal component analysis, online extraction, recursive algorithm

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Authors: S. K. Mohan, T. Viruthagiri, C. Arunkumar

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Tannase (tannin acyl hydrolase, E.C.3.1.1.20) is an important hydrolysable enzyme with innumerable applications and industrial potential. In the present study, a kinetic model has been developed for the batch fermentation used for the production of tannase by A.flavus MTCC 3783. Maximum tannase activity of 143.30 U/ml was obtained at 96 hours under optimum operating conditions at 35oC, an initial pH of 5.5 and with an inducer tannic acid concentration of 3% (w/v) for a fermentation period of 120 hours. The biomass concentration reaches a maximum of 6.62 g/l at 96 hours and further there was no increase in biomass concentration till the end of the fermentation. Various unstructured kinetic models were analyzed to simulate the experimental values of microbial growth, tannase activity and substrate concentration. The Logistic model for microbial growth , Luedeking - Piret model for production of tannase and Substrate utilization kinetic model for utilization of substrate were capable of predicting the fermentation profile with high coefficient of determination (R2) values of 0.980, 0.942 and 0.983 respectively. The results indicated that the unstructured models were able to describe the fermentation kinetics more effectively.

Keywords: Aspergillus flavus, Batch fermentation, Kinetic model, Tannase, Unstructured models.

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Authors: Shan Gao, Zaiming Liu

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This paper treats a discrete-time batch arrival queue with single working vacation. The main purpose of this paper is to present a performance analysis of this system by using the supplementary variable technique. For this purpose, we first analyze the Markov chain underlying the queueing system and obtain its ergodicity condition. Next, we present the stationary distributions of the system length as well as some performance measures at random epochs by using the supplementary variable method. Thirdly, still based on the supplementary variable method we give the probability generating function (PGF) of the number of customers at the beginning of a busy period and give a stochastic decomposition formulae for the PGF of the stationary system length at the departure epochs. Additionally, we investigate the relation between our discretetime system and its continuous counterpart. Finally, some numerical examples show the influence of the parameters on some crucial performance characteristics of the system.

Keywords: Discrete-time queue, batch arrival, working vacation, supplementary variable technique, stochastic decomposition.

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Authors: Seni Karnchanawong, Wachara Phajee

Abstract:

The effects of upflow liquid velocity (ULV) on performance of expanded granular sludge bed (EGSB) system were investigated. The EGSB reactor, made from galvanized steel pipe 0.10 m diameter and 5 m height, had been used to treat piggery wastewater, after passing through acidification tank. It consisted of 39.3 l working volume in reaction zone and 122 l working volume in sedimentation zone, at the upper part. The reactor was seeded with anaerobically digested sludge and operated at the ULVs of 4, 8, 12 and 16 m/h, consecutively, corresponding to organic loading rates of 9.6 – 13.0 kg COD/ (m3.d). The average COD concentrations in the influent were 9,601 – 13,050 mg/l. The COD removal was not significantly different, i.e. 93.0% - 94.0%, except at ULV 12 m/h where SS in the influent was exceptionally high so that VSS washout had occurred, leading to low COD removal. The FCOD and VFA concentrations in the effluent of all experiments were not much different, indicating the same range of treatment performance. The biogas production decreased at higher ULV and ULV of 4 m/h is suggested as design criterion for EGSB system.

Keywords: Expanded granular sludge bed system, piggery wastewater, upflow liquid velocity

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Authors: Hyun-Woo Cho

Abstract:

Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

Abstract:

In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: Emergence procedure, expert system, operator support, PWR nuclear power plant.

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