Search results for: batch digester

Authors: A. Shashank Tiwari, S. P. Mahapatra

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Scale-up is defined as the process of increasing batch size. Scale-up of a process viewed as a procedure for applying the same process to different output volumes. There is a subtle difference between these two definitions: batch size enlargement does not always translate into a size increase of the processing volume. In mixing applications, scale-up is indeed concerned with increasing the linear dimensions from the laboratory to the plant size. On the other hand, processes exist (e.g., tableting) where the term ‘scale-up’ simply means enlarging the output by increasing the speed. To complete the picture, one should point out special procedures where an increase of the scale is counterproductive and ‘scale-down’ is required to improve the quality of the product. In moving from Research and Development (R&D) to production scale, it is sometimes essential to have an intermediate batch scale. This is achieved at the so-called pilot scale, which is defined as the manufacturing of drug product by a procedure fully representative of and simulating that used for full manufacturing scale. This scale also makes it possible to produce enough products for clinical testing and to manufacture samples for marketing. However, inserting an intermediate step between R&D and production scales does not, in itself, guarantee a smooth transition. A well-defined process may generate a perfect product both in the laboratory and the pilot plant and then fail quality assurance tests in production.

Keywords: scale up, research, size, batch

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Authors: Jaemin Kim, Ilsun Pang, Yongrae Cho, Kwanghun Kim, Sungsun Baik

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Manufacturing cost reduction is becoming more important due to excessive oversupply of Single crystalline ingot in recent solar market. Many companies are carrying out extensive research to grow more than one Single crystalline ingot in one batch to reduce manufacturing cost. However what most companies are finding difficult in this process is the effect on ingot due to increasing levels of impurities. Every ingot leaves a certain amount of melt after it is fully grown. This is the impurity that lowers the ingot quality. This impurity increase in the batch after second, third and more are grown subsequently in one batch. In order to solve this problem, the experiment to remove the residual melt in high temperature of hot zone was performed and succeeded. Theoretical average metal concentration of second ingot by new method was calculated and compared to it by conventional method.

Keywords: single crystal, solar cell, metal impurity, Ingot

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Authors: Sidra Saleemi, Arsalan Khan, Urooj Baig, Tahir Jamil

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In this research, it was examined that some residual amount of bleaching chemicals left in the liquor, this amount is more in Batch-wise process as compared to continuous process. These chemicals can be recovered and reused for bleaching by adding more quantity of fresh bleaching chemicals and water, this quantity will be required to balance the recipe for fabric. This liquor is recovered and samples were bleached with different modified recipe of liquor for both processes i.e. Batch-wise and continuous process. Every time good results were achieved with negligible variation in the quality parameter between the fabric bleached with fresh liquor and the fabric bleached with Recovered Liquor. Additionally, samples were dyed, and found that dyeing can be done easily on samples bleached with recover liquor.

Keywords: bleaching process, hydrogen peroxide, sodium hydroxide, liquor recovery

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Authors: Andres Diaz Garcia, Ana Maria Ceballos Rojas, Duvan Albeiro Millan Montano

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This paper describes the initial technological development stages in the area of liquid fermentation required to reach the quantities of biomass of the biofertilizer microorganism Rhizobium sp. strain B02, for the application of the unitary stages downstream at laboratory scale. In the first stage, the adjustment and standardization of the fermentation process in conventional batch mode were carried out. In the second stage, various fed-batch and continuous fermentation strategies were evaluated in 10L-bioreactor in order to optimize the yields in concentration (Colony Forming Units/ml•h) and biomass (g/l•h), to make feasible the application of unit operations downstream of process. The growth kinetics, the evolution of dissolved oxygen and the pH profile generated in each of the strategies were monitored and used to make sequential adjustments. Once the fermentation was finished, the final concentration and viability of the obtained biomass were determined and performance parameters were calculated with the purpose of select the optimal operating conditions that significantly improved the baseline results. Under the conditions adjusted and standardized in batch mode, concentrations of 6.67E9 CFU/ml were reached after 27 hours of fermentation and a subsequent noticeable decrease was observed associated with a basification of the culture medium. By applying fed-batch and continuous strategies, significant increases in yields were achieved, but with similar concentration levels, which involved the design of several production scenarios based on the availability of equipment usage time and volume of required batch.

Keywords: biofertilizer, liquid fermentation, Rhizobium sp., standardization of processes

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Authors: A. D. Susanti, W. B. Sediawan, S. K. Wirawan, Budhijanto, Ritmaleni

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Rice bran oil contains significant amounts of oryzanol, a natural antioxidant that considered has higher antioxidant activity than vitamin E (tocopherol). Oryzanol reviewed has several health properties and interested in pharmacy, nutrition, and cosmetics. For practical usage, isolation and purification would be necessary due to the low concentration of oryzanol in crude rice bran oil (0.9-2.9%). Batch chromatography has proved as a promising process for the oryzanol recovery, but productivity was still low and scale-up processes of industrial interest have not yet been described. In order to improve productivity of batch chromatography, a continuous chromatography design namely Simulated Moving Bed (SMB) concept have been proposed. The SMB concept has interested for continuous commercial scale separation of binary system (oryzanol and rice bran oil), and rice bran oil still obtained as side product. Design of SMB chromatography for oryzanol separation requires quantification of its equilibrium. In this study, equilibrium of oryzanol separation conducted in batch adsorption using silica as the adsorbent and n-hexane/acetone (9:1) as the eluent. Three isotherm models, namely the Henry, Langmuir, and Freundlich equations, have been applied and modified for the experimental data to establish appropriate correlation for each sample. It turned out that the model quantitatively describe the equilibrium experimental data and will directed for design of SMB chromatography.

Keywords: adsorption, equilibrium, oryzanol, rice bran oil, simulated moving bed

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Authors: Gómez Romero Jacob, García Peña Elvia Inés

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The co-digestion process of crude cheese whey (CCW) with fruit vegetable waste (FVW) for biohydrogen production was investigated in batch and continuous systems, in stirred 1.8 L bioreactors at 37°C. Five different C/N ratios (7, 17, 21, 31, and 46) were tested in batch systems. While, in continuous system eight conditions were evaluated, hydraulic retention time (from 60 to 10 h) and organic load rate (from 21.96 to 155.87 g COD/L d). Data in batch tests showed a maximum specific biohydrogen production rate of 10.68 mmol H2/Lh and a biohydrogen yield of 449.84 mL H2/g COD at a C/N ratio of 21. In continuous co-digestion system, the optimum hydraulic retention time and organic loading rate were 17.5 h and 80.02 g COD/L d, respectively. Under these conditions, the highest volumetric production hydrogen rate (VPHR) and hydrogen yield were 11.02 mmol H2/L h, 800 mL H2/COD, respectively. A pyrosequencing analysis showed that the main acclimated microbial communities for co-digestion studies consisted of Bifidobacterium, with 85.4% of predominance. Hydrogen producing bacteria such as Klebsiella (9.1%), Lactobacillus (0.97%), Citrobacter (0.21%), Enterobacter (0.27%), and Clostridium (0.18%) were less abundant at this culture period. The microbial population structure was correlated with the lactate, acetate, and butyrate profiles obtained. Results demonstrated that the co-digestion of CCW with FVW improves biohydrogen production due to a better nutrient balance and improvement of the system’s buffering capacity.

Keywords: acclimatation, biohydrogen, co-digestion, microbial community

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Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

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Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

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Authors: Sunarti Sinaga, Hsueh-Jung Lu, Jia-Rong Lin

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Blue mackerel (Scomber australasicus) is a crucial target species for Taiwan coastal fisheries and has maintained its status as the highest-produced species. Timely measurement of spawning status is crucial for determining the correct management strategy for this species. The objective of this study was to determine size at maturity, fecundity, batch fecundity, and spawning frequency on the basis of samples collected from Nan-Fang-Ao fishing port in Yilan during the spawning season from 2017 to 2019. Histological sections indicated that the blue mackerel are multiple spawners. A higher percentage of female fish spawned at the peak of the gonadosomatic index. The 50% sizes at maturity were 32.02, 32.13, and 29.64 cm. Mean total fecundity (batch fecundity) was 165 (103), 229 (96), and 210 (68) oocytes per ovary-free weight (g) for 2017, 2018, and 2019, respectively; fecundity was determined through observation of postovulatory follicles (POFs). The spawning frequencies (spawning fraction) in 2017, 2018, and 2019 were 3–10 days (0.13), 4–14 days (0.08), and 4–12 days (0.08), respectively. The spawning frequencies determined through the 3 estimated methods, namely the sums of (a) hydrated and Day 0 POFs; (b) Day 1+ POFs, and (c) all data combined, were 1 spawning event per 8, 10, and 9 days, respectively. The reproduction of the blue mackerel was greater in 2017 than it was in 2018 or 2019, as indicated by the higher batch fecundity and shorter spawning seasons. Environmental factors should also be considered as a major factor influencing successful reproduction and the spawning season.

Keywords: scomber australasicus, spawning frequency, batch fecundity, fecundity

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Authors: E. Al-Essa, R. Bello-Mendoza, D. G. Wareham

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Anaerobic batch experiments were conducted to investigate the effect of magnetite-supplementation (7 mM) on methane production from digested sludge undergoing two different microbial growth phases, namely fresh sludge (exponential growth phase) and degassed sludge (endogenous decay phase). Three different particle sizes were assessed: small (50 - 150 nm), medium (168 – 490 nm) and large (800 nm - 4.5 µm) particles. Results show that, in the case of the fresh sludge, magnetite significantly enhanced the methane production rate (up to 32%) and reduced the lag phase (by 15% - 41%) as compared to the control, regardless of the particle size used. However, the cumulative methane produced at the end of the incubation was comparable in all treatment and control bottles. In the case of the degassed sludge, only the medium-sized magnetite particles increased significantly the methane production rate (12% higher) as compared to the control. Small and large particles had little effect on the methane production rate but did result in an extended lag phase which led to significantly lower cumulative methane production at the end of the incubation period. These results suggest that magnetite produces a clear and positive effect on methane production only when an active and balanced microbial community is present in the anaerobic digester. It is concluded that, (i) the effect of magnetite particle size on increasing the methane production rate and reducing lag phase duration is strongly influenced by the initial metabolic state of the microbial consortium, and (ii) the particle size would positively affect the methane production if it is provided within the nanometer size range.

Keywords: anaerobic digestion, iron oxide, methanogenesis, nanoparticle

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Authors: César Huiliñir, Danilo Villanueva, Pedro Iván Alvarez, Francisco Cubillos

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Biodrying aims at removing water from biowastes and has been mostly studied for municipal solid wastes (MSW), while few studies have dealt with secondary sludge from the paper and pulp industry. The goal of this study was to investigate the effect of initial moisture content (MC) on the batch biodrying of pulp and paper secondary sludge, using rice husks as bulking agents. Three initial MCs were studied (54, 65, and 74% w.b.) in closed batch laboratory-scale reactors under adiabatic conditions and with a constant air-flow rate (0.65 l min-1 kg-1 wet solid). The initial MC of the mixture of secondary sludge and rice husks showed a significant effect on the biodrying process. Using initial moisture content between 54-65% w.b., the solid moisture content was reduce up to 37 % w.b. in ten days, getting calorific values between 8000-9000 kJ kg-1. It was concluded that a decreasing of initial MC improves the drying rate and decreases the solid volatile consumption, therefore, the optimization of biodrying should consider this parameter.

Keywords: biodrying, secondary sludge, initial moisture content, pulp and paper industry, rice husk

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Authors: Hsin-Yueh Chang, Pin-Chen Liao, Jo-Shu Chang, Chun-Yen Chen

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Biofuel has drawn much attention as a potential substitute to fossil fuels. However, biodiesel from waste oil, oil crops or other oil sources can only satisfy partial existing demands for transportation. Due to the feature of being clean, green and viable for mass production, using microalgae as a feedstock for biodiesel is regarded as a possible solution for a low-carbon and sustainable society. In particular, Thraustochytrium sp. BM2, an indigenous heterotrophic microalga, possesses the potential for metabolizing glycerol to produce lipids. Hence, it is being considered as a promising microalgae-based oil source for biodiesel production and other applications. This study was to optimize the culture pH, scale up, assess the feasibility of producing microalgal lipid from crude glycerol and apply operation strategies following optimal results from shake flask system in a 5L stirred-tank fermenter for further enhancing lipid productivities. Cultivation of Thraustochytrium sp. BM2 without pH control resulted in the highest lipid production of 3944 mg/L and biomass production of 4.85 g/L. Next, when initial glycerol and corn steep liquor (CSL) concentration increased five times (50 g and 62.5 g, respectively), the overall lipid productivity could reach 124 mg/L/h. However, when using crude glycerol as a sole carbon source, direct addition of crude glycerol could inhibit culture growth. Therefore, acid and metal salt pretreatment methods were utilized to purify the crude glycerol. Crude glycerol pretreated with acid and CaCl₂ had the greatest overall lipid productivity 131 mg/L/h when used as a carbon source and proved to be a better substitute for pure glycerol as carbon source in Thraustochytrium sp. BM2 cultivation medium. Engineering operation strategies such as fed-batch and semi-batch operation were applied in the cultivation of Thraustochytrium sp. BM2 for the improvement of lipid production. In cultivation of fed-batch operation strategy, harvested biomass 132.60 g and lipid 69.15 g were obtained. Also, lipid yield 0.20 g/g glycerol was same as in batch cultivation, although with poor overall lipid productivity 107 mg/L/h. In cultivation of semi-batch operation strategy, overall lipid productivity could reach 158 mg/L/h due to the shorter cultivation time. Harvested biomass and lipid achieved 232.62 g and 126.61 g respectively. Lipid yield was improved from 0.20 to 0.24 g/g glycerol. Besides, product costs of three kinds of operation strategies were also calculated. The lowest product cost 12.42 $NTD/g lipid was obtained while employing semi-batch operation strategy and reduced 33% in comparison with batch operation strategy.

Keywords: heterotrophic microalga Thrasutochytrium sp. BM2, microalgal lipid, crude glycerol, fermentation strategy, biodiesel

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Authors: Ali W. N. Alattabi, Clare B. Harris, Rafid M. Alkhaddar, Montserrat Ortoneda, David A. Phipps, Ali Alzeyadi, Khalid S. Hashim

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This study was performed to optimise the hydraulic retention time (HRT) and study its effects on the sludge characteristics and the effluent quality in an aerobic suspension sequencing batch reactor (ASSBR) treating synthetic wastewater. The results showed that increasing the HRT from 6 h to 12 h significantly improved the COD and Nitrate removal efficiency; it was increased from 78.7% - 75.7% to 94.7% – 97% for COD and Nitrate respectively. However, increasing the HRT from 12 h to 18 h reduced the COD and Nitrate removal efficiency from 94.7% - 97% to 91.1% – 94.4% respectively. Moreover, Increasing the HRT from 18 h to 24 h did not affect the COD and Nitrate removal efficiency. Sludge volume index (SVI) was used to monitor the sludge settling performance. The results showed a direct relationship between the HRT and SVI value. Increasing the HRT from 6 h to 12 h led to decrease the SVI value from 123 ml/g to 82.5 ml/g, and then it remained constant despite of increasing the HRT from 12 h to 18 h and to 24 h. The results obtained from this study showed that the HRT of 12 h was better for COD and Nitrate removal and a good settling performance occurred during that range.

Keywords: COD, hydraulic retention time, nitrate, sequencing batch reactor, sludge characteristics

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Authors: Amin Mojiri, Hamidi Abdul Aziz

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Leachate is created while water penetrates through the waste in a landfill, carrying some forms of pollutants. In literature, for treatment of wastewater and leachate, different ways of biological treatment were used. Sequencing batch reactor (SBR) is a kind of biological treatment. This study investigated the co-treatment of landfill leachate and domestic waste water by SBR and powdered activated carbon augmented (PAC) SBR process. The response surface methodology (RSM) and central composite design (CCD) were employed. The independent variables were aeration rate (L/min), contact time (h), and the ratio of leachate to wastewater mixture (%; v/v)). To perform an adequate analysis of the aerobic process, three dependent parameters, i.e. COD, color, and ammonia-nitrogen (NH3-N or NH4-N) were measured as responses. The findings of the study indicated that the PAC-SBR showed a higher performance in elimination of certain pollutants, in comparison with SBR. With the optimal conditions of aeration rate (0.6 L/min), leachate to waste water ratio (20%), and contact time (10.8 h) for the PAC-SBR, the removal efficiencies for color, NH3-N, and COD were 72.8%, 98.5%, and 65.2%, respectively.

Keywords: co-treatment, landfill Leachate, wastewater, sequencing batch reactor, activate carbon

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

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Authors: Young Min Kim, Deokyeong Choe, Chul Soo Shin

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Monascus pigments, commonly used as a natural colorant in Asia, have many biological activities, such as cholesterol level control, anti-obesity, anti-cancer, and anti-oxidant, that have recently been elucidated. Especially, amino acid derivatives of Monascus pigments are receiving much attention because they have higher biological activities than original Monascus pigments. Previously, there have been two ways to produce amino acid derivatives: one-step production and two-step production. However, the one-step production has low purity, and the two-step production—precursor(orange pigments) fermentation and derivatives synthesis—has low productivity and growth rate during its precursor fermentation step. In this study, it was verified that pH is a key factor that affects the stability of orange pigments and the growth rate of Monascus. With an optimal pH profile obtained by pH-stat fermentation, we designed a process of precursor(orange pigments) fermentation that is a pH-controlled fed-batch fermentation. The final concentration of orange pigments in this process increased to 5.5g/L which is about 30% higher than the concentration produced from the previously used precursor fermentation step.

Keywords: cultivation process, fed-batch fermentation, monascus pigments, pH stability

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Lakshmidevi Rajendran, Bharathidasan Kanniappan, Gopi Raja, Muthukumar Karuppan

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This study investigates the feasibility of fed-batch mixotrophic cultivation of microalgae Scenedesmus sp. in a 3-litre airlift photobioreactor under standard operating conditions. The results of this study suggest the algae species may serve as an excellent feed for aquatic species using organic byproducts. Microalgae Scenedesmus sp., was cultured using a synthetic wastewater by stepwise addition of crude glycerol concentration ranging from 2-10g/l under fed-batch mixotrophic mode for a period of 15 days. The attempts were made with the stepwise addition of crude glycerol as a carbon source in the initial growth phase to evade the inhibitory nature of high glycerol concentration on the growth of Scenedesmus sp. Crude glycerol was chosen since it is readily accessible as byproduct from biodiesel production sectors. Highest biomass concentration was achieved to be 2.43 g/l at the crude glycerol concentration of 6g/l after 10 days which is 3 fold times the increase in the biomass concentration compared with the control medium without the addition of glycerol. Biomass growth data obtained for the microalgae Scenedesmus sp. was fitted well with the modified Logistic equation. Substrate utilization kinetics was also employed to model the biomass productivity with respect to the various crude glycerol concentration. The results indicated that the supplement of crude glycerol to the mixotrophic culture of Scenedesmus sp., enhances the biomass concentration, chlorophyll and lutein productivity. Thus the application of fed-batch mixotrophic cultivation with stepwise addition of crude glycerol to Scenedesmus sp., provides a subtle way to reduce the production cost and improvisation in the large-scale cultivation along with biochemical compound synthesis.

Keywords: airlift photobioreactor, crude glycerol, microalgae Scenedesmus sp., mixotrophic cultivation, lutein production

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Authors: Mohamed Ahmed AbdelKawy, A. H. El-Shazly

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In this study, Nano iron-copper core-shell was synthesized by using Kinetic energy micro reactor ( K-M reactor). The reaction between nano-pure iron with copper sulphate pentahydrate (CuSO4.5H2O) beside NaCMC as a stabilizer at K-M reactor gives many advantages in comparison with the traditional chemical method for production of nano iron-Copper core-shell in batch reactor. Many factors were investigated for its effect on the process performance such as initial concentrations of nano iron and copper sulphate pentahydrate solution. Different techniques were used for investigation and characterization of the produced nano iron particles such as SEM, XRD, UV-Vis, XPS, TEM and PSD. The produced Nano iron-copper core-shell particle using micro mixer showed better characteristics than those produced using batch reactor in different aspects such as homogeneity of the produced particles, particle size distribution and size, as core diameter 10nm particle size were obtained. The results showed that 10 nm core diameter were obtained using Micro mixer as compared to 80 nm core diameter in one-fourth the time required by using traditional batch reactor and high thickness of copper shell and good stability.

Keywords: nano iron, core-shell, reduction reaction, K-M reactor

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Vaishnavi Unde, Srikanth Mutnuri

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Today dye stuff sector is one of the major chemical industries in India. Indigo is a blue coloured dye used all over the world in large quantity. The indigo dye produced and used in textile industries is synthetic having toxic effect, thus there is an increase in interest for natural dyes owing to the environmental concerns. The present study focuses on the use of a strain Pandoraea sp. isolated from garage soil, for the production of indigo in fed batch bioreactor. A comparative study between single phase and two phase production was carried out in this work. The blue colour produced during the experiments was analyzed using, TLC, UV-visible spectrophotometer and FTIR technique. The blue pigment was found to be indigo. The production of bio-indigo was done in a single phase fermentor carrying medium and substrate indole in dissolved form and was found to produce maximum of 0.041 g/L of indigo. Whereas there was an increase in production of indigo to 0.068 g/L in a two phase, water-silicone oil system. In this study the advantage of using second phase as silicone oil has enhanced the indigo production, as the second phase made the substrate available to the bacteria by increasing the surface area as well as it helped to prevent the inhibition effect of the high concentration of substrate, indole. The effect of single and two phases on the growth of bacteria was also studied.

Keywords: dyes, fed batch reactor, indole, Indigo

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Authors: Wen-Tsung Ho, Ku-Kuang Chang, Hsin-Yuan Chang

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In this study, we consider an economic lot-size batch-shipment scheduling problem (ELBSP) with extended basic period (EBP) and power-of-two (PoT) policies. In this problem, the supplier using a single facility to manufacture multiple products and equally sized batches are then delivered by the supplier to buyers over an infinite planning horizon. Further, the extended basic period (EBP) and power-of-two (PoT) policy are utilized. Relaxing the production schedule converts the ELBSP to an economic lot-size batch-shipment problem (ELBP) with EBP and PoT policies, and a nonlinear integer programming model of the ELBP is constructed. Using the replenishment cycle division and recursive tightening methods, optimal solutions are then solved separately for each product. The sum of these optimal solutions is the lower bound of the ELBSP. A proposed heuristic method with polynomial complexity is then applied to figure out the near-optimal solutions of the ELBSP. Numerical example is presented to confirm the efficacy of the proposed method.

Keywords: economic lot-size scheduling problem, extended basic period, replenishment cycle division, recursive tightening, power-of-two

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Authors: G. Quiroga-Cubides, A. Díaz, M. Gómez

Abstract:

The genus Azotobacter has been widely used as bio-fertilizer due to its significant effects on the stimulation and promotion of plant growth in various agricultural species of commercial interest. In order to obtain significantly viable cellular concentration, a scale-up strategy for a liquid fermentation process (SmF) with two strains of A. chroococcum (named Ac1 and Ac10) was validated and adjusted at laboratory and pilot scale. A batch fermentation process under previously defined conditions was carried out on a biorreactor Infors®, model Minifors of 3.5 L, which served as a baseline for this research. For the purpose of increasing process efficiency, the effect of the reduction of stirring speed was evaluated in combination with a fed-batch-type fermentation laboratory scale. To reproduce the efficiency parameters obtained, a scale-up strategy with geometric and fluid dynamic behavior similarities was evaluated. According to the analysis of variance, this scale-up strategy did not have significant effect on cellular concentration and in laboratory and pilot fermentations (Tukey, p > 0.05). Regarding air consumption, fermentation process at pilot scale showed a reduction of 23% versus the baseline. The percentage of reduction related to energy consumption reduction under laboratory and pilot scale conditions was 96.9% compared with baseline.

Keywords: Azotobacter chroococcum, scale-up, liquid fermentation, fed-batch process

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Authors: Snehal D. Ganjave, Hardik Dodia, Avinash V. Sunder, Swati Madhu, Pramod P. Wangikar

Abstract:

Batch cultivation of recombinant bacteria in shake flasks results in low cell density due to nutrient depletion. Previous protocols on high cell density cultivation in shake flasks have relied mainly on controlled release mechanisms and extended cultivation protocols. In the present work, we report an optimized fed-batch process for high cell density cultivation of recombinant E. coli BL21(DE3) for protein production. A cybernetic model-based, multi-objective optimization strategy was implemented to obtain the optimum operating variables to achieve maximum biomass and minimized substrate feed rate. A syringe pump was used to feed a mixture of glycerol and yeast extract into the shake flask. Preliminary experiments were conducted with online monitoring of dissolved oxygen (DO) and offline measurements of biomass and glycerol to estimate the model parameters. Multi-objective optimization was performed to obtain the pareto front surface. The selected optimized recipe was tested for a range of proteins that show different extent soluble expression in E. coli. These included eYFP and LkADH, which are largely expressed in soluble fractions, CbFDH and GcanADH , which are partially soluble, and human PDGF, which forms inclusion bodies. The biomass concentrations achieved in 24 h were in the range 19.9-21.5 g/L, while the model predicted value was 19.44 g/L. The process was successfully reproduced in a standard laboratory shake flask without online monitoring of DO and pH. The optimized fed-batch process showed significant improvement in both the biomass and protein production of the tested recombinant proteins compared to batch cultivation. The proposed process will have significant implications in the routine cultivation of E. coli for various applications.

Keywords: cybernetic model, E. coli, high cell density cultivation, multi-objective optimization

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Authors: Aiman Elragig, Hanan Dreiwi, Dung Ly, Idriss Elmabrook

Abstract:

This paper highlights a new approach to look at online principle components analysis (OPCA). Given a data matrix X ∈ R,^m x n we characterise the online updates of its covariance as a matrix perturbation problem. Up to the principle components, it turns out that online updates of the batch PCA can be captured by symmetric matrix perturbation of the batch covariance matrix. We have shown that as n→ n0 >> 1, the batch covariance and its update become almost similar. Finally, utilize our new setup of online updates to find a bound on the angle distance of the principle components of X and its update.

Keywords: online data updates, covariance matrix, online principle component analysis, matrix perturbation

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Authors: Erwin Chan, Aravind Subramaniyan, Siti Abdullah Fatehah, Steve Lian Kuling

Abstract:

Foam assisted lift technology is proven across the industry to provide efficient deliquification in gas wells. Such deliquification is typically achieved by delivering the foamer chemical downhole via capillary strings. In highly liquid loaded wells where capillary strings are not readily available, foamer can be delivered via batch injection or bull-heading. The latter techniques differ from the former in that cap strings allow for liquid to be unloaded continuously, whereas foamer batches require that periodic batching be conducted for the liquid to be unloaded. Although batch injection allows for liquid to be unloaded in wells with suitable water to gas (WGR) ratio and condensate to gas (CGR) ratio without well intervention for capillary string installation, this technique comes with its own set of challenges - for foamer to de-liquify liquids, the chemical needs to reach perforation locations where gas bubbling is observed. In highly scaled perforation zones in certain wells, foamer delivered in batches is unable to reach the gas bubbling zone, thus achieving poor lift efficiency. This paper aims to discuss the techniques and challenges for unloading liquid via batch injection in scaled perforation wells X and Y, whose WGR is 6bbl/MMscf, whose scale build-up is observed at the bottom of perforation interval, whose water column is 400 feet, and whose ‘bubbling zone’ is less than 100 feet. Variables such as foamer Z dosage, batching technique, and well flow control valve opening times are manipulated during the duration of the trial to achieve maximum liquid unloading and gas rates. During the field trial, the team has found optimal values between the three aforementioned parameters for best unloading results, in which each cycle’s gas and liquid rates are compared with baselines with similar flowing tubing head pressures (FTHP). It is discovered that amongst other factors, a good agitation technique is a primary determinant for efficient liquid unloading. An average increment of 2MMscf/d against an average production of 4MMscf/d at stable FTHP is recorded during the trial.

Keywords: foam, foamer, gas lift, liquid unloading, scale, batch injection

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

Abstract:

The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Mustafa M. Bob, Siti Izaidah Azmi, Mohd Hakim Ab Halim, Nur Syahida Abdul Jamal, Aznah Nor-Anuar, Zaini Ujang

Abstract:

In this research, the formation and development of aerobic granular sludge (AGS) for domestic wastewater treatment application in hot climate conditions was studied using a sequencing batch reactor (SBR). The performance of the developed AGS in the removal of organic matter and nutrients from wastewater was also investigated. The operation of the reactor was based on the sequencing batch system with a complete cycle time of 3 hours that included feeding, aeration, settling, discharging and idling. The reactor was seeded with sludge collected from the municipal wastewater treatment plant in Madinah city, Saudi Arabia and operated at a temperature of 40ºC using synthetic wastewater as influent. Results showed that granular sludge was developed after an operation period of 30 days. The developed granular sludge had a good settling ability with the average size of the granules ranging from 1.03 to 2.42 mm. The removal efficiency of chemical oxygen demand (COD), ammonia nitrogen (NH3-N) and total phosphorus (TP) were 87.31%, 91.93% and 61.25% respectively. These results show that AGS can be developed at elevated temperatures and it is a promising technique to treat domestic wastewater in hot and low humidity climate conditions such as those encountered in Saudi Arabia.

Keywords: aerobic granular sludge, hot climate, sequencing batch reactor, domestic wastewater treatment

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Authors: Amin Mojiri, Akiyoshi Ohashi, Tomonori Kindaichi

Abstract:

Synthetic domestic wastewater was treated via combining treatment methods, including electrochemical oxidation, adsorption, and sequencing batch reactor (SBR). In the upper part of the reactor, an anode and a cathode (Ti/RuO₂-IrO₂) were organized in parallel for the electrochemical oxidation procedure. Sodium sulfate (Na₂SO₄) with a concentration of 2.5 g/L was applied as the electrolyte. The voltage and current were fixed on 7.50 V and 0.40 A, respectively. Then, 15% working value of the reactor was filled by activated sludge, and 85% working value of the reactor was added with synthetic wastewater. Powdered cockleshell, 1.5 g/L, was added in the reactor to do ion-exchange. Response surface methodology was employed for statistical analysis. Reaction time (h) and pH were considered as independent factors. A total of 97.0% biochemical oxygen demand, 99.9% phosphorous and 88.6% cadmium were eliminated at the optimum reaction time (80.0 min) and pH (6.4).

Keywords: adsorption, electrochemical oxidation, metals, SBR

Procedia PDF Downloads 173