Search results for: batch bioreactor design

Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

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In this research, diesel oil properties, such as aniline point, density, diesel index, cetane index and cetane number before and after treatment were studied. The investigation was considered for diesel oil samples after batch adsorption process using powdered activated carbon. Batch distillation process was applied to all treated diesel oil samples for separation of the solid-liquid mixture. The diesel oil properties were studied to observe the impact of adsorptive desulfurization process on fuel quality. Results showed that the best cetane number for desulfurized diesel oil was found at the best-operating conditions 60℃, 10g activated carbon and 180 minute contact time. The best-desulfurized diesel oil cetane number was obtained around 51 while the cetane number of untreated diesel oil was 34. Results also showed that the calculated cetane number increases as the operating temperature and amounts of adsorbent increases. This behavior was same for other diesel oil properties such as aniline point, diesel index, cetane index and density. The best value for all the fuel properties was found at same operating conditions mentioned above. Thus, it can be concluded that adsorptive desulfurization using powdered activated carbon as adsorbent had significantly improved the fuel quality of diesel oil by reducing aromatic contents of diesel oil.

Keywords: activated carbon, adsorption, desulfurization, diesel oil, fuel quality

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Authors: Juliet Okoli

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The removal of BTEX (Benzene, toluene, Ethylbenzene and p-Xylene) from water by orange peel and eggshell compared to GAC were investigated. The influence of various factors such as contact time, dosage and pH on BTEX removal by virgin orange peel and egg shell were accessed using the batch adsorption set-up. These were also compared to that of GAC which serves as a benchmark for this study. Further modification (preparation of Activated carbon) of these virgin low-cost adsorbents was also carried out. The batch adsorption result showed that the optimum contact time, dosage and pH for BTEX removal by virgin LCAs were 180 minutes, 0.5g and 7 and that of GAC was 30mintues, 0.2g and 7. The maximum adsorption capacity for total BTEX showed by orange peel and egg shell were 42mg/g and 59mg/g respectively while that of GAC was 864mg/g. The adsorbent preference for adsorbate were in order of X>E>T>B. A comparison of batch and column set-up showed that the batch set-up was more efficient than the column set-up. The isotherm data for the virgin LCA and GAC prove to fit the Freundlich isotherm better than the Langmuir model, which produced n values >1 in case of GAC and n< 1 in case of virgin LCAs; indicating a more appropriate adsorption of BTEX onto the GAC. The adsorption kinetics for the three studied adsorbents were described well by the pseudo-second order, suggesting chemisorption as the rate limiting step. This was further confirmed by desorption study, as low levels of BTEX (<10%) were recovered from the spent adsorbents especially for GAC (<3%). Further activation of the LCAs which was compared to the virgin LCAs, revealed that the virgin LCAs had minor higher adsorption capacity than the activated LCAs. Economic analysis revealed that the total cost required to clean-up 9,600m3 of BTEX contaminated water using LCA was just 2.8% lesser than GAC, a difference which could be considered negligible. However, this area still requires a more detailed cost-benefit analysis, and if similar conclusions are reached; a low-cost adsorbent, easy to obtain are still promising adsorbents for BTEX removal from aqueous solution; however, the GAC are still more superior to these materials.

Keywords: activated carbon, BTEX removal, low cost adsorbents, water treatment

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Authors: J. Ritonja

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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification

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Authors: Kgomotso Matobole, Natania De Wet, Tefo Mbambo, Hilary Rutto, Tumisang Seodigeng

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Nitrogen and phosphorus are nutrients which are required in the ecosystem, however, at high levels, these nutrients contribute to the process of eutrophication in the receiving water bodies, which threatens aquatic organisms. Hence it is vital that they are removed before the water is discharged. This phenomenon increases the cost related to wastewater treatment. This raises the need for the development of processes that are cheaper. Activated biocarbon was used in batch and filtration system to remove nitrates and phosphates. The batch system has higher nutrients removal capabilities than the filtration system. For phosphate removal, 93 % removal is achieved at the adsorbent of 300 g while for nitrates, 84 % removal is achieved when 200 g of activated carbon is loaded.

Keywords: waste water treatment, phosphates, nitrates, activated carbon, agricultural waste

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Authors: Yassets Egaña, Patricio Núñez, Juan C. Rios, Ivan Balic, Alex Manquez, Yarela Flores, Maria C. Gatica, Sergio Diez De Medina, Rocio Tijaro-Rojas

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Globally, humans produce millions of tons of waste per year. An important percentage of this waste is plastic, which frequently ends up in landfills and oceans. During the last decades, the greatest plastics production in history have been made, a few amount of this plastic is recycled, the rest ending up as plastic pollution in soils and seas. Plastic pollution is disastrous for the environment, affecting essential species, quality of consumption water, and some economic activities such as tourism, in different parts of the world. Due to its durability and decomposition on micro-plastics, animals and humans are accumulating a variety of plastic components without having clear their effects on human health, economy, and wildlife. In dry regions as the Atacama Desert, up to 95% of the water consumption comes from underground reservoirs, therefore preventing the soil pollution is an urgent need. This contribution focused on isolating, genotyping and optimizing microorganisms that use plastic waste as the only source of food to construct a batch-type bioreactor able to degrade in a faster way the plastic waste before it gets the desert soils and groundwater consumed by people living in this areas. Preliminary results, under laboratory conditions, has shown an improved degradation of polyethylene when three species of bacteria and three of fungi act on a selected plastic material. These microorganisms have been inoculated in dry soils, initially lacking organic matter, under environmental conditions in the laboratory. Our team designed and constructed a prototype using the natural conditions of the region and the best experimental results.

Keywords: biological breakdown, plastic bags, prototype, desert regions

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Magdi. M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

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Authors: Wicleffe Musingarimi

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Currently, the rising energy demand as a result of an increase in the world’s population and the sustainable use of abundant natural resources are key issues facing many developed and developing countries including South Africa. Most of the energy to meet this growing demand comes from fossil fuel. Use of fossil fuels has led to environmental problems such air pollution, climate change, and acid rain. In addition, fossil fuels are facing continual depletion, which has led to the rise in oil prices, leading to the global economies melt down. Hence development of alternative clean and renewable energy source is a global priority. Renewable biomass from forest products, agricultural crops, and residues, as well as animal and municipal waste are promising alternatives. South Africa is one of the leading wine producers in the world; leading to a lot of winery waste (ww) being produced which can be used in anaerobic digestion (AD) to produce biogas. Biogas was produced from batch anaerobic digestion of zebra manure (zm) and batch anaerobic co-digestion of winery waste (ww) and zebra manure through water displacement. The batch digester with slurry of winery waste and zebra manure in the weight ratio of 1:2 was operated in a 1L container at 37°C for 30days. Co-digestion of winery waste and zebra manure produced higher amount of biogas as compared to zebra manure alone and winery waste alone. No biogas was produced by batch anaerobic digestion of winery waste alone. Chemical analysis of C/N ratio and total solids (TS) of zebra manure was 21.89 and 25.2 respectively. These values of C/N ratio and TS were quite high compared to values of other studied manures. Zebra manure also revealed unusually high concentration of Fe reaching 3600pm compared to other studies of manure. PCR with communal DNA of the digestate gave a positive hit for the presence of archaea species using standard archea primers; suggesting the presence of methanogens. Methanogens are key microbes in the production of biogas. Therefore, this study demonstrated the potential of zebra manure as an inoculum in the production of biogas.

Keywords: anaerobic digestion, biogas, co-digestion, methanogens

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Authors: Lars Rödel, Jonas Krebs, Gregor Müller

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The growing price pressure due to the increasing number of global suppliers, the growing individualization of products and ever-shorter delivery times are upcoming challenges in the industry. In this context, Mass Personalization stands for the individualized production of customer products in batch size 1 at the price of standardized products. The possibilities of digitalization and automation of technical order processing open up the opportunity for companies to significantly reduce their cost of complexity and lead times and thus enhance their competitiveness. Many companies already use a range of CAx tools and configuration solutions today. Often, the expert knowledge of employees is hidden in "knowledge silos" and is rarely networked across processes. DesignChain describes the automated digital process from the recording of individual customer requirements, through design and technical preparation, to production. Configurators offer the possibility of mapping variant-rich products within the Design Chain. This transformation of customer requirements into product features makes it possible to generate even complex CAD models, such as those for large-scale plants, on a rule-based basis. With the aid of an automated CAx chain, production-relevant documents are thus transferred digitally to production. This process, which can be fully automated, allows variants to always be generated on the basis of current version statuses.

Keywords: automation, design, CAD, CAx

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Authors: Michael Graz, Natasha Hurril, Andrew Shearer

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Research on feed supplementation with natural compounds is currently being intensively pursued with a view to improving energy utilisation in ruminants and mitigating the production of methane by these animals. Towards this end, a novel combination of extracts from garlic and bitter orange was therefore selected for trials on the basis of their previously published in vitro anti-methanogenic potential. Three separate in vitro experiments were conducted to determine energy utilisation and greenhouse gas production. These included use of rumen fluid from fistulated cows and sheep in batch culture, the Hohenheim gas test, and the Rusitec technique. Experimental and control arms were utilised, with 5g extracts per kilogram of total dietary dry matter (0.05g/kg active compounds) being used to supplement or not supplement the in vitro systems. Respiratory measurements were conducted on experimental day 1 for the batch culture and Hohenheim gas test and on day 14-21 for the Rusitec Technique (in a 21-day trial). Measurements included methane (CH4) production, total volatile fatty acid (VFA) concentration, molar proportions of acetate, propionate and butyrate and degradation of organic matter (Rusitec). CH4 production was reduced by 82% (±16%), 68% (±11%) and 37% (±4%) in the batch culture, Hohenheim gas test and Rusitec, respectively. Total VFA production was reduced by 13% (±2%) and 2% (±0.1%) in the batch culture and Hohenheim gas test whilst it was increased by 8% (±2%) in the Rusitec. Total VFA production was reduced in all tests between 2 and 10%, whilst acetate production was reduced between 10% and 29%. Propionate production which is an indicator of weight gain was increased in all cases between 16% and 30%. Butyrate production which is considered an indicator of potential milk yield was increased by between 6 and 11%. Degradation of organic matter in the Rusitec experiments was improved by 10% (±0.1%). In conclusion, the study demonstrated the potential of the combination of garlic and citrus extracts to improve digestion, enhance body energy retention and limit CH4 formation in relation to feed intake.

Keywords: citrus, garlic, methane, ruminants

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Authors: Sirirat Jangkorn, Pornsawai Praipipat

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Sugarcane bagasse ash of sugar factories is solid wastes that the richest source of silica. The alkali fusion method, quartz particles in material can be dissolved and they can be used as the silicon source for synthesizing silica-based materials such as zeolites. Zeolites have many advantages such as catalyst to improve the chemical reactions and they can also remove heavy metals in the water including lead. Therefore, this study attempts to synthesize zeolites from the sugarcane bagasse ash, investigate their structure characterizations and chemical components to confirm the happening of zeolites, and examine their lead removal efficiency through the batch test studies. In this study, the sugarcane bagasse ash was chosen as the silicon source to synthesize zeolites, X-ray diffraction (XRD) and X-ray fluorescence spectrometry (XRF) were used to verify the zeolite pattern structures and element compositions, respectively. The batch test studies in dose (0.05, 0.1, 0.15 g.), contact time (1, 2, 3), and pH (3, 5, 7) were used to investigate the lead removal efficiency by the synthesized zeolite. XRD analysis result showed the crystalline phase of zeolite pattern, and XRF result showed the main element compositions of the synthesized zeolite that were SiO₂ (50%) and Al₂O₃ (30%). The batch test results showed the best optimum conditions of the synthesized zeolite for lead removal were 0.1 g, 2 hrs., and 5 of dose, contact time, and pH, respectively. As a result, this study can conclude that the zeolites can synthesize from the sugarcane bagasse ash and they can remove lead in the water.

Keywords: sugarcane bagasse ash, solid wastes, zeolite, lead

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Authors: Kailash C. Madan

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We study the steady state behaviour of a batch arrival single server queue in which the first service with general service times is compulsory and the second service with general service times is optional. We term such a two phase service as generalized Coxian-2 service. Just after completion of a service the server must take a vacation of random length of time with general vacation times. We obtain steady state probability generating functions for the queue size as well as the steady state mean queue size at a random epoch of time in explicit and closed forms. Some particular cases of interest including some known results have been derived.

Keywords: batch arrivals, compound Poisson process, generalized Coxian-2 service, steady state

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Mohamed H. Sorour, Hayam F. Shaalan, Heba A. Hani, Eman S. Sayed

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Ion exchange adsorption has a long standing history of success for seawater softening and selective ion removal from saline sources. Strong, weak and mixed types ion exchange systems could be designed and optimized for target separation. In this paper, different types of adsorbents comprising zeolite 13X and kaolin, in addition to, poly acrylate/zeolite (AZ), poly acrylate/kaolin (AK) and stand-alone poly acrylate (A) hydrogel types were prepared via microwave (M) and ultrasonic (U) irradiation techniques. They were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The developed adsorbents were evaluated on bench scale level and based on assessment results, a composite bed has been formulated for performance evaluation in pilot scale column investigations. Owing to the hydrogel nature of the partially crosslinked poly acrylate, the developed adsorbents manifested a swelling capacity of about 50 g/g. The pilot trials have been carried out using magnesium enriched Red Seawater to simulate Red Seawater desalination brine. Batch studies indicated varying uptake efficiencies, where Mg adsorption decreases according to the following prepared hydrogel types AU>AM>AKM>AKU>AZM>AZU, being 108, 107, 78, 69, 66 and 63 mg/g, respectively. Composite bed adsorbent tested in the up-flow mode column studies indicated good performance for Mg uptake. For an operating cycle of 12 h, the maximum uptake during the loading cycle approached 92.5-100 mg/g, which is comparable to the performance of some commercial resins. Different regenerants have been explored to maximize regeneration and minimize the quantity of regenerants including 15% NaCl, 0.1 M HCl and sodium carbonate. Best results were obtained by acidified sodium chloride solution. In conclusion, developed cation exchange adsorbents comprising clay or zeolite support indicated adequate performance for Mg recovery under saline environment. Column design operated at the up-flow mode (approaching expanded bed) is appropriate for such type of separation. Preliminary cost indicators for Mg recovery via ion exchange have been developed and analyzed.

Keywords: batch and dynamic magnesium separation, seawater, polyacrylate hydrogel, cost evaluation

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Authors: Ashish Pathak, Dong-Jin Kim, Haragobinda Srichandan, Byoung-Gon Kim

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Microbial depyritization of coal using chemoautotrophic bacteria is gaining acceptance as an efficient and eco-friendly technique. The process uses the metabolic activity of chemoautotrophic bacteria in removing sulfur and pyrite from the coal. The aim of the present study was to investigate the potential of Acidithiobacillus ferrooxidans in removing the pyritic sulfur and iron from high iron and sulfur containing US coal. The experiment was undertaken in 8 L bench scale stirred tank reactor having 1% (w/v) pulp density of coal. The reactor was operated at 35ºC and aerobic conditions were maintained by sparging the air into the reactor. It was found that at the end of bio-depyritization process, about 90% of pyrite and 67% of pyritic sulfur was removed from the coal. The results indicate that the bio-depyritization process is an efficient process in treating the high pyrite and sulfur containing coal.

Keywords: At.ferrooxidans, batch reactor, coal desulfurization, pyrite

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Authors: Jan Busch, Maurice Schmidt, Peter Nyhuis

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The change of conditions for production companies in high-wage countries is characterized by the globalization of competition and the transition of a supplier´s to a buyer´s market. The companies need to face the challenges of reacting flexibly to these changes. Due to the significant and increasing degree of automation, assembly has become the most expensive production process. Regarding the reduction of production cost, assembly consequently offers a considerable rationalizing potential. Therefore, an aerodynamic feeding system has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. In former research activities, this system has been enabled to adjust itself using genetic algorithm. The longer the genetic algorithm is executed the better is the feeding quality. In this paper, the relation between the system´s setting time and the feeding quality is observed and a function which enables the user to achieve the minimum of the total feeding time is presented.

Keywords: aerodynamic feeding system, batch size, optimisation, setting time

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Authors: Widi Astuti, Rizki Agus Hermawan, Hariono Mukti, Nurul Retno Sugiyono

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The removal of lead ion (Pb²⁺) from aqueous solution by activated carbon with phosphoric acid activation employing mangrove propagule as precursor was investigated in a batch adsorption system. Batch studies were carried out to address various experimental parameters including pH and contact time. The Langmuir and Freundlich models were able to describe the adsorption equilibrium, while the pseudo first order and pseudo second order models were used to describe kinetic process of Pb²⁺ adsorption. The results show that the adsorption data are seen in accordance with Langmuir isotherm model and pseudo-second order kinetic model.

Keywords: activated carbon, adsorption, equilibrium, kinetic, lead, mangrove propagule

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Authors: Koray U. Erbas

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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: María D. Groppa, Andrea Trentini, Myriam Zawoznik, Roxana Bigi, Carlos Nadra, Patricia L. Marconi

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In the present work, a remediation bioprocess based on the use of a local isolate of the microalgae Chlorella vulgaris immobilized in alginate beads is proposed. This process was shown to be effective for the reduction of several chemical and microbial contaminants present in Cildáñez stream, a water course that is part of the Matanza-Riachuelo Basin (Buenos Aires, Argentina). The bioprocess, involving the culture of the microalga in autotrophic conditions in a stirred-tank bioreactor supplied with a marine propeller for 6 days, allowed a significant reduction of Escherichia coli and total coliform numbers (over 95%), as well as of ammoniacal nitrogen (96%), nitrates (86%), nitrites (98%), and total phosphorus (53%) contents. Pb content was also significantly diminished after the bioprocess (95%). Standardized cytotoxicity tests using Allium cepa seeds and Cildáñez water pre- and post-remediation were also performed. Germination rate and mitotic index of onion seeds imbibed in Cildáñez water subjected to the bioprocess was similar to that observed in seeds imbibed in distilled water and significantly superior to that registered when untreated Cildáñez water was used for imbibition. Our results demonstrate the potential of this simple and cost-effective technology to remove urban-water contaminants, offering as an additional advantage the possibility of an easy biomass recovery, which may become a source of alternative energy.

Keywords: bioreactor, bioremediation, Chlorella vulgaris, Matanza-Riachuelo Basin, microalgae

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Authors: S. Wesebaum, S. Willeke

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Production companies are faced with an increasingly turbulent business environment, which demands very high production volumes- and delivery date flexibility. If a decoupling by storage stages is not possible (e.g. at a contract manufacturing company) or undesirable from a logistical point of view, load scattering effects the production processes. ‘Load’ characterizes timing and quantity incidence of production orders (e.g. in work content hours) to workstations in the production, which results in specific capacity requirements. Insufficient coordination between load (demand capacity) and capacity supply results in heavy load scattering, which can be described by deviations and uncertainties in the input behavior of a capacity unit. In order to respond to fluctuating loads, companies try to implement consistent and realizable input behavior using the capacity supply available. For example, a uniform and high level of equipment capacity utilization keeps production costs down. In contrast, strong load scattering at workstations leads to performance loss or disproportionately fluctuating WIP, whereby the logistics objectives are affected negatively. Options for reducing load scattering are e.g. shifting the start and end dates of orders, batch splitting and outsourcing of operations or shifting to other workstations. This leads to an adjustment of load to capacity supply, and thus to a reduction of load scattering. If the adaptation of load to capacity cannot be satisfied completely, possibly flexible capacity must be used to ensure that the performance of a workstation does not decrease for a given load. Where the use of flexible capacities normally raises costs, an adjustment of load to capacity supply reduces load scattering and, in consequence, costs. In the literature you mostly find qualitative statements for describing load scattering. Quantitative evaluation methods that describe load mathematically are rare. In this article the authors discuss existing approaches for calculating load scattering and their various disadvantages such as lack of opportunity for normalization. These approaches are the basis for the development of our mathematical quantification approach for describing load scattering that compensates the disadvantages of the current quantification approaches. After presenting our mathematical quantification approach, the method of batch splitting will be described. Batch splitting allows the adaptation of load to capacity to reduce load scattering. After describing the method, it will be explicitly analyzed in the context of the logistic curve theory by Nyhuis using the stretch factor α1 in order to evaluate the impact of the method of batch splitting on load scattering and on logistic curves. The conclusion of this article will be to show how the methods and approaches presented can help companies in a turbulent environment to quantify the occurring work load scattering accurately and apply an efficient method for adjusting work load to capacity supply. In this way, the achievements of the logistical objectives are increased without causing additional costs.

Keywords: batch splitting, production logistics, production planning and control, quantification, load scattering

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Authors: Indrajeet Singh, Abhishek Gandhi, Smita Mohanty, S. K. Nayak

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In this article, a focused study has been performed to comprehend the influence of change in depressurization rate on microcellular polycarbonate foamed morphological attributes. The depressurization rate considered in this study were 0.5, 0.05, 0.01 and 0.005 MPa/sec and the physical blowing agent utilized was carbon dioxide owing to its high solubility in polycarbonate at room temperature. The study was performed on two distinct saturation pressures, i.e., 3 MPa and 6 MPa to understand if saturation pressure has any effects on it. It is reported that with increase in depressurization rate, a higher amount of thermodynamic instability was induced which resulted in generation of larger number of smaller sized cells. This article puts forward an understanding of how depressurization rate control could be well exploited during the batch foaming process to develop high quality microcellular foamed products with exceedingly well controlled cell size.

Keywords: depressurization, porous polymer, foaming, microcellular

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Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

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The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

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Authors: Bukunola A.Oguntade, Abdul- Azeez A. Oderinde

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Fishbone is a type of waste generated from food and food processing industries. Fishbone wastes are usually treated as the source of organic matter for the by-production. It is a rich source of hydroxyapatite (HAP). In this study, the adsorption behavior of fishbone was examined in a batch system as an economically viable adsorbent for the removal of Ni⁺² ions from aqueous solution. The powdered fishbone was characterized using Fourier Transform Infrared (FT-IR) spectrophotometer and Scanning Electron microscope (SEM). The study investigated the influence of adsorbent dosage, solution pH, contact time, and initial metal concentration on the removal of Nickel (II) ions at room temperature. The batch kinetics study showed that the optimum adsorption of Ni(II) was 98% at pH 7, metal ion concentration of 30 mg/L. The results obtained from the experimental work showed that fishbone can be used as an adsorbent for the removal of Ni(II) ions from aqueous solution.

Keywords: adsorption, aqueous media, fishbone, kinetic study

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Authors: Pornsiri Kaewpradit, Chalisa Pourneaw

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Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study.

Keywords: model predictive control, batch reactor, temperature control, membrane reactor

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Authors: Nikolaos Katsoulas, Sofia Faliagka, George Kountrias, Eleni Dimitriou, Eleftheria Pechlivani

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The challenges to feed the world in 2050 are becoming more and more apparent. This calls for producing more with fewer inputs (most of them under scarcity), higher resource efficiency, minimum or zero effect on the environment, and higher sustainability. Therefore, increasing the circularity of production systems is highly significant for their sustainability. Protected horticulture offers opportunities for maximum resource efficiency across various levels within and between farms and at the regional level), high-quality production, and contributes significantly to the nutrition security as part of the world food production. In greenhouses, closed soilless cultivation systems give the opportunity to increase the water and nutrient use efficiency and reduce the environmental impact of the cultivation system by the reuse of the drained water and nutrients. However, due to the low quality of the water used in the Mediterranean countries, a completely closed system is not feasible. Partial discharge of the drainage nutrient solution when the levels of electrical conductivity (EC) or of the toxic ions in the system are reached is still a necessity. Thus, in the frame of the circular economy concept, this work presents the utilisation of the drainage solution of soilless cultivation systems for microalgae and biofertilisers production. The system includes a greenhouse equipped with a soilless cultivation system, a drainage solution collection tank, a closed bioreactor for microalgae production, and a biocatalysis tank. The bioreactor tested in the frame of this work includes two closed tube loops of a capacity of 1000 L each where, after the initial inoculation, the microalgae is developed using as a growth medium the drainage solution collected from the greenhouse crops. The bioreactor includes light and temperature control while pH is still manually regulated. As soon as the microalgae culture reaches a certain density level, 20% of the culture is harvested, and the culture system is refiled by a drainage nutrient solution. The microalgae produced goes through a biocatalysis process, which leads to the production of a rich aminoacids (and nitrogen) biofertiliser. The produced biofertiliser is then used for the fertilisation of greenhouse crops. The complete production cycle along with the effects of the biofertiliser produced on crop growth and yield are presented and discussed in this manuscript. Acknowledgment: This work was carried out under the PestNu project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Green Deal grant agreement No. 101037128 — PestNu.

Keywords: soilless, water use efficiency, nutrients use efficiency, biostimulant

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Authors: Julia DeVoy, Olivia Berlin

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The United States exports over 1.6 billion pounds of post-consumer textiles every year, primarily to countries in the Global South. These textiles make their way to landfills and open-air dumps where they decompose, contaminating water systems and releasing harmful greenhouse gases. Through this inequitable system of waste disposal, countries with less political and economic power are coerced into accepting the environmental and health consequences of over-consumption in the Global North. Thus, the global trade of post-consumer textile waste represents a serious issue of environmental justice and a public health hazard. Our research located, characterizes, and quantifies the environmental and human health risks that occur when post-consumer textiles are left to decompose in landfills and open-air dumps in the Global South. In our work, we make use of United Nations International Trade Statistics data to map the global distribution of post-consumer textiles exported from the United States. Next, we present our landfill simulating reactor designed to measure toxicity of leachate resulting from the decomposition of textiles in developing countries and to quantify the related greenhouse gas emissions. This design makes use of low-cost and sustainable materials to promote frugal innovation and make landfill reactors more accessible. Finally, we describe how the data generated from these tools can be leveraged to inform individual consumer behaviors, local policies around textile waste disposal, and global advocacy efforts to mitigate the environmental harms caused by textile waste.

Keywords: sustainability, textile design, public health, built environment

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Authors: Aadila Cayenne, Hinrich Uellendahl

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Optimization of the anaerobic digestion (AD) process of halophytic plants is essential as the biomass contains a high salt content that can inhibit the AD process. Anaerobic co-digestion, together with manure, can resolve the inhibitory effects of saline biomass in order to dilute the salt concentration and establish favorable conditions for the microbial consortia of the AD process. The present laboratory study investigated the co-digestion of S. ramosissima (Sram), and pig manure (PM) in batch and semi-continuous stirred tank reactors (CSTR) under mesophilic (38oC) conditions. The 0.5L batch reactor experiments were in mono- and co-digestion of Sram: PM using different percent volatile solid (VS) based ratios (0:100, 15:85, 25:75, 35:65, 50:50, 100:0) with an inoculum to substate (I/R) ratio of 2. Two 5L CSTR systems (R1 and R2) were operated for 133 days with a feed of PM in a control reactor (R1) and with a co-digestion feed in an increasing Sram VS ratio of Sram: PM of 15:85, 25:75, 35:65 in reactor R2 at an organic loading rate (OLR) of 2 gVS/L/d and hydraulic retention time (HRT) of 20 days. After a start-up phase of 8 weeks for both reactors R1 and R2 with PM feed alone, the halophyte biomass Sram was added to the feed of R2 in an increasing ratio of 15 – 35 %VS Sram over an 11-week period. The process performance was monitored by pH, total solid (TS), VS, total nitrogen (TN), ammonium-nitrogen (NH4 – N), volatile fatty acids (VFA), and biomethane production. In the batch experiments, biomethane yields of 423, 418, 392, 365, 315, and 214 mL-CH4/gVS were achieved for mixtures of 0:100, 15:85, 25:75, 35:65, 50:50, 100:0 %VS Sram: PM, respectively. In the semi-continuous reactor processes, the average biomethane yields were 235, 387, and 365 mL-CH4/gVS for the phase of a co-digestion feed ratio in R2 of 15:85, 25:75, and 35:65 %VS Sram: PM, respectively. The methane yield of PM alone in R1 was in the corresponding phases on average 260, 388, and 446 mL-CH4/gVS. Accordingly, in the continuous AD process, the methane yield of the halophyte Sram was highest at 386 mL-CH4/gVS in the co-digestion ratio of 25:75%VS Sram: PM and significantly lower at 15:85 %VS Sram: PM (100 mL-CH4/gVS) and at 35:65 %VS Sram (214 mL-CH4/gVS). The co-digestion process showed no signs of inhibition at 2 – 4 g/L NH4 – N, 3.5 – 4.5 g/L TN, and total VFA of 0.45 – 2.6 g/L (based on Acetic, Propionic, Butyric and Valeric acid). This study demonstrates that a stable co-digestion process of S. ramosissima and pig manure can be achieved with a feed of 25%VS Sram at HRT of 20 d and OLR of 2 gVS/L/d.

Keywords: anaerobic co-digestion, biomethane production, halophytes, pig manure, salicornia ramosissima

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: Rosaria Tizzani, Tomas Morosinotto, Fabrizio Bezzo, Eleonora Sforza

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Red microalga Porphyridium marinum CCAP 13807/10 has the potential to produce a broad range of commercially valuable chemicals such as PhycoErytrin (PE) and sulphated ExoPolySaccharides (EPS). Multiple abiotic factors influence the growth of Porphyridium sp., e.g. the wavelength of the light source and different cultivation strategies (one or two steps, batch, semi-, and continuous regime). The microalga of interest is cultivated in a two-step system. First, the culture grows photoautotrophically in a controlled bioreactor with pH-dependent CO2 injection, temperature monitoring, light intensity, and LED wavelength remote control in a semicontinuous mode. In the second step, the harvested biomass is subjected to mixotrophic conditions to enhance further growth. Preliminary tests have been performed to define the suitable media, salinity, pH, and organic carbon substrate to obtain the highest biomass productivity. Dynamic light and operational conditions (e.g. HRT) are evaluated to achieve high biomass production, high PE accumulation in the biomass, and high EPS release in the medium. Porphyridium marinum is able to chromatically adapt the photosynthetic apparatus to efficiently exploit the full light spectra composition. The effect of specific narrow LED wavelengths (white W, red R, green G, blue B) and a combination of LEDs (WR, WB, WG, BR, BG, RG) are identified to understand the phenomenon of chromatic adaptation under photoautotrophic conditions. The effect of light intensity, residence time, and light quality are investigated to define optimal operational strategies for full scale commercial applications. Production of biomass, phycobiliproteins, PE, EPS, EPS sulfate content, EPS composition, Chlorophyll-a, and pigment content are monitored to determine the effect of LED wavelength on the cultivation Porphyridium marinum in order to optimize the production of these multiple, highly valuable bioproducts of commercial interest.

Keywords: red microalgae, LED, exopolysaccharide, phycoerythrin

Procedia PDF Downloads 86