938 resultados para batch digesters


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This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.

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Diazotrophic (N2-fixing) cyanobacteria provide the biological source of new nitrogen for large parts of the ocean. However, little is known about their sensitivity to global change. Here we show that the single most important nitrogen fixer in today's ocean, Trichodesmium, is strongly affected by changes in CO2 concentrations. Cell division rate doubled with rising CO2 (glacial to projected year 2100 levels) prompting lower carbon, nitrogen and phosphorus cellular contents, and reduced cell dimensions. N2 fixation rates per unit of phosphorus utilization as well as C:P and N:P ratios more than doubled at high CO2, with no change in C:N ratios. This could enhance the productivity of N-limited oligotrophic oceans, drive some of these areas into P limitation, and increase biological carbon sequestration in the ocean. The observed CO2 sensitivity of Trichodesmium could thereby provide a strong negative feedback to atmospheric CO2 increase.

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The impact of alkyl chain length on the esterification of C2–C16 organic acids with C1–C4 alcohols has been systematically investigated over bulk and SBA-15 supported sulfated zirconias (SZs). Rates of catalytic esterification for methanol with acetic acid are directly proportional to the sulfur content for both SZ and SZ/SBA-15, with the high dispersion of SZ achievable in conformal coatings over mesoporous SBA-15 confering significant rate-enhancements. Esterification over the most active 0.24 mmol gcat−1 bulk SZ and 0.29 mmol gcat−1 SZ/SBA-15 materials was inversely proportional to the alkyl chain length of alcohol and acid reactants; being most sensitive to changes from methanol to ethanol and acetic to hexanoic acids respectively. Kinetic analyses reveal that these alkyl chain dependencies are in excellent accord with the Taft relationship for polar and steric effects in aliphatic systems and the enthalpy of alcohol adsorption, implicating a Langmuir–Hinshelwood mechanism. The first continuous production of methyl propionate over a SZ fixed-bed is also demonstrated.

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The presented thesis was written in the frame of a project called 'seepage water prognosis'. It was funded by the Federal Ministry for Education and Science (BMBF). 41 German institutions among them research institutes of universities, public authorities and engineering companies were financed for three years respectively. The aim was to work out the scientific basis that is needed to carry out a seepage water prognosis (Oberacker und Eberle, 2002). According to the Federal German Soil Protection Act (Federal Bulletin, 1998) a seepage water prognosis is required in order to avoid future soil impacts from the application of recycling products. The participants focused on the development of either methods to determine the source strength of the materials investigated, which is defined as the total mass flow caused by natural leaching or on models to predict the contaminants transport through the underlying soil. Annual meetings of all participants as well as separate meetings of the two subprojects were held. The department of Geosciences in Bremen participated with two subprojects. The aim of the subproject that resulted in this thesis was the development of easily applicable, valid, and generally accepted laboratory methods for the determination of the source strength. In the scope of the second subproject my colleague Veith Becker developed a computer model for the transport prognosis with the source strength as the main input parameter.

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Das Verfahren der Lebensmitteltrocknung wird häufig angewendet, um ein Produkt für längere Zeit haltbar zu machen. Obst und Gemüse sind aufgrund ihres hohen Wassergehalts leicht verderblich durch biochemische Vorgänge innerhalb des Produktes, nicht sachgemäße Lagerung und unzureichende Transportmöglichkeiten. Um solche Verluste zu vermeiden wird die direkte Trocknung eingesetzt, welche die älteste Methode zum langfristigen haltbarmachen ist. Diese Methode ist jedoch veraltet und kann den heutigen Herausforderungen nicht gerecht werden. In der vorliegenden Arbeit wurde ein neuer Chargentrockner, mit diagonalem Luftstömungskanal entlang der Länge des Trocknungsraumes und ohne Leitbleche entwickelt. Neben dem unbestreitbaren Nutzen der Verwendung von Leitblechen, erhöhen diese jedoch die Konstruktionskosten und führen auch zu einer Erhöhung des Druckverlustes. Dadurch wird im Trocknungsprozess mehr Energie verbraucht. Um eine räumlich gleichmäßige Trocknung ohne Leitbleche zu erreichen, wurden die Lebensmittelbehälter diagonal entlang der Länge des Trockners platziert. Das vorrangige Ziel des diagonalen Kanals war, die einströmende, warme Luft gleichmäßig auf das gesamte Produkt auszurichten. Die Simulation des Luftstroms wurde mit ANSYS-Fluent in der ANSYS Workbench Plattform durchgeführt. Zwei verschiedene Geometrien der Trocknungskammer, diagonal und nicht diagonal, wurden modelliert und die Ergebnisse für eine gleichmäßige Luftverteilung aus dem diagonalen Luftströmungsdesign erhalten. Es wurde eine Reihe von Experimenten durchgeführt, um das Design zu bewerten. Kartoffelscheiben dienten als Trocknungsgut. Die statistischen Ergebnisse zeigen einen guten Korrelationskoeffizienten für die Luftstromverteilung (87,09%) zwischen dem durchschnittlich vorhergesagten und der durchschnittlichen gemessenen Strömungsgeschwindigkeit. Um den Effekt der gleichmäßigen Luftverteilung auf die Veränderung der Qualität zu bewerten, wurde die Farbe des Produktes, entlang der gesamten Länge der Trocknungskammer kontaktfrei im on-line-Verfahren bestimmt. Zu diesem Zweck wurde eine Imaging-Box, bestehend aus Kamera und Beleuchtung entwickelt. Räumliche Unterschiede dieses Qualitätsparameters wurden als Kriterium gewählt, um die gleichmäßige Trocknungsqualität in der Trocknungskammer zu bewerten. Entscheidend beim Lebensmittel-Chargentrockner ist sein Energieverbrauch. Dafür wurden thermodynamische Analysen des Trockners durchgeführt. Die Energieeffizienz des Systems wurde unter den gewählten Trocknungsbedingungen mit 50,16% kalkuliert. Die durchschnittlich genutzten Energie in Form von Elektrizität zur Herstellung von 1kg getrockneter Kartoffeln wurde mit weniger als 16,24 MJ/kg und weniger als 4,78 MJ/kg Wasser zum verdampfen bei einer sehr hohen Temperatur von jeweils 65°C und Scheibendicken von 5mm kalkuliert. Die Energie- und Exergieanalysen für diagonale Chargentrockner wurden zudem mit denen anderer Chargentrockner verglichen. Die Auswahl von Trocknungstemperatur, Massenflussrate der Trocknungsluft, Trocknerkapazität und Heiztyp sind die wichtigen Parameter zur Bewertung der genutzten Energie von Chargentrocknern. Die Entwicklung des diagonalen Chargentrockners ist eine nützliche und effektive Möglichkeit um dei Trocknungshomogenität zu erhöhen. Das Design erlaubt es, das gesamte Produkt in der Trocknungskammer gleichmäßigen Luftverhältnissen auszusetzen, statt die Luft von einer Horde zur nächsten zu leiten.

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This thesis addresses the Batch Reinforcement Learning methods in Robotics. This sub-class of Reinforcement Learning has shown promising results and has been the focus of recent research. Three contributions are proposed that aim to extend the state-of-art methods allowing for a faster and more stable learning process, such as required for learning in Robotics. The Q-learning update-rule is widely applied, since it allows to learn without the presence of a model of the environment. However, this update-rule is transition-based and does not take advantage of the underlying episodic structure of collected batch of interactions. The Q-Batch update-rule is proposed in this thesis, to process experiencies along the trajectories collected in the interaction phase. This allows a faster propagation of obtained rewards and penalties, resulting in faster and more robust learning. Non-parametric function approximations are explored, such as Gaussian Processes. This type of approximators allows to encode prior knowledge about the latent function, in the form of kernels, providing a higher level of exibility and accuracy. The application of Gaussian Processes in Batch Reinforcement Learning presented a higher performance in learning tasks than other function approximations used in the literature. Lastly, in order to extract more information from the experiences collected by the agent, model-learning techniques are incorporated to learn the system dynamics. In this way, it is possible to augment the set of collected experiences with experiences generated through planning using the learned models. Experiments were carried out mainly in simulation, with some tests carried out in a physical robotic platform. The obtained results show that the proposed approaches are able to outperform the classical Fitted Q Iteration.

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Carbon capture and storage (CCS) in the oil and water industries is becoming common and a significant consumer of energy typically requiring 150–450 °C and or several hundred bar pressure [1] particularly in geological deposition. A biological carbon capture and conversion has been considered in conventional anaerobic digestion processes. The process has been utilised in biological mixed culture, where acetoclastic bacteria and hydrogenophilic methanogens play a major key role in the utilisation of carbon dioxide. However, the bio catalytic microorganisms, hydrogenophilic methanogens are reported to be unstable with acetoclastic bacteria. In this work the biochemical thermodynamic efficiency was investigated for the stabilisation of the microbial process in carbon capture and utilisation. The authors observed that a thermodynamic efficiency of biological carbon capture and utilisation (BCCU) had 32% of overall reduction in yield of carbon dioxide with complimentary increase of 30% in yield of methane, while the process was overall endothermic. Total consumption of energy (≈0.33 MJ l−1) was estimated for the carbonate solubility (0.1 mol l−1) in batched BCCU. This has a major influence on microbial composition in the bioreactor. This thermodynamic study is an essential tool to aid the understanding of the interactions between operating parameters and the mixed microbial culture.

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In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy -- Some mathematical models are developed from experimental data to describe the system behavior -- The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed -- The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework

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The current energy market requires urgent revision for the introduction of renewable, less-polluting and inexpensive energy sources. Biohydrogen (bioH2) is considered to be one of the most appropriate options for this model shift, being easily produced through the anaerobic fermentation of carbohydrate-containing biomass. Ideally, the feedstock should be low-cost, widely available and convertible into a product of interest. Microalgae are considered to possess the referred properties, being also highly valued for their capability to assimilate CO2 [1]. The microalga Spirogyra sp. is able to accumulate high concentrations of intracellular starch, a preferential carbon source for some bioH2 producing bacteria such as Clostridium butyricum [2]. In the present work, Spirogyra biomass was submitted to acid hydrolysis to degrade polymeric components and increase the biomass fermentability. Initial tests of bioH2 production in 120 mL reactors with C. butyricum yielded a maximum volumetric productivity of 141 mL H2/L.h and a H2 production yield of 3.78 mol H2/mol consumed sugars. Subsequently, a sequential batch reactor (SBR) was used for the continuous H2 production from Spirogyra hydrolysate. After 3 consecutive batches, the fermentation achieved a maximum volumetric productivity of 324 mL H2/L.h, higher than most results obtained in similar production systems [3] and a potential H2 production yield of 10.4 L H2/L hydrolysate per day. The H2 yield achieved in the SBR was 2.59 mol H2/mol, a value that is comparable to those attained with several thermophilic microorganisms [3], [4]. In the present work, a detailed energy consumption of the microalgae value-chain is presented and compared with previous results from the literature. The specific energy requirements were determined and the functional unit considered was gH2 and MJH2. It was possible to identify the process stages responsible for the highest energy consumption during bioH2 production from Spirogyra biomass for further optimisation.

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L’industrie des biocarburants de deuxième génération utilise, entre autre, la biomasse lignocellulosique issue de résidus forestiers et agricoles et celle issue de cultures énergétiques. Le sorgho sucré [Sorghum bicolor (L.) Moench] fait partie de ces cultures énergétiques. L’intérêt croissant de l’industrie agroalimentaire et des biocarburants pour cette plante est dû à sa haute teneur en sucres (jusqu’à 60% en masse sèche). En plus de se développer rapidement (en 5-6 mois), le sorgho sucré a l’avantage de pouvoir croître sur des sols pauvres en nutriments et dans des conditions de faibles apports en eau, ce qui en fait une matière première intéressante pour l’industrie, notamment pour la production de bioéthanol. Le concept de bioraffinerie alliant la production de biocarburants à celle de bioénergies ou de bioproduits est de plus en plus étudié afin de valoriser la production des biocarburants. Dans le contexte d’une bioraffinerie exploitant la biomasse lignocellulosique, il est nécessaire de s’intéresser aux différents métabolites extractibles en plus des macromolécules permettant la fabrication de biocarburants et de biocommodités. Ceux-ci pouvant avoir une haute valeur ajoutée et intéresser l’industrie pharmaceutique ou cosmétique par exemple. Les techniques classiques pour extraire ces métabolites sont notamment l’extraction au Soxhlet et par macération ou percolation, qui sont longues et coûteuses en énergie. Ce projet s’intéresse donc à une méthode d’extraction des métabolites primaires et secondaires du sorgho sucré, moins coûteuse et plus courte, permettant de valoriser économiquement l’exploitation industrielle du de cette culture énergétique. Ce travail au sein de la CRIEC-B a porté spécifiquement sur l’utilisation d’une émulsion ultrasonique eau/carbonate de diméthyle permettant de diminuer les temps d’opération (passant à moins d’une heure au lieu de plusieurs heures) et les quantités de solvants mis en jeu dans le procédé d’extraction. Cette émulsion extractive permet ainsi de solubiliser à la fois les métabolites hydrophiles et ceux hydrophobes. De plus, l’impact environnemental est limité par l’utilisation de solvants respectueux de l’environnement (80 % d’eau et 20 % de carbonate de diméthyle). L’utilisation de deux systèmes d’extraction a été étudiée. L’un consiste en la recirculation de l’émulsion, en continu, au travers du lit de biomasse; le deuxième permet la mise en contact de la biomasse et des solvants avec la sonde à ultrasons, créant l’émulsion et favorisant la sonolyse de la biomasse. Ainsi, en réacteur « batch » avec recirculation de l’émulsion eau/DMC, à 370 mL.min[indice supérieur -1], au sein du lit de biomasse, l’extraction est de 37,91 % en 5 minutes, ce qui est supérieur à la méthode ASTM D1105-96 (34,01 % en 11h). De plus, en réacteur « batch – piston », où la biomasse est en contact direct avec les ultrasons et l’émulsion eau/DMC, les meilleurs rendements sont de 35,39 % en 17,5 minutes, avec 15 psig de pression et 70 % d’amplitude des ultrasons. Des tests effectués sur des particules de sorgho grossières ont donné des résultats similaires avec 30,23 % d’extraits en réacteur « batch » avec recirculation de l’émulsion (5 min, 370 mL.min[indice supérieur -1]) et 34,66 % avec le réacteur « batch-piston » (30 psig, 30 minutes, 95 % d’amplitude).

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Este estudo tem como objetivo a valorização económica de resíduos agroindustriais, nomeadamente resíduos de kiwi, por digestão anaeróbia de forma a otimizar a produção de biogás e a sua qualidade (% CH4). Trata-se de uma pesquisa experimental que consistiu na avaliação da produção de biogás usando diferentes proporções de substrato e inóculo, quatro valores distintos para a razão C:N, inóculo de diferentes digestores e colheita do inóculo em épocas distintas do ano. Os ensaios foram desenvolvidos num reator batch em condições mesofílicas, sendo o processo acompanhado por monitorização dos parâmetros: pH, Alcalinidade, Ácidos Gordos Voláteis (AGV), Sólidos Totais (ST), Sólidos Voláteis (SV), Carência Química de Oxigénio (CQO) e Carbono. Para a totalidade dos ensaios, o valor de pH no reator praticamente não apresentou variação, mantendo-se em torno de 7,0; a alcalinidade do meio, 1500 mg CaCO3/L, revelou-se adequada uma vez que no final do processo de DA a concentração de AGV (400-600 mg/L), nunca excede os valores considerados críticos. Os resultados obtidos apresentam valores interessantes para um número considerável de ensaios. Das 10 experiências realizadas, em duas foram obtidos resultados muito significativos em relação à literatura; o ensaio com 1% de substrato (experiência 2) registou uma produção de biogás de 1628 L/kg SV com uma %CH4 de 57% e o biogás de maior qualidade, 85% de metano, foi obtido no ensaio com 5% de resíduo de kiwi (experiência 10). As experiências em que se avaliou o efeito da razão C:N foram as menos produtivas, possivelmente devido à inibição da atividade da população microbiana pelo KNO3. A qualidade do inóculo revelou-se determinante num conjunto de ensaios, nomeadamente quando a sua colheita foi realizada no inverno, com o digestor a apresentar temperaturas bastante baixas. De acordo com os valores mais favoráveis para a produção de biogás, por tonelada de resíduo de kiwi poderá ser obtido um valor monetário bruto de 102 €, resolvendo-se um problema de eliminação deste resíduo, com valorização energética simultaneamente.

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The present study deals with a new analytical procedure based on a cellulose diffusion membrane and immobilised tetraethylene-pentamine-hexaacetate chelator (DM-TEPHA) for an in situ differentiation of labile and inert metal species in aquatic systems. The DM-TEPHA system was prepared by placing TEPHA chelator in pre-purified cellulose bags and in situ applied immersing the system in two Brazilian rivers to study the relative lability of metal species (Cu, Pb, Fe, Mn and Ni) as a function of the time and the quantity of exchanger, respectively. The procedure is simple and enables a new perspective for understanding the complexation, transport, stability and lability of metal species in aquatic systems rich in organic matter.

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An integrated analysis of naproxen adsorption on bone char in batch and packed-bed column conditions has been performed. Kinetic, thermodynamic and breakthrough parameters have been calculated using adsorption models and artificial neural networks. Results show that naproxen removal using bone char in batch conditions is a feasible and effective process, which could involve electrostatic and non-electrostatic interactions depending mainly on pH conditions. However, the application of packed-bed column for naproxen adsorption on bone char is not effective for the treatment of diluted solutions due to the low degree of adsorbent utilization (below 4%) at tested operating conditions. The proposed mechanism for naproxen removal using bone char could include a complexation process via phosphate and naproxen, hydrogen bonding and the possibility of hydrophobic interactions via π–π electron. This study highlights the relevance of performing an integrated analysis of adsorbent effectiveness in batch and dynamic conditions to establish the best process configuration for the removal of emerging water pollutants such as pharmaceuticals.

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The remediation of paracetamol (PA), an emerging contaminant frequently found in wastewater treatment plants, has been studied in the low concentration range (0.3–10 mg L−1) using as adsorbent a biomass-derived activated carbon. PA uptake of up to 100 mg g−1 over the activated carbon has been obtained, with the adsorption isotherms being fairly explained by the Langmuir model. The application of Reichemberg and the Vermeulen equations to the batch kinetics experiments allowed estimating homogeneous and heterogeneous diffusion coefficients, reflecting the dependence of diffusion with the surface coverage of PA. A series of rapid small-scale column tests were carried out to determine the breakthrough curves under different operational conditions (temperature, PA concentration, flow rate, bed length). The suitability of the proposed adsorbent for the remediation of PA in fixed-bed adsorption was proven by the high PA adsorption capacity along with the fast adsorption and the reduced height of the mass transfer zone of the columns. We have demonstrated that, thanks to the use of the heterogeneous diffusion coefficient, the proposed mathematical approach for the numerical solution to the mass balance of the column provides a reliable description of the breakthrough profiles and the design parameters, being much more accurate than models based in the classical linear driving force.