Emissions modelling for engine cycle and aircraft trajectory optimisation

The aviation industry is currently experiencing a growth rate of about 4% per annum and this trend is expected to continue into the future. One concern about this growth rate is the impact it will have on the environment particularly in terms of emissions of CO2, NOx and relatively recently also cirrus clouds induced by contrails. The ACARE has set emissions reduction targets of 50% reduction of CO2 and noise and 80% reduction of NOx by 2020 relative to Y2000 technology. Clean Sky and other large EU collaborative projects have been launched in an effort to identify new, more efficient, aircraft and engine technologies, greener operational and asset management practices and lower life cycle emissions. This PhD research was funded by and contributed to the Systems for Green Operations Integrated Technology Demonstrator (SGO-ITD) of the Clean Sky project. The key contribution to knowledge of this research is the development and application of a methodology for simultaneous optimisation of aircraft trajectories and engine cycles. Previous studies on aircraft trajectory optimisation studies, published in the public domain, are based on relatively low fidelity models. The case studies presented in this thesis are multi-objective and based on higher fidelity, verified aircraft, engine and emissions models and also include assessments of conceptual engines with conceptual LPP combustors. The first task involved the development of reactor based NOx emission prediction models for a conventional aero gas turbine combustor and a novel conceptual lean pre-mixed pre-vaporised combustor. A persistent contrails prediction model was also developed. A multi-disciplinary framework comprising a genetic algorithm based optimiser integrated with an engine performance, an aircraft performance and an emission prediction model was then developed. The framework was initially used to perform multi-disciplinary aircraft trajectory optimisation studies and subsequently both aircraft trajectory and engine cycle optimisation studies simultaneously to assess trade-offs between mission fuel burn, flight time, NOx production and persistent contrails formation ... [cont.]

Entwicklung und Anwendung einer auf genetischen Algorithmen basierten Methode zur Reduktion und Optimierung von chemischen kinetischen Mechanismen

An automatic method for the reduction and optimization of chemical kinetic mechanisms under specific physical or thermodynamic conditions has been developed and described in this work. The mechanism reduction method relies on the genetic algorithm (GA) search for a smallest possible subset of reactions from the detailed mechanism while still preserving the ability of the reduced mechanism to describe the overall chemistry at an acceptable error. Accuracy of the reduced mechanism is determined by comparing its solution to the solution obtained with the full mechanism under the same initial and/or physical conditions. For the reduction, not only the chemical accuracy and the size of the mechanism are considered but also the time for its solution which helps to avoid stiff and slow-converging mechanisms. The (subsequent) optimization technique is based on a genetic algorithm that aims at finding new reaction rate coefficients to restore the accuracy which is usually decreased by the preceding reduction process. The accuracy is defined by an objective function that covers regions of interest where the reduced mechanism may deviate from the original mechanism. The objective function directs the search towards more accurate reduced mechanisms that are valid for a given set of operating conditions. The mechanism's performance is assessed for homogeneous-reactor or laminar-flame simulations against the results obtained from a given reference. An additional term introduced to the objective function is a so-called penalty term that influences the reaction rates during the optimization. With the penalty term, the change to the reaction rates can be minimized, keeping them as close as possible to their nominal values. It is demonstrated that the penalty function can be used instead of defining the uncertainty bounds from the literature for each reaction in the mechanism, which can be a tremendous effort when dealing with large or insufficiently investigated mechanisms. The penalty term can also be used for further reduction of the mechanism by driving the reaction rates towards zero during the optimization. This approach is addressed in a greater detail in the final section of the thesis which shows the convergence behaviour of the integer-coded reduction, the real-coded optimization and reduction of the reduced mechanisms and the real-coded-optimization and reduction of the full mechanism. The convergence study shows that the real-coded optimization with the size-penalty function exhibits the fastest convergence towards one global optimum, which makes a good case for investigating and improving the real-coded reduction as a direct way to optimize and reduce the full mechanism at the same time. The GA-based reduction and optimization method has shown to be robust, flexible, and applicable to a range of operating conditions by using multiple criteria simultaneously.In dieser Arbeit wurde eine automatische Methode zur Reduktion und Optimierung von chemischen kinetischen Mechanismen unter spezifischen physikalischen oder thermodynamischen Bedingungen entwickelt und beschrieben. Die Reduktion des Mechanismus beruht auf dem genetischen Algorithmus (GA), der nach einer kleinstmöglichen Untermenge von Reaktionen aus dem detaillierten Mechanismus sucht, während er die Fähigkeit des reduzierten Mechanismus noch bewahrt, die Gesamtchemie bei einem akzeptablen Fehler zu beschreiben. Die Genauigkeit des reduzierten Mechanismus wird durch Vergleich seiner Lösung mit der Lösung, die mit dem vollständigen Mechanismus unter den gleichen Anfängsbedingungen und/oder physikalischen Bedingungen erhalten wird, bestimmt. Für die Reduktion werden nicht nur die chemische Genauigkeit und die Größe des Mechanismus berücksichtigt, sondern auch die Simulationszeit, die hilft, steife und langsam konvergierende Mechanismen zu vermeiden. Die (nachfolgende) Optimierungstechnik basiert auf einem genetischen Algorithmus, der darauf abzielt, neue Koeffizienten der Reaktionsgeschwindigkeiten zu finden, um die Genauigkeit die üblicherweise durch den vorhergehenden Reduktionsvorgang verringert wird, wiederherzustellen. Die Genauigkeit wird durch eine Zielfunktion definiert, die Bereiche vom Interesse abdeckt, in denen der reduzierte Mechanismus von dem ursprünglichen Mechanismus abweichen kann. Die Zielfunktion lenkt die Suche nach genaueren reduzierten Mechanismen, die für einen bestimmten Satz von Betriebsbedingungen gültig sind. Die Leistung des Mechanismus wird für Simulationen von homogenem Reaktor oder laminaren Flammen gegenüber den Ergebnissen aus einer gegebenen Referenz bewertet. Ein zusätzlicher Term, der in der Zielfunktion eingeführt wird, ist ein sogenannter Strafterm, der die Reaktionsgeschwindigkeiten während der Optimierung beeinflusst. Mit dem Strafterm kann die Änderung der Reaktionsgeschwindigkeiten minimiert werden, sodass sie so nah wie möglich an ihren Startwerten gehalten werden. Es wird gezeigt, dass der Strafterm verwendet werden kann, anstatt die Unsicherheitsgrenzen aus der Literatur für jede Reaktion im Mechanismus zu definieren. Der Strafterm kann auch zur weiteren Reduzierung des Mechanismus verwendet werden, indem die Reaktionsgeschwindigkeiten während der Optimierung auf Null gestellt werden. Dieser Ansatz wird im letzten Abschnitt der Arbeit näher erläutert. Es wird das Konvergenzverhalten der ganzzahlig codierten Reduktion, der realcodierten Optimierung und Reduktion der reduzierten Mechanismen, sowie der realcodierten Optimierung und Reduktion des vollständigen Mechanismus analysiert. Die Konvergenzstudie zeigt, dass die realcodierte Optimierung mit dem Strafterm die schnellste Konvergenz zu einem globalen Optimum hat. Das bietet einige neue Möglichkeiten für die Erforschung und Verbesserung der realcodierten Reduktion, als direkten Weg zur gleichzeitigen Optimierung und Reduzierung des vollen Mechanismus. Die GA-basierte Reduktions- und Optimierungsmethoden haben sich als robust, flexibel und anwendbar für eine Reihe von Betriebsbedingungen erwiesen, indem gleichzeitig mehrere Kriterien betrachtet werden sollen

Model optimization and techniques for the simulation of multiphase chemical reactors

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016von M. Sc. Luís Guilherme Medeiros de SouzaLiteraturverzeichnis: Seite 121-13

Evaluation and optimisation of environmentally friendly aircraft propulsion systems

In this globalised world where the efficient transportation of people and goods greatly contributes to the development of a given region or country, the aviation industry has found the ideal conditions for its development, thereby becoming in one of the fastest growing economic sectors during the last decades. The continuing growth in air traffic and the increasing public awareness about the anthropogenic contribution to global warming have meant that environmental issues associated with aircraft operations are currently one of the most critical aspects of commercial aviation. Several alternatives for reducing the environmental impact of aircraft operations have been proposed over the years, and they broadly comprise reductions in the number of aircraft operations, changes in the type of aircraft, and changes in the aircraft operational rules and procedures. However, since the passenger traffic is expected to increase over the next years, only the last two options seem to be the most feasible solutions to alleviate the problem. Accordingly, the general aim of this research work is to develop a methodology to evaluate and quantify aircraft/engines design trade-offs originated as a consequence of addressing conflicting objectives such as low environmental impact and low operating costs. More specifically, it is an objective of this work to evaluate and optimise both aircraft flight trajectories and aircraft engine cycles taking into account multidisciplinary aspects such as performance, gaseous emissions, and economics. In order to accomplish the objectives proposed in this project, a methodology for optimising aircraft trajectories has been initially devised. A suitable optimiser with a library of optimisation algorithms, Polyphemus, has been then developed and/or adapted. Computational models simulating different disciplines such as aircraft performance, engine performance, and pollutants formation, have been selected or developed as necessary. Finally, several evaluation and optimisation processes aiming to determine optimum and ‘greener’ aircraft trajectories and engine cycles have been carried out and their main results summarised. In particular, an advanced, innovative gaseous emissions prediction model that allows the reliable calculation of emissions trends from current and potential future aircraft gas turbine combustors has been developed. When applied to a conventional combustor, the results showed that in general the emission trends observed in practice were sufficiently well reproduced, and in a computationally efficient manner for its subsequent incorporation in optimisation processes. For performing the processes of optimisation of aircraft trajectories and engine cycles, an optimiser (Polyphemus) has also been developed and/or adapted in this work. Generally the results obtained using Polyphemus and other commercially available optimisation algorithms presented a satisfactory level of agreement (average discrepancies of about 2%). It is then concluded that the development of Polyphemus is proceeding in the correct direction and should continue in order to improve its capabilities for identifying and efficiently computing optimum and ‘greener’ aircraft trajectories and engine cycles, which help to minimise the environmental impact of commercial aircraft operations. The main contributions of this work to knowledge broadly comprise the following: (i) development of an environmental-based methodology for carrying out both aircraft trajectory optimisation processes, and engine cycle optimisation-type ones; (ii) development of both an advanced, innovative gas turbine emissions prediction model, and an optimiser (Polyphemus) suitable to be integrated into multi-disciplinary optimisation frameworks; and (iii) determination and assessment of optimum and ‘greener’ aircraft trajectories and aircraft engine cycles using a multi-disciplinary optimisation tool, which included the computational tools developed in this work. Based on the results obtained from the different evaluation and optimisation processes carried out in this research project, it is concluded that there is indeed a feasible route to reduce the environmental impact of commercial aviation through the introduction of changes in the aircraft operational rules and procedures and/or in the aircraft/engine configurations. The magnitude of these reductions needs to be determined yet through careful consideration of more realistic aircraft trajectories and the use of higher fidelity computational models. For this purpose, the computations will eventually need to be extended to the entire fleet of aircraft, and they will also need to include different operational scenarios involving partial replacements of old aircraft with new environmentally friendly ones.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of a generalised kinetic model for the combustion of hydrocarbon fuels

Includes abstract.Includes bibliographical references (leaves 73-76).The aim of this work is to find a generalised model for the combustion of hydrocarbons. Predicted temperature-time profiles can be obtained from detailed combustion kinetics, which can be used to derive a generalised model. If the generalised model can predict results from the detailed model it can be applied in computational fluid dynamics code where detailed kinetic mechanisms cannot.A generalised kinetic model is proposed, adapting the Schreiber model (Schreiber et al., 1994) to accurately predict the combustion behaviour of hydrocarbon fuels. The combustion behaviour is described through the characteristics of the temperature-time profiles and the ignition delay diagram, which include two stage ignition and the negative temperature co-efficient region. The Schreiber model is specifically adapted to improve the description of the very low temperature rise before and between ignitions and the auto-catalytic temperature rises during ignition. Using a Genetic Algorithm to optimise the prediction of the proposed model, the pre-exponent factor Ai and the activation energy Eai are the adjustable parameters which are optimised for each reaction in the model. These parameters have been optimised for three fuels: i-octane, n-heptane and methanol. The ignition delays of the pure fuels were accurately predicted. The temperature-time profiles in the instances of two stage ignition are relatively inaccurate. The temperature profiles are however an improvement on the temperature profiles predicted by the Schreiber model, particularly in terms of the slow temperature rise during the ignition delay andthe sharp temperature rise during ignition. The combustion of the binary blends of the three fuels have been predicted using model parameters which are found using the rate constants of each fuel, the blends composition and binary interaction rules. The binary interaction parameters were also optimised using a Genetic Algorithm. The binary interaction rules are based on the Peng-Robinson mixing rules. Overall the ignition delays of binary fuel blends were accurately predicted using binary interactions. However, when modelling the blends between methanol and n-heptane, where one fuel has extreme NTC behaviour and the other fuel has no NTC behaviour, the predictions were less accurate. These binary interaction rules are then used to model ternary mixtures. It is shown that the combustion behaviour of ternary mixtures of the three fuels can be accurately predicted without any further regression or parameter fitting. The accuracy of the ternary prediction is dependent on the accuracy of the binary predictions

Detailed modelling and optmization of crystallization process

Orientador: Rubens Maciel FilhoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia QuimicaResumo: O foco de estudo neste trabalho é a cristalização, processo bastante utilizado industrialmente, principalmente na obtenção de produtos de alto valor agregado nas indústrias farmacêuticas e de química fina. Embora seja um processo de clássica utilização, seus mecanismos, sua modelagem e o real controle de sua operação ainda requerem estudos. A tese apresenta discussões e desenvolvimentos na área de modelagem determinística detalhada do processo e sua otimização, tanto por métodos determinísticos quanto estocásticos. A modelagem é discutida detalhadamente e os desenvolvimentos presentes na literatura de métodos numéricos aplicáveis à solução do balanço de população, parte integrante da modelagem, são apresentados com enfoque nos processos de cristalização e nas principais vantagens e desvantagens. Estudos preliminares de melhoria do processo de cristalização em modo batelada operada por resfriamento indicam a necessidade de otimização da política operacional de resfriamento. Uma vez que o método determinístico de otimização de Programação Quadrática Sucessiva se apresenta ineficiente para resolução do problema de otimização, a utilização de Algoritmo Genético, um método estocástico de otimização bastante estabelecido na literatura, é avaliada, para a busca do ótimo global deste processo, em um estudo pioneiro na literatura de aplicação dessa técnica de otimização em processos de cristalização. Uma vez que o uso de Algoritmos Genéticos exige que se executem sucessivas corridas com diferentes valores para os seus parâmetros no intuito de se aumentar a probabilidade de alcance do ótimo global (ou suas cercanias), um procedimento original, geral e relativamente simples é desenvolvido e proposto para detecção do conjunto de parâmetros do algoritmo de influência significativa sobre a resposta de otimização. A metodologia proposta é aplicada a casos de estudo gerais, de complexidades diferentes e se mostra bastante útil nos estudos preliminares via Algoritmo Genético. O procedimento é então aplicado ao problema de otimização da trajetória de resfriamento a ser utilizada em um processo de cristalização em modo batelada. Os resultados obtidos na tese apontam para a dificuldade dos métodos determinísticos de otimização em lidar com problemas de alta dimensionalidade, levando a ótimos locais, enquanto os métodos evolucionários são capazes de se aproximar do ótimo global, sendo, no entanto, de lenta execução. O procedimento desenvolvido para detecção dos parâmetros significativos do Algoritmo Genético é uma contribuição relevante da tese e pode ser aplicado a qualquer problema de otimização, de qualquer complexidade e dimensionalidadeAbstract: This work is focused on crystallization, a process widely used in industry, especially for the production of high added-value particles in pharmaceutical and fine chemistry industries. Although it is a process of established utilization, its mechanisms, modeling and the real control of its operation still require research and study. This thesis presents considerations and developments on the detailed deterministic modeling area and the process optimization with both deterministic and stochastic methods. The modeling is discussed in detail and the literature developed numerical methods for the population balance solution, which is part of the modeling, are presented focusing on crystallization processes and on the main advantages and drawbacks. Preliminary studies on batch cooling crystallization processes improvement drive to the need of cooling operating policy optimization. Since the Sequential Quadratic Programming deterministic method of optimization is inefficient for the optimization problem, the use of Genetic Algorithm (GA), a stochastic optimization method well established in literature, is evaluated in the global optimum search for this process, in a pioneering literature study of GA application in crystallization processes. Since the GA requires that many runs, with different values for its parameters, are executed, in order to increase the probability of global optimum (or its neighborhood) achievement, an original, general and relatively simple procedure for the detection of the parameters set with significant influence on the optimization response is developed and proposed. The proposed methodology is applied to general case studies, with different complexities and is very useful in the preliminary studies via GA. The procedure is, then, applied to the cooling profile optimization problem in a batch cooling optimization process. The results of the study presented in this thesis indicate that the deterministic optimization methods do not deal well with high dimensionality problems, leading to achievement of local optima. The evolutionary methods are able to detect the region of the global optimum but, on the other hand, are not fast codes. The developed procedure for the significant GA parameters detection is a relevant contribution of the thesis and can be applied to any optimization problem (of any complexity and of any dimensionality)DoutoradoDesenvolvimento de Processos QuímicosDoutor em Engenharia Químic

Evaluation of optimised flight trajectories for conventional and novel aircraft and engine integrated systems

Today, the air transport industry has become an essential element of global society by its great contributions to the wide exchanges of cultures/people and to the rapid growth in the world economy. However, on the other hand, the adverse impacts on the environment caused by air transport, such as air pollution, noise and climate change, are drawing, increasingly, growing public concern. In order to address the steady growth in air-travel demand in the next decades through an environmentally-friendly way and realise the ACARE 2020 environmental goals, The Clean Sky programme has been launched by European Union over the period 2008 – 2013. The project research, described in this thesis and sponsored by the Clean Sky programme, aims at evaluating the feasibility of reducing the environmental impact of commercial aviation through the introduction of changes in the aircraft operational rules and procedures, as well as the application of the new-generation propfan (open rotor) engine, based on flight trajectory multidisciplinary optimisation and analysis of commercial aircraft. In order to accomplish the above research objectives, a complete methodology to achieve and realise optimum flight trajectories has been initially proposed. Then, 12 component-level models which function as simulating different disciplines, such as aircraft performance, engine performance, engine gaseous emission, and flight noise, have been developed or selected/adopted. Further, nine system-level integration and optimisation models were built. These system-level models simulate flights from Amsterdam Schiphol airport in the Netherlands to Munich airport in Germany flown by different types of aircraft through different flight phases with different optimisation objectives. Finally, detailed investigations into the flight trajectory optimisations were performed, extensive optimisation results were achieved and corresponding description, analysis and comparisons were provided. The main contributions of this work to knowledge broadly comprise the following: 1) the further development regarding the methodology of flight trajectory multidisciplinary optimisation; 2) previous work on aircraft trajectory optimisation has often considered fixed objectives over the complete flight trajectory. This research focused on representative flight phases of a flight mission with different optimisation objectives, namely, noise impact and fuel burn during the departure phase; fuel burn and flight time during en route phase; and noise impact and NOx emission during the arrival phase; 3) this research has extended the current flight trajectory optimisations to turboprop and propfan equipped aircraft. As a result, a relative complete 2D flight trajectory multidisciplinary optimisation spectrum, spanned by primary commercial aircraft types, primary flight phases and primary optimisation objectives of interest, has been built. Although encouraging progress have been achieved, this project research, as with any other research activity, is also only ‘on the way’ rather than coming to the ‘end’ point. There are still many aspects which can be improved further and there is still much new research and exploration which can be investigated further. All these have also been suggested in this thesis

Pertanika Journal of Science & Technology

TesisEl propósito de este trabajo de investigación fue determinar el grado de relación entre el clima organizacional y la satisfacción laboral en los trabajadores de la Asociación para el Desarrollo Empresarial en Apurímac, Andahuaylas. A fin de proporcionar al directivo de la institución, sugerencias de cambio, reforzamiento y/o de mejora. Para la realización de este estudio se determinó como muestra al total de la población, conformada por 30 trabajadores a quienes se les aplicó un cuestionario estructurado, tipo escala de Likert, para diagnosticar el clima organizacional, compuesto por 21 ítems correspondiente a 5 dimensiones, y para medir la satisfacción laboral, compuesto por 14 ítems correspondiente a 2 dimensiones, validados por tres expertos en la materia. El análisis de fiabilidad de los cuestionarios arroja un coeficiente de Alf a de Cronbach para la escala de clima organizacional y satisfacción laboral de 0.796 y 0.721 respectivamente confiables. La hipótesis principal señalaba que existía relación entre el clima organizacional y satisfacción laboral. La principal conclusión comprobó que hay relación entre las dos variable, es decir, existe relación significativa positiva entre el clima organizacional y satisfacción laboral. A nivel de las hipótesis específicas se comprobó las dimensiones de clima organizacional la estructura, autonomía, relaciones interpersonales, identidad se correlacionaron de forma significante y positiva con la satisfacción laboral. Sin embargo no se encontró relación entre la dimensión recompensa con la satisfacción laboral en la Asociación para el Desarrollo Empresarial el Apurímac

The mathematical model of Schizosaccharomyces pombe : Batch and repeated batch simulations.

Mathematical models are playing an important part in the current developments in engineering, science and biotechnology. Within this field the most fashionable and representative organisms are the ones who are genetically and physiologically tractable. Since the fission yeast Schizosaccharomyces pombe plays a role model among them and its behaviour has medical, genetic and industrial links (related to cancer research, metabolic pathways and beer production), this makes it a particularly interesting organism for study. This dissertation presents the first physiological model ever developed for the yeast S. pombe. The model allows for the simulation and prediction of batch and repeated batch experiments which are an important engineering tool in terms of optimization of industrial processes improving yield in bioreactors by predicting precise values of harvest fraction (HF) and dilution cycle times (DCT). The model has been developed within the generic modelling framework of CelCyMUS (Cell Cycle Model University of Surrey). As part of the research being carried out CelCyMUS has been up-dated by introducing the new Fortran 95 features and utilities in order to exploit its powerful new features and to keep the generic model in pace with technological software advancements. The model is a one-dimensional age-based population balance for the fission yeast S. pombe. It includes the four typical phases (S, G2, M and G1) with the G2 phase divided into two phases (G2A, G2B) and two checkpoints that govern the movement of cells between G1 and S, and G2B and M phases. The transitions (movement of cells between phases) are determined by a probability function related to the consumption of glucose. The G2B-M transition is also dependent on cell size, but since individual growth of cells is related to the consumption of the carbon source (in this case glucose), cell size is dependent upon the amount of glucose consumed per cell. The model also includes a phase for cells facing starvation before going into a meiotic cycle, with some chance of coming back to the mitotic cycle, and a death phase that accounts for cells dying with no chance of recovering at all. Parameters in the S. pombe model have been gathered from experimental data in batch culture reported in literature. Data generated from this specific model have been compared with data from experiments (Fotuhi, 2002) in batch and repeated batch cultures of S. pombe following the behaviour of population balance, consumption of nutrients, and production of metabolites. The new code was tested by successftilly reproducing data from mm-321 hybridoma cell line, the first specific model of a cell line developed in CelCyMUS. As a new feature a model of mass transfer has been incorporated in the generic framework. This mass transfer module accounts for interactions of metabolites (oxygen and carbon dioxide) in the gas and liquid phase of bioreactors. The new S. pombe model was fitted to the experiments of Creanor (1992) on synchronised cultures where the consumption of oxygen was being measured. Such experiments identify two points (G2B and G1) where the rate of oxygen uptake increased in the cycle, doubling the consumption at the end of every cycle. With the model fitted to experimental results in synchronised cultures of S. pombe the model was then used to simulate desynchronised cultures. S. pombe was successfully tested when reproducing experimental data generated by Fotuhi (2002) in S.pombe for batch and repeated batch bioreactors. The S. pombe model was able to simulate cell number, oxygen and glucose consumption. Carbon dioxide and ATP production were predicted by the model however there was no experimental data to compare with. Now that the S. pombe model has been tested against experimental data it will be applied in a model-based observer strategy for the online control of bioreactors

Degradation of dye-containing textile effluents by enzymatic catalysis

Tese de doutoramento. Engenharia Química. Faculdade de Engenharia. Universidade do Porto. 201