A Novel Optimization Framework to Replicate the Vibro-Acoustics Response of an Aircraft Fuselage

In this work, a novel optimization framework, based on a Multi-Disciplinary Optimization (MDO) procedure, applied to the vibro-acoustic Finite Element Method (FEM) model of an aircraft fuselage mock-up, is proposed. The MDO procedure, based on an Efficient Global Optimization (EGO)-like approach, is implemented to characterize acoustic sources that replicate the sound pressure field generated by the engines on the fuselage. A realistic sound pressure field, evaluated by aeroacoustic simulations, was considered as the reference acoustic load, whereas two equivalent sound fields, displayed by two different arrays of microphones and generated by the same configuration of monopoles, were calculated by the proposed vibro-acoustic FEM-MDO procedure. The proposed FEM-MDO framework enables to set up ground experimental tests on aircraft components, useful to replicate their vibro-acoustic performances as if tested in flight. More in general, such a procedure can also be used as a reference tool to design simplified tests starting from more complex ones

Modelação numérica da resposta dinâmica de proteções multi-material sujeitas a impactos balísticos

With the current events concerning terrorist attacks, it is imperative to perform research and development on issues related to ballistic protection. The need to protect soldiers from high impact velocity threats has become increasingly important and challenging. Within the scope of this work the aim is to develop an optimised armour configuration for an advanced ballistic helmet design, which is able to defeat impacts from high velocity rifle bullets. This is done using finite element modelling supported by results from experimental tests. The design presented here is based on four different layers, where: (i) the first layer is designed to break and erode the projectile, (ii) the second layer absorbs the kinetic energy of the projectile, (iii) the third layer minimises the back face deflection and, finally, (iv) a fourth layer absorbs the shock wave of the initial impact and provides the necessary standoff (required by the back face deflection) for the first three layers, so that direct contact between these layers and the head does not occur. The results obtained by simulation with the finite element method (using LS-DynaTM) demonstrate that the models agree with the experimental results. A detailed numerical study of the diferent layers as well as the 7.62x39 M43 projectile was made. A good correlation between numerical and experimental results of the ammunition and armour materials was achieved, as well as between numerical and experimental results in terms of the depth of indentation as a function of impact velocity of the new ballistic helmet design. The last two sets of numerical analysis made for the helmet shell configuration was relative to the shock absorbing layer. The first set of simulations consisted of introducing rigid boundaries to the composite layer of the at panel. A second set of simulations considered the composite layer of the at panel to be attached to a rigid frame, without fixing this frame. From the simulation results, a shock-absorbing layer can be designed in such a way as to significantly reduce the risk on behind-helmet blunt trauma, and with acceptable force transfer to the head. An optimum standoff distance was determined for a ballistic helmet concept able to stop the M43 Kalashnikov projectile.Face aos sucessivos eventos relativos a ataques terroristas, é imperativo realizar investigação científica e desenvolvimento em questões relacionadas com a proteção balística. O objetivo principal do trabalho que aqui se apresenta _e desenvolver um novo capacete balístico capaz de parar projéteis de alta velocidade, usando modelos de elementos finitos, validados com base em resultados de testes experimentais. O modelo de capacete aqui apresentado _e composto por quatro diferentes camadas, onde: (i) a primeira é capaz de deformar e fraturar o projétil, especialmente o núcleo de aço, ajudando a reduzir a sua velocidade; (ii) a segunda camada absorve energia cinética do projétil, (iii) a terceira limita a deflexão da face anterior e, finalmente, (iv) a quarta camada absorve a onda de choque do impacto inicial e garante a distância necessária para evitar o contato dessas camadas com a cabeça. Foi também realizado um estudo numérico detalhado das diferentes partes do projétil 7.62 x 39 M43. Obteve-se uma boa correlação entre os resultados numéricos (usando o software LS-DynaTM) e experimentais para os modelos do projétil quer do equipamento de proteção pessoal (capacete). Atingiu-se também uma boa correlação em termos de velocidade de impacto em função da profundidade de deformação do novo desenho de capacete balístico. Realizou-se uma análise numérica mais detalhada para a configuração do capacete relativa _a camada de absorção da onda de choque. Um primeiro conjunto de simulações consistiu em introduzir limites rígidos nas extremidades das três primeiras camadas. Um segundo conjunto de simulações considerou as três primeiras camadas anexadas a uma estrutura rígida, fixa no capacete. A partir dos resultados numéricos, conclui-se ser possível projetar uma camada de absorção da onda de choque de maneira a reduzir significativamente o risco de traumatismo craniano causado pelo impacto no capacete. Uma distância mínima entre a cabeça e o capacete pode, portanto, ser determinada para um novo modelo de capacete balístico capaz de parar o projétil M43 Kalashnikov.Programa Doutoral em Engenharia Mecânic

Evaluation of an evaluation list for model complexity

This study (‘WOt-werkdocument’) builds on the project ‘Evaluation model complexity’, in which a list has been developed to assess the ‘equilibrium’ of a model or database. This list compares the complexity of a model or database with the availability and quality of data and the application area. A model or database is said to be in equilibrium if the uncertainty in the predictions by the model or database is appropriately small for the intended application, while the data availability supports this complexity. In this study the prototype of the list is reviewed and tested by applying it to test cases. The review has been performed by modelling experts from within and outside Wageningen University & Research centre (Wageningen UR). The test cases have been selected form the scientific literature in order to evaluate the various elements of the list. The results are used to update the list to a new version

Ecological models at fish community and species level to support effective river restoration

RESUMEN Los peces nativos son indicadores de la salud de los ecosistemas acuáticos, y se han convertido en un elemento de calidad clave para evaluar el estado ecológico de los ríos. La comprensión de los factores que afectan a las especies nativas de peces es importante para la gestión y conservación de los ecosistemas acuáticos. El objetivo general de esta tesis es analizar las relaciones entre variables biológicas y de hábitat (incluyendo la conectividad) a través de una variedad de escalas espaciales en los ríos Mediterráneos, con el desarrollo de herramientas de modelación para apoyar la toma de decisiones en la restauración de ríos. Esta tesis se compone de cuatro artículos. El primero tiene como objetivos modelar la relación entre un conjunto de variables ambientales y la riqueza de especies nativas (NFSR), y evaluar la eficacia de potenciales acciones de restauración para mejorar la NFSR en la cuenca del río Júcar. Para ello se aplicó un enfoque de modelación de red neuronal artificial (ANN), utilizando en la fase de entrenamiento el algoritmo Levenberg-Marquardt. Se aplicó el método de las derivadas parciales para determinar la importancia relativa de las variables ambientales. Según los resultados, el modelo de ANN combina variables que describen la calidad de ribera, la calidad del agua y el hábitat físico, y ayudó a identificar los principales factores que condicionan el patrón de distribución de la NFSR en los ríos Mediterráneos. En la segunda parte del estudio, el modelo fue utilizado para evaluar la eficacia de dos acciones de restauración en el río Júcar: la eliminación de dos azudes abandonados, con el consiguiente incremento de la proporción de corrientes. Estas simulaciones indican que la riqueza aumenta con el incremento de la longitud libre de barreras artificiales y la proporción del mesohabitat de corriente, y demostró la utilidad de las ANN como una poderosa herramienta para apoyar la toma de decisiones en el manejo y restauración ecológica de los ríos Mediterráneos. El segundo artículo tiene como objetivo determinar la importancia relativa de los dos principales factores que controlan la reducción de la riqueza de peces (NFSR), es decir, las interacciones entre las especies acuáticas, variables del hábitat (incluyendo la conectividad fluvial) y biológicas (incluidas las especies invasoras) en los ríos Júcar, Cabriel y Turia. Con este fin, tres modelos de ANN fueron analizados: el primero fue construido solamente con variables biológicas, el segundo se construyó únicamente con variables de hábitat y el tercero con la combinación de estos dos grupos de variables. Los resultados muestran que las variables de hábitat son los ¿drivers¿ más importantes para la distribución de NFSR, y demuestran la importancia ecológica de los modelos desarrollados. Los resultados de este estudio destacan la necesidad de proponer medidas de mitigación relacionadas con la mejora del hábitat (incluyendo la variabilidad de caudales en el río) como medida para conservar y restaurar los ríos Mediterráneos. El tercer artículo busca comparar la fiabilidad y relevancia ecológica de dos modelos predictivos de NFSR, basados en redes neuronales artificiales (ANN) y random forests (RF). La relevancia de las variables seleccionadas por cada modelo se evaluó a partir del conocimiento ecológico y apoyado por otras investigaciones. Los dos modelos fueron desarrollados utilizando validación cruzada k-fold y su desempeño fue evaluado a través de tres índices: el coeficiente de determinación (R2 ), el error cuadrático medio (MSE) y el coeficiente de determinación ajustado (R2 adj). Según los resultados, RF obtuvo el mejor desempeño en entrenamiento. Pero, el procedimiento de validación cruzada reveló que ambas técnicas generaron resultados similares (R2 = 68% para RF y R2 = 66% para ANN). La comparación de diferentes métodos de machine learning es muy útil para el análisis crítico de los resultados obtenidos a través de los modelos. El cuarto artículo tiene como objetivo evaluar la capacidad de las ANN para identificar los factores que afectan a la densidad y la presencia/ausencia de Luciobarbus guiraonis en la demarcación hidrográfica del Júcar. Se utilizó una red neuronal artificial multicapa de tipo feedforward (ANN) para representar relaciones no lineales entre descriptores de L. guiraonis con variables biológicas y de hábitat. El poder predictivo de los modelos se evaluó con base en el índice Kappa (k), la proporción de casos correctamente clasificados (CCI) y el área bajo la curva (AUC) característica operativa del receptor (ROC). La presencia/ausencia de L. guiraonis fue bien predicha por el modelo ANN (CCI = 87%, AUC = 0.85 y k = 0.66). La predicción de la densidad fue moderada (CCI = 62%, AUC = 0.71 y k = 0.43). Las variables más importantes que describen la presencia/ausencia fueron: radiación solar, área de drenaje y la proporción de especies exóticas de peces con un peso relativo del 27.8%, 24.53% y 13.60% respectivamente. En el modelo de densidad, las variables más importantes fueron el coeficiente de variación de los caudales medios anuales con una importancia relativa del 50.5% y la proporción de especies exóticas de peces con el 24.4%. Los modelos proporcionan información importante acerca de la relación de L. guiraonis con variables bióticas y de hábitat, este nuevo conocimiento podría utilizarse para apoyar futuros estudios y para contribuir en la toma de decisiones para la conservación y manejo de especies en los en los ríos Júcar, Cabriel y Turia.Olaya Marín, EJ. (2013). Ecological models at fish community and species level to support effective river restoration [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/28853TESI

Multidisciplinary Design Optimization for Space Applications

Multidisciplinary Design Optimization (MDO) has been increasingly studied in aerospace engineering with the main purpose of reducing monetary and schedule costs. The traditional design approach of optimizing each discipline separately and manually iterating to achieve good solutions is substituted by exploiting the interactions between the disciplines and concurrently optimizing every subsystem. The target of the research was the development of a flexible software suite capable of concurrently optimizing the design of a rocket propellant launch vehicle for multiple objectives. The possibility of combining the advantages of global and local searches have been exploited in both the MDO architecture and in the selected and self developed optimization methodologies. Those have been compared according to computational efficiency and performance criteria. Results have been critically analyzed to identify the most suitable optimization approach for the targeted MDO problem

Modelling the Eddy Pattern in the harbour of Zeebrugge

Hydrodynamic

Optimizing the performance of complex engineering systems aided by artificial neural networks

In the first problem Polyetherimide graphene nanoplatelets papers (PEIGNP) were tested with different graphene loadings varying from 0-97 weight percent (WT%). The resulting stress-strain curves were utilized to develop two ANN models. Stress-controlled and strain-controlled models. Both models shoan excellent correlation to the experimental. Several Mechanical properties were calculated from the predicted stress-strain curves namely; toughness maximum strength maximum strain and maximum tangent modulus. Both models captured the same overall behavior of the PEIGNP composite. However the strain-controlled model was found to predict lower stress than the stress-controlled model. Finally a Graphical User Interface (GUI) was developed to aid in future use of the developed material. In the second problem a comprehensive investigation is performed to study the behavior of earthen embankments during an overtopping event. Due to experimental limitations numerical simulations are performed utilizing multi-phase Smoothed Particle Hydrodynamics (SPH) to study the post-failure behavior of the simulated embankments. This technique is validated by modeling different experiments focusing on various aspects of soil behavior such as; failure mechanism and seepage flow. Two hundred forty simulations are performed for different soil properties and embankment geometries. Embankment geometry consists of the side slope and height. The embankment slope range considered between 1.2:1 – 3:1 (H:V). And the height range is between 3-15 m. While the soil is divided into two sections; embankment and foundation soil. Four different soil types were considered for the embankment soil and five for the foundation soil. Many failure parameters were studied including; failure mode peak discharge Breach percent and initiation time and foundation erosion. Eight ANN models were developed to predict these failure parameters. The developed models shoan excellent correlation to the numerical simulations. Finally an EXCEL based GUI was designed to simplify the use of the developed models. Performance-based approach for material design risk assessment and emergency planning is utilized in this research. Artificial Neural Network (ANN) technique is employed to analyze and optimize two engineering problems; characterizing the stress-strain behavior of graphene nanocomposites and predicting earthen embankment failure due to overtopping. In the first application the optimization is based on experimental data and in the second application it is based on numerical data

강화된 친환경 화학 공정의 타당성 개선을 위한 시뮬레이션 기반 연구

학위논문(박사) -- 서울대학교대학원 : 공과대학 화학생물공학부(에너지환경 화학융합기술전공), 2021.8. 이종민.Technologies to mitigate risks from climate change have made significant advances in both research academia and industry. However, most advanced techniques were still considered only in the lab-scale experience. Moreover, the process intensification development during the process synthesis is in its incipient stages. To promote the application of a novel process technique to an eco-friendly process, the process feasibility of economy or operation should be considered. In this thesis, simulation-based framework to improve feasibility of intensified chemical processes, which are suggested under limited experimental conditions, is proposed. To solve the feasibility problem derived from the characteristics of process intensification, which is mainly developed by the numerous experiments rather than derived from the theoretical verification, the digital twin technology, which is developed to simulate various situations by modeling the reactor and process, is implemented. In addition, the framework, including the procedures from verification or validation of developed digital twin model to feasibility study and improvement of economic and operational feasibility, is proposed. First, intensified eco-friendly processes such as the biodiesel production process and carbon capture and utilization process were simulated, and comparative study and optimization were conducted to improve the economic or operational feasibility of that processes. As an example of applying the procedure to verify and to improve the economic feasibility, the economic feasibility study on the intensified biodiesel production process is implemented to increase the profitability of the biodiesel production process by reducing the process units, enhancing biodiesel quality, and reducing the raw material cost. As an example of applying the procedure to verify and to improve the operational feasibility, the modeling and validation of the semi-continuous carbonation process are implemented to estimate the overall CO2 removal efficiency during the operation and when the reaction ends. Using the developed process model, the operational feasibility of the semi-continuous carbonation process is verified and the optimization algorithms is adopted to obtain the optimal operation recipes. For the effective operational feasibility improvement, two new operation recipes were suggested and optimized via Bayesian optimization. Consequently, in order to verify and improve the applicability of the newly proposed intensified process, a methodology is proposed including the process modeling, which is conducted using laboratory-scale experimental data for the reaction kinetic studies, economic analysis, sensitivity analysis, and comparative study. In addition, the process modeling and optimization, using pilot-scale operation data, are carried out. Especially, the operational feasibility of semi-continuous carbonation process is effectively improved by proposing new operation recipe as well as adopting the digital twin model to the Black-box optimization method. In this thesis, a framework, improving economic/operational feasibility of newly proposed intensified chemical processes with two different experimental data depending on the purpose, is developed.기후 변화로 인한 위험들을 완화하는 기술들은 학술 분야와 산업 모두에서 상당한 발전을 이루었다. 그러나 대부분의 진보된 기술들은 여전히 실험실 규모의 실험에서만 고려되고 있다. 더욱이, 공정 합성 과정에서의 공정 강화 개발은 초기 단계에 머물러있다. 새로운 공정 기술들을 친환경 공정에 적용하는 것을 촉진시키기 위해서는, 공정의 경제성 또는 운전 타당성을 고려해야 한다. 본 학위논문에서는 제한된 실험 조건 하에서 제안된, 강화된 친환경 공정의 시뮬레이션 기반 타당성 개선 방법론을 제시하였다. 이론적인 검증을 통한 공정 강화가 아닌 수많은 실험을 통해 제안되는 공정 강화의 방식에서 파생되는 타당성 검증에 대한 문제를 해결하고자, 공정 및 반응기의 모델을 구축하고 다양한 상황을 모사하는 디지털 트윈 기술을 구현하였다. 또한, 구축된 디지털 트윈 모델의 검증부터, 강화된 공정의 경제적 타당성 및 운전 타당성 검증 및 개선까지의 일련의 과정들을 포함하는 방법론을 제시하였다. 먼저, 바이오디젤 생산 공정과 탄소 포집 및 활용 공정과 같은 강화된 친환경 공정을 시뮬레이션하고, 해당 공정의 경제적 타당성 또는 운전 타당성을 개선하기 위해 비교 연구 및 최적화를 수행하였다. 경제적 타당성 검증 방법론을 적용한 한가지 예제로써, 공정 유닛을 줄이고, 바이오디젤 품질 향상 및 원재료 비용을 감소시킴으로써 바이오디젤 생산 공정의 수익성을 증가시키는 강화된 바이오디젤 생산 공정의 경제적 타당성 연구를 수행하였다. 운전 타당성 검증 방법론을 적용한 한가지 예제로써, 반연속식 탄산화 공정의 운전 중 전체 이산화탄소 제거 효율과 반응 종료 시기를 추정하기 위해 시뮬레이션 기반 모델링 및 구축된 모델의 검증을 수행하였다. 구축된 시뮬레이션 기반 모델을 이용하여, 반연속식 탄산화 공정의 운전 타당성을 확인하고 최적의 운전 레시피를 얻기 위해 최적화 알고리즘에 적용하였다. 효과적인 반연속식 탄산화 공정의 운영 타당성 개선을 위해 두개의 새로운 운전 레시피를 제시하였고, 베이지안 최적화 기법을 이용하여 최적화하였다. 결론적으로, 반응식 및 반응 계수 연구를 위한 실험실 규모의 실험 데이터를 활용하여 공정 모델을 구축하고, 경제성 분석, 민감도 분석, 비교 분석을 통해 새로 제안된 강화된 공정의 현업에의 적용 가능성을 검증하고 개선시키는 방법론을 제안하였다. 또한, 실제 현업에 적용되는 크기의 반응기를 가진 중간 규모의 실험 데이터를 활용하여 공정 모델을 구축하고 최적화하였다. 특히, 반연속식 공정의 새로운 운전 방식을 제안함과 동시에 구축된 디지털 트윈 모델에 블랙박스 (Black-box) 최적화 기법을 적용하여 제안된 반연속식 친환경 공정의 운전 타당성을 효과적으로 개선할 수 있었다. 본 학위논문에서는 목적에 따라 다른 두 가지의 실험 결과를 이용하여, 새롭게 제안된 강화된 친환경 공정의 경제적 또는 운전 타당성 검증 및 개선을 위한 방법론을 제시하였다.Chapter 1 1 Introduction 1 1.1 Research motivation 1 1.2 Target process descriptions 4 1.2.1 Biodiesel production process 4 1.2.2 Aqueous mineral carbonation process 6 1.3 Outline of the thesis 8 1.4 Associated publications 8 Chapter 2 9 Economic feasibility study on biodiesel production process 9 2.1 Introduction 9 2.2 Reaction kinetics 13 2.3 Process simulation 15 2.3.1 Material and thermodynamic model 18 2.3.2 Assumptions 22 2.3.3 SC PFR 22 2.3.4 Cu-based PBR 26 2.3.5 Pd-based PBR 30 2.4 Economic analysis 33 2.4.1 Total capital investment 37 2.4.2 Total manufacturing cost 39 2.4.3 Sensitivity analysis 41 2.5 Summary 46 Chapter 3 48 Modeling and validation of pilot-scale aqueous mineral carbonation process 48 3.1 Introduction 48 3.2 Reaction kinetics 48 3.2.1 Calcium hydroxide dissolution in water 49 3.2.2 Mass transfer of CO2 gas into the alkali solution 50 3.2.3 Ionic reactions and precipitation of calcium carbonate 53 3.3 Process design and modeling 56 3.3.1 Assumptions 56 3.3.2 Reactor modelling 57 3.3.3 Sequence of reactant replenishment 59 3.3.4 ACM model validation 63 3.4 Summary 65 Chapter 4 66 Bayesian optimization approach to semi-continuous carbonation process operation recipe 66 4.1 Introduction 66 4.2 Problem descriptions 68 4.3 Multi-objective Bayesian optimization algorithm 76 4.4 Results and discussion 84 4.5 Summary 91 Chapter 5 Concluding remarks 94 References 97 Abstract in Korean (국문초록) 106박