The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of novel and cost-effective combustion technologies and the minimization of environmental concerns at industrial scale. CFD simulations facilitate scaling-up procedures that otherwise would be complicated by strong interactions between reaction kinetics, turbulence and heat transfer. CFD calculations can be applied directly at the industrial scale of interest, thus avoiding scaling-up from lab-scale experiments. However, this advantage can only be obtained if CFD tools are quantitatively predictive and trusted as so. Despite the improvements in the computational capability, the implementation of detailed physical and chemical models in CFD simulations can still be prohibitive for real combustors, which require large computational grids and therefore significant computational efforts. Advanced simulation approaches like Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) guarantee higher fidelity in computational modeling of combustion at, unfortunately, increased computational cost. However, with adequate, reduced, and cost-effective modeling of physical phenomena, such as chemical kinetics and turbulence-chemistry interactions, and state of the art computing, LES will be the tool of choice to describe combustion processes at industrial scale accurately. Therefore, the development of reduced physics and chemistry models with quantified model-form uncertainty is needed to overcome the challenges of performing LES of industrial systems. Reduced-order models must reproduce the main features of the corresponding detailed models. They feature predictivity and capability of bridging scales when validated against a broad range of experiments and targeted by Validation and Uncertainty Quantification (V/UQ) procedures. In this work, V/UQ approaches are applied for reduced-order modeling of pulverized coal devolatilization and subsequent char oxidation, and furthermore for modeling NOx emissions in combustion systems.For coal devolatilization, a benchmark of the Single First-Order Reaction (SFOR) model was performed concerning the accuracy of the prediction of volatile yield. Different SFOR models were implemented and validated against experimental data coming from tests performed in an entrained flow reactor at oxy-conditions, to shed light on their drawbacks and benefits. SFOR models were chosen because of their simplicity: they can be easily included in CFD codes and are very appealing in the perspective of LES of pulverized coal combustion burners. The calibration of kinetic parameters was required to allow the investigated SFOR model to be predictive and reliable for different heating rates, hold temperatures and coal types. A comparison of several calibration approaches was performed to determine if one-step models can be adaptive and able to bridge scales, without losing accuracy, and to select the calibration method to employ for wider ranges of coal rank and operating conditions. The analysis pointed out that the main drawback of the SFOR models is the assumption of a constant ultimate volatile yield, equal to the value from the coal proximate analysis. To overcome this drawback, a yield model, i.e. a simple functional form that relates the ultimate volatile yield to the particle temperature, was proposed. The model depends on two parameters that have a certain degree of uncertainty. The performances of the yield model were assessed using a collaboration of experiments and simulations of a pilot-scale entrained flow reactor. A consistency analysis, based on the Bound-to-Bound Data Collaboration (B2B-DC) approach, and a Bayesian method, based on Gaussian Process Regression (GPR), were employed for the investigation of experiments and simulations. In Bound-to- Bound Data Collaboration the model output, evaluated at specified values of the model parameters, is compared with the experimental data: if the prediction of the model falls within the experimental uncertainty, the corresponding parameter values would be included in the so-called feasible set. The existence of a non-empty feasible set signifies consistency between the experiments and the simulations, i.e. model-data agreement. Consistency was indeed found when a relative error of 19% for all the experimental data was applied. Hence, a feasible set of the two SFOR model parameters was provided. A posterior state of knowledge, indicating potential model forms that could be explored in yield modeling, was obtained by Gaussian Process Regression. The model form evaluated through the consistency analysis is included within the posterior derived from GPR, indicating that it can satisfactorily match the experimental data and provide reliable estimation in almost every range of temperatures. CFD simulations were carried out using the proposed yield model with first-order kinetics, as in the SFOR model. Results showed promising agreement between predicted and experimental conversion for all the investigated cases.Regarding char combustion modeling, the consistency analysis has been applied to validate a reduced-order model and quantify the uncertainty in the prediction of char conversion. The model capability to address heterogeneous reaction between char carbon and O2, CO2 and H2O reagents, mass transport of species in the particle boundary layer, pore diffusion, and internal surface area changes was assessed by comparison with a large number of experiments performed in air and oxy-coal conditions. Different model forms had been considered, with an increasing degree of complexity, until consistency between model outputs and experimental results was reached. Rather than performing forward propagation of the model-form uncertainty on the predictions, the reduction of the parameter uncertainty of a selected model form was pursued and eventually achieved. The resulting 11-dimensional feasible set of model parameters allows the model to predict the experimental data within almost ±10% uncertainty. Due to the high dimensionality of the problem, the employed surrogate models resulted in considerable fitting errors, which led to a spoiled UQ inverse problem. Different strategies were taken to reduce the discrepancy between the surrogate outputs and the corresponding predictions of the simulation model, in the frameworks of constrained optimization and Bayesian inference. Both strategies succeeded in reducing the fitting errors and also resulted in a least-squares estimate for the simulation model. The variety of experimental gas environments ensured the validity of the consistent reduced model for both conventional and oxy-conditions, overcoming the differences in mass transport and kinetics observed in several experimental campaigns.The V/UQ-aided modeling of coal devolatilization and char combustion was done in the framework of the Predictive Science Academic Alliance Program II (PSAAP-II) funded by the US Department of Energy. One of the final goals of PSAAP-II is to develop high-fidelity simulation tools that ensure 5% uncertainty in the incident heat flux predictions inside a 1.2GW Ultra-Super-Critical (USC) coal-fired boiler. The 5% target refers to the expected predictivity of the full-scale simulation without considering the uncertainty in the scenario parameters. The data-driven approaches used in this Thesis helped to improve the predictivity of the investigated models and made them suitable for LES of the 1.2GW USC coal-fired boiler. Moreover, they are suitable for scale-bridging modeling of similar multi-phase processes involved in the conversion of solid renewable sources, such as biomass.In the final part of the Thesis, the sensitivity to finite-rate chemistry combustion models and kinetic mechanisms on the prediction of NO emissions was assessed. Moreover, the forward propagation of the uncertainty in the kinetics of the NNH route (included in the NOx chemistry) on the predictions of NO was investigated to reveal the current state of the art of kinetic modeling of NOx formation. The analysis was carried out on a case where NOx formation comes from various formation routes, both conventional (thermal and prompt) and unconventional ones. To this end, a lab-scale combustion system working in Moderate and Intense Low-oxygen Dilution (MILD) conditions was selected. The results showed considerable sensitivity of the NO emissions to the uncertain kinetic parameters of the rate-limiting reactions of the NNH pathway when a detailed kinetic mechanism is used. The analysis also pointed out that the use of one-step global rate schemes for the NO formation pathways, necessary when a skeletal kinetic mechanism is employed, lacks the required chemical accuracy and dims the importance of the NNH pathway in this combustion regime. An engineering modification of the finite-rate combustion model was proposed to account for the different chemical time scales of the fuel-oxidizer reactions and NOx formation pathways. It showed an equivalent impact on the emissions of NO than the uncertainty in the kinetics of the NNH route. At the cost of introducing a small mass imbalance (of the order of ppm), the adjustment led to improved predictions of NO. The investigation established a possibility for the engineering modeling of NO formation in MILD combustion with a finite-rate chemistry combustion model that can incorporate a detailed mechanism at affordable computational costs. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

In this paper we describe an approach to generating low-order models of spiral inductors that accurately capture the dependence on both frequency and geometry (width and spacing) parameters. The approach is based on adapting a multiparameter Krylov-subspace based moment matching method to reducing an integral equation for the three dimensional electromagnetic behavior of the spiral inductor. The approach is demonstrated on a typical on-chip rectangular inductor. / Singapore-MIT Alliance (SMA)

In der vorliegenden Arbeit wird eine Prozedur zur Ordnungsreduktion von Finite Elemente Modellen mikromechanischer Struktur mit elektrostatischem Wirkprinzip entwickelt und analysiert. Hintergrund der Ordnungsreduktion ist eine Koordinatentransformation von lokalen Finite Elemente Koordinaten in globale Koordinaten. Die globalen Koordinaten des reduzierten Modells werden durch einige wenige Formfunktionen beschrieben. Damit wird das Makromodell nicht mehr durch lokale Knotenverschiebungen beschrieben, sondern durch globale Formfunktionen, welche die gesamte Deformation der Struktur beeinflussen. Es wird gezeigt, dass Eigenvektoren der linearisierten mechanischen Struktur einfache und effiziente Formfunktionen darstellen. Weiterhin kann diese Methode für bestimmte Nichtlinearitäten und für verschiedene in Mikrosystemen auftretende Lasten angewendet werden. Das Ergebnis sind Makromodelle, die über Klemmen in Systemsimulatoren eingebunden werden können, die Genauigkeiten einer Finite Elemente Analyse erreichen und für Systemsimulationen typische Laufzeitverhalten besitzen.

O estudo da dinâmica estrutural de risers oceânicos apresenta instigantes desafios aos pesquisadores da área da engenharia de estruturas, uma vez que os meios tradicionais de análises dinâmicas lineares nem sempre se ajustam às suas complexas particularidades. No atual estágio do desenvolvimento científico da área de engenharia de estruturas, a aplicação de técnicas de análise dinâmica não linear, dentro de determinadas hipóteses, mostra-se como uma das alternativas possíveis e viáveis à tradicional análise dinâmica linear. Com vistas a uma nova abordagem do problema, o presente trabalho adota uma metodologia de análise não linear dinâmica de risers oceânicos em configuração de lançamento de catenária, conjugada a uma técnica de processamento de Modelos de Ordem Reduzida para o estudo dos fenômenos dinâmicos manifestados por risers. Trata-se de um método de modelagem local, restrito à região de contato unilateral do riser com o solo, considerado este último um meio viscoelástico. Os resultados da aplicação desta metodologia são demonstrados nos estudos de caso apresentados com comparações com modelos numéricos (Método dos Elementos Finitos) e modelos físicos. / The dynamic study of offshore risers still demands large efforts from structural engineering researchers, since these systems may behave in a way that is not well modeled and understood using simply linear dynamic theories. Nevertheless, the current development stage of non linear dynamic theories gives hope that their use for the analyses of such systems can be of great value, even though, this must be carefully done specially by the analyst. The present work refers to a non linear dynamic methodology application to offshore risers, particularly steel catenary risers, by a technique known as reduced-order modeling, in the study of dynamic phenomena that these structures may present. The model is local, which means that it represents the touch-down zone of the riser-soil system. The soil modeling was presumed to be viscoelastic. The results obtained in case studies are compared with those from numerical (Finite Element Method) and small scale physical models.

In this thesis, the method of Proper Orthogonal Decomposition (POD) is implemented to construct approximate, reduced order models (ROM) of mesh movement methods. Three mesh movement algorithms are implemented and comparatively evaluated, namely radial basis function interpolation, mesh optimization and elastic deformation. POD models of the mesh movement algorithms are constructed using a series of system observations, or snapshots of a given mesh for a set of boundary deformations. The scalar expansion coefficients for the POD basis modes are computed in three different ways, through coefficient optimization, Galerkin projection of the governing set of equations and coefficient interpolation. It is found that using only coefficient interpolation yields mesh movement models that accurately approximates the full order mesh movement, with CPU cost savings in excess of 99%. We further introduce a novel training procedure whereby the POD models are generated in a fully automated fashion. The technology is applicable to any mesh movement method and enables potential reductions of up to four orders of magnitude in mesh movement related costs. The proposed model can be implemented without having to pre-train the POD model, to any fluid-structure interaction code with an existing mesh movement scheme. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Mechanical and Aeronautical Engineering / unrestricted

The number of electrical machines used in modern road-vehicles is continuously increasing to meet regulatory requirements regarding safety and efficiency, as well as consumer expectations in terms of comfort. For auxiliary applications, such as cooling fan or pumps, permanent-magnet synchronous machines (PMSMs) are extensively used owing to their high power density. This thesis focuses on the modelling aspects of PMSMs, with a particular focus on finite-element and reduced-order models to be used in system-level simulations. 2-D and 3-D parametric finite-element (FE) models are developed, allowing to compute irreversible demagnetization in addition to the standard quantities such as torque, back electromotive force and flux-linkages. The effects of magnet overhang on the performance of an interior PMSM is briefly discussed. Using the FE model, a reduced-order lookup-table (LUT) based electromagnetic model, having similar accuracy as FE analysis, is then developed. Coupled to a mechanical state-space representation obtained from a modal FE analysis, the final model allows to compute electromagnetic induced vibrations under pulse width modulation supply. The validation of the complete workflow is carried out on a 12slot-10pole PMSM used to drive a cooling fan. After fitting the damping coefficient in the structural state-space model, the results are in agreement with the experimental results. Due to the usage of LUTs, the simulation time is low compared to a pure FE analysis. This allows the model to be used to optimize low noise control strategies. To conclude this thesis, the parametric FE model is used in an optimization routine to minimize the cost and vibrations of the motor, whilst satisfying the working points. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Thermal energy storage (TES) modules are specifically designed to respond to transient thermal loading. Their dynamic response depends on the overall structure of the module, including module geometry and dimensions, the internal spatial distribution of phase change material (PCM) and conductive heat-spreading elements, and the thermophysical properties of the different materials composing the module. However, due to the complexity of analyzing a system’s dynamic thermal response to transient input signals, optimal design of a TES module for a particular application is challenging. Conventional design approaches are limited by (1) the computational cost associated with high fidelity simulation of heat transfer in nonlinear systems undergoing a phase transition and (2) the lack of model integration with robust optimization tools. To overcome these challenges, I derive reduced-order dynamic models of two different metal-PCM composite TES modules and validate them against a high fidelity CFD model. Through simulation and validation of both turbulent and laminar flow cases, I demonstrate the accuracy of the reduced-order models in predicting, both spatially and temporally, the evolution of the dynamic model states and other system variables of interest, such as PCM melt fraction. The validated models are used to conduct univariate and bivariate parametric studies to understand the effects of various design parameters on different performance metrics. Finally, a case study is presented in which the models are used to conduct detailed design optimization for the two HX geometries.

Recent advances in manufacturing and growing concerns on the sustainability of aviation environment have led to a remarkable interest in electrical unmanned aerial systems (UASs) in the past decade. Among various UAS types, the newly designed quadrotor biplane tailsitter class is capable of delivering a wide range of civilian and military tasks, relying on its Vertical Take-Off and Landing (VTOL) capability as well as great maneuverability. Nevertheless, as such UASs employ rotors to generate thrust, and wings to generate lift, and operate at less-understood low to mid-Reynolds flow regime, they experience complicated flight aerodynamics with a noise generation mechanism which is different from common aircrafts. The present work aims at addressing this knowledge gap by studying the aerodynamics and aeroacoustics of a UAS of this type designed by the Army Research Lab. High-fidelity computational fluid dynamics (CFD) simulations are carried out for a wide range of operating conditions to understand the physics involved in the UAS aerodynamics and characterize its performance. Relying on the CFD results, a physics-informed reduced order model (ROM) is developed based on machine learning algorithms, to predict the propellers effects on the wings and calculate the dominant loads. The results of this study indicate that the UAS aerodynamics is significantly influenced by the propeller-wing interaction, which makes it challenging to estimate the loads by classic methods. The proposed physics-informed ROM shows a promising performance based on its computational cost and accuracy. Additionally, it is found that the aeroacoustics of the UAS is ruled by a two-way mechanism through which the propellers and the structure impose unsteadiness on each other.

No description available.

In aeromechanical design one of the major rules is to operate under High Cyclic Fatigue (HCF) margins and away from flutter. The level of dynamic excitations and risk of HCF can be estimated by performing forced response analyses from blade row interaction forces or Low Engine Order (LEO) excitation mechanisms. On the other hand, flutter stability prediction can be assessed by calculation of aerodynamic damping forces due to blade motion. In order to include these analyses as regular practices in an industrial aeromechanical design process, interaction between the fields of fluid and structural dynamics must be established in a rather simple yet accurate manner. Effects such as aerodynamic and structural mistuning should also be taken into account where parametric and probabilistic studies take an important role. The present work presents the development and validation of a numerical tool for aeromechanical design. The tool aims to integrate in a standard and simple manner regular aeromechanical analysis such as forced response analysis and aerodynamic damping analysis of bladed disks. Mistuning influence on forced response and aerodynamic damping is assessed by implementing existing model order reduction techniques in order to decrease the computational effort and assess results in an industrially applicable time frame.  The synthesis program solves the interaction of structure and fluid from existing Finite Element Modeling (FEM) and Computational Fluid Dynamics (CFD) solvers inputs by including a mapping program which establishes the fluid and structure mesh compatibility. Blade row interaction harmonic forces and/or blade motion aerodynamic damping forces are inputs from unsteady fluid dynamic solvers whereas the geometry, mass and stiffness matrices of a blade alone or bladed disk sector are inputs from finite element solvers. Structural and aerodynamic damping is also considered. Structural mistuning is assessed by importing different sectors and any combinations of the full disk model can be achieved by using Reduced Order Model (ROM) techniques. Aerodynamic mistuning data can also be imported and its effects on the forced response and stability assessed. The tool is developed in such a way to allow iterative analysis in a simple manner, being possible to realize aerodynamically and structurally coupled analyses of industrial bladed disks. A new method for performing aerodynamic coupled forced response and stability analyses considering the interaction of different mode families has also been implemented. The method is based on the determination of the aerodynamic matrices by means of least square approximations and is here referred as the Multimode Least Square (MLS) method. The present work includes the program description and its applicability is assessed on a high pressure ratio transonic compressor blade and on a simple blisk. / QC 20110324 / Turbopower / AROMA