Membrane Distillation (MD) is an emerging sustainable desalination technique. While MD has many advantages and can be powered by solar thermal energy, its main drawback is the low water production rate. However, the MD process has not been fully optimized in terms of its manipulated and controlled variables. This is largely due to the lack of adequate dynamic models to study and simulate the process. In addition, MD is prone to membrane fouling, which is a fault that degrades the performance of the MD process. This work has three contributions to address these challenges. First, we derive a mathematical model of Direct Contact Membrane Distillation (DCMD), which is the building block for the next parts. Then, the proposed model is extended to account for membrane fouling and an observer-based fouling detection method is developed. Finally, various control strategies are implemented to optimize the performance of the DCMD solar-powered process. In part one, a reduced-order dynamic model of DCMD is developed based on lumped capacitance method and electrical analogy to thermal systems. The result is an electrical equivalent thermal network to the DCMD process, which is modeled by a system of nonlinear differential algebraic equations (DAEs). This model predicts the water-vapor flux and the temperature distribution along the module length. Experimental data is collected to validate the steady-state and dynamic responses of the proposed model, with great agreement demonstrated in both. The second part proposes an extension of the model to account for membrane fouling. An adaptive observer for DAE systems is developed and convergence proof is presented. A method for membrane fouling detection is then proposed based on adaptive observers. Simulation results demonstrate the performance of the membrane fouling detection method. Finally, an optimization problem is formulated to maximize the process efficiency of a solar-powered DCMD. The adapted method is known as Extremum Seeking (ES). A Newton-based ES is designed and the proposed model is used to accurately forecast the distilled water flux. Although good results are obtained with this method, a practical modification to the ES scheme is proposed to enhance the practical stability.

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.

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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

This dissertation contains work that addresses both theoretical and numerical aspects of reduced order models (ROMs). In an under-resolved regime, the classical Galerkin reduced order model (G-ROM) fails to yield accurate approximations. Thus, we propose a new ROM, the data-driven variational multiscale ROM (DD-VMS-ROM) built by adding a closure term to the G-ROM, aiming to increase the numerical accuracy of the ROM approximation without decreasing the computational efficiency. The closure term is constructed based on the variational multiscale framework. To model the closure term, we use data-driven modeling. In other words, by using the available data, we find ROM operators that approximate the closure term. To present the closure term's effect on the ROMs, we numerically compare the DD-VMS-ROM with other standard ROMs. In numerical experiments, we show that the DD-VMS-ROM is significantly more accurate than the standard ROMs. Furthermore, to understand the closure term's physical role, we present a theoretical and numerical investigation of the closure term's role in long-time integration. We theoretically prove and numerically show that there is energy exchange from the most energetic modes to the least energetic modes in closure terms in a long time averaging. One of the promising contributions of this dissertation is providing the numerical analysis of the data-driven closure model, which has not been studied before. At both the theoretical and the numerical levels, we investigate what conditions guarantee that the small difference between the data-driven closure model and the full order model (FOM) closure term implies that the approximated solution is close to the FOM solution. In other words, we perform theoretical and numerical investigations to show that the data-driven model is verifiable. Apart from studying the ROM closure problem, we also investigate the setting in which the G-ROM converges optimality. We explore the ROM error bounds' optimality by considering the difference quotients (DQs). We theoretically prove and numerically illustrate that both the ROM projection error and the ROM error are suboptimal without the DQs, and optimal if the DQs are used. / Doctor of Philosophy / In many realistic applications, obtaining an accurate approximation to a given problem can require a tremendous number of degrees of freedom. Solving these large systems of equations can take days or even weeks on standard computational platforms. Thus, lower-dimensional models, i.e., reduced order models (ROMs), are often used instead. The ROMs are computationally efficient and accurate when the underlying system has dominant and recurrent spatial structures. Our contribution to reduced order modeling is adding a data-driven correction term, which carries important information and yields better ROM approximations. This dissertation's theoretical and numerical results show that the new ROM equipped with a closure term yields more accurate approximations than the standard ROM.

Lithium ion (Li-ion) batteries have been identified as a promising solution to meet the increasing demands for alternative energy in electric vehicles (EVs) and hybrid electric vehicle (HEVs). This work describes experimental and numerical study of thermal management of battery module consisting of cylindrical Li-ion cells, with an emphasis on the use of active control to achieve optimal cooling performance with minimal parasitic power consumption. The major contribution from this work is the first experimental demonstration (based on our review of archival journal and conference literature) and the corresponding analysis of active thermal control of battery modules. The results suggest that the active control strategy, when combined with reciprocating cooling flow, can reduce the parasitic energy consumption and cooling flow amount substantially. Compared with results using passive control with unidirectional cooling flow, the parasitic energy consumption was reduced by about 80%. This contribution was achieved in three steps, which was detailed in this dissertation in chapters 2, 3, and 4, respectively. In the first step, an experimental facility and a corresponding CFD model were developed to capture the thermal behavior of multiple battery cells. Based on the experimental and CFD results, a reduced-order model (ROM) was then developed for active monitoring and control purposes. In the second step, the ROM was parameterized and an observer-based control strategy was developed to control the core temperature of battery cells. Finally, based on the experimental facility and the ROM model, the active control of a battery module was demonstrated. Each of these steps represents an important facet of the thermal management problem, and it is expected that the results and specifics documented in this dissertation lay the groundwork to facilitate further study. / Ph. D.

This thesis describes several approaches for stabilizing POD-ROMs (that is, reduced order models based on basis functions derived from the proper orthogonal decomposition) for both the CDR (convection-diffusion-reaction) equation and the NSEs (Navier-Stokes equations). Stabilization is necessary because standard POD-ROMs of convection-dominated problems usually display numerical instabilities. The first stabilized ROM investigated is a streamline-upwind Petrov-Galerkin ROM (SUPG-ROM). I prove error estimates for the SUPG-ROM and derive optimal scalings for the stabilization parameter. I test the SUPG-ROM with the optimal parameter in the numerical simulation of a convection-dominated CDR problem. The SUPG-ROM yields more accurate results than the standard Galerkin ROM (G-ROM) by eliminating the inherent numerical artifacts (noise) in the data and dampening spurious oscillations. I next propose two regularized ROMs (Reg-ROMs) based on ideas from large eddy simulation and turbulence theory: the Leray ROM (L-ROM) and the evolve-then-filter ROM (EF-ROM). Both Reg-ROMs use explicit POD spatial filtering to regularize (smooth) some of the terms in the standard G-ROM. I propose two different POD spatial filters: one based on the POD projection and a novel POD differential filter. These two new Reg-ROMs and the two spatial filters are investigated in the numerical simulation of the three-dimensional flow past a circular cylinder problem at Re = 100. The numerical results show that EF-ROM-DF is the most accurate Reg-ROM and filter combination and the differential filter generally yields better results than the projection filter. The Reg-ROMs perform significantly better than the standard G-ROM and decrease the CPU time (compared against the direct numerical simulation) by orders of magnitude (from about four days to four minutes). / Ph. D.

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.

<p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p> / Turbopower / AROMA

Le comportement dynamique de structures complexes, comme les alternateurs, doit être maîtrisé afin d’en garantir un fonctionnement fiable. Cependant, la modélisation comporte de nombreuses incertitudes rendant délicates la prédiction du comportement vibratoire. Ces travaux de recherche ont pour objectif de fournir des outils d’aide à la décision afin de faciliter la prise de décision rapide suite au redémarrage d’alternateurs. Basé sur la théorie info-gap, un premier outil d’aide à la décision est proposé : il a pour objectif d’évaluer la robustesse de réponses dynamiques vis-à-vis d’un modèle modal incertain. Nous avons également étudié comment de l’information nouvelle peut être intégrée au modèle d’incertitude pour améliorer sa représentativité à la réalité.Une expansion par l’erreur en relation de comportement étendue de modes propres identifiés permet ensuite d’enrichir la représentativité du modèle numérique fournissant ainsi un modèle qualifié d’hybride et permettant d’évaluer les niveaux de réponse. Comme la modélisation comporte de nombreuses méconnaissances, nous avons proposé le procédé d’expansion robuste dont l’objectif est d’obtenir des vecteurs étendus robustes. En présence de méconnaissances sévères, nous montrons enfin qu’il est préférable de calibrer un modèle en maximisant la robustesse vis-à-vis des incertitudes plutôt qu’en maximisant uniquement la fidélité vis-à-vis des données. Couplée à des techniques de réduction de modèle et de construction de méta modèles,nous appliquons cette démarche à une structure de complexité industrielle représentative du contexte industriel. / The complex structural dynamic behavior of alternator must be well understood in order to insuretheir reliable and safe operation. The numerical model is however difficult to construct mainlydue to the presence of a high level of uncertainty. The objective of this work is to providedecision support tools in order to assess the vibratory levels in operation before to restart thealternator. Based on info-gap theory, a first decision support tool is proposed: the objective hereis to assess the robustness of the dynamical response to the uncertain modal model. Based on realdata, the calibration of an info-gap model of uncertainty is also proposed in order to enhance itsfidelity to reality. Then, the extended constitutive relation error is used to expand identified modeshapes which are used to assess the vibratory levels. The robust expansion process is proposed inorder to obtain robust expanded mode shapes to parametric uncertainties. In presence of lack-ofknowledge,the trade-off between fidelity-to-data and robustness-to-uncertainties which expressesthat robustness improves as fidelity deteriorates is emphasized on an industrial structure by usingboth reduced order model and surrogate model techniques.