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Computation for Design and Optimization - Master's degree

Mostrando recursos 1 - 20 de 173

  1. Prediction of velocity distribution from the statistics of pore structure in 3D porous media via high-fidelity pore-scale simulation

    AlAdwani, Mohammad S. Kh. F. Sh
    Fluid flow and particle transport through porous media are determined by the geometry of the host medium itself. Despite the fundamental importance of the velocity distribution in controlling early-time and late-time transport properties (e.g., early breakthrough and superdiffusive spreading), direct relations linking velocity distribution with the statistics of pore structure in 3D porous media have not been established yet. High velocities are controlled by the formation of channels, while low velocities are dominated by stagnation zones. Recent studies have proposed phenomenological models for the distribution of high velocities including stretched exponential and power-exponential distributions but without an underlying mechanistic or...

  2. Modeling flow encountering abrupt topography using hybridizable discontinuous Galerkin projection methods

    Vo, Johnathan Hiep
    In this work novel high-order hybridizable discontinuous Galerkin (HDG) projection methods are further developed for ocean dynamics and geophysical fluid predictions. We investigate the effects of the HDG stabilization parameter for both the momentum equation as well as tracer diffusion. We also make a correction to our singularity treatment algorithm for nailing down a numerically consistent and unique solution to the pressure Poisson equation with homogeneous Neumann boundary conditions everywhere along the boundary. Extensive numerical results using physically realistic ocean flows are presented to verify the HDG projection methods, including the formation of internal wave beams over a shallow but...

  3. Value of heterogeneous information in stochastically congestible facilities

    Khan, Zaid S. (Zaid Saeed)
    This thesis studies the effects of heterogeneous information on traffic equilibria and the resulting travel costs (both individual and social) when commuters make departure time choices to cross an unreliable bottleneck link. Increasing adoption and improved predictive abilities of Traveler Information Systems (TIS) enable commuters to plan their trips; however, there are inherent heterogeneities in information access and TIS accuracies, which can significantly affect commuters' choices and the equilibrium level of congestion. Our work addresses the open problem raised in Arnott et al. (1991) about the need to consider asymmetrically informed commuters in the bottleneck model of traffic congestion. We...

  4. A quantitative approach to patient risk assessment and safety optimization in intensive care units

    Hu, Yiqun, S.M. Massachusetts Institute of Technology
    Health care quality and patient safety has gained an increasing amount of attention for the past two decades. The quality of care nowadays does not only refer to successful cure of diseases for patients, but a much broader concept involving health care community, inter-relationships among care providers, patients and family, efficiency, humanity and satisfaction. The intensive care units (ICU) typically admit and care for the most clinically complex patients. While much effort has been put into patient safety improvement, the critical care system still continuous to see many human errors occur each day, despite the fact that people who work...

  5. Loss pattern recognition and profitability prediction for insurers through machine learning

    Wang, Ziyu, S.M. Massachusetts Institute of Technology
    For an insurance company, assessing risk exposure for Property Damage (PD), and Business Interruption (BI) for large commercial clients is difficult because of the heterogeneity of that exposure, within a single client (account), and between different divisions, and regions, where the client is active. Traditional risk assessment models attempt to scale up the single location approach used in personal lines: A large amount of data is collected to profile a sample of the locations and based on this information the risk is then inferred and somewhat subjectively assessed for the whole account. The assumption is that the risk characteristics at...

  6. Loss pattern recognition and profitability prediction for insurers through machine learning

    Wang, Ziyu, S.M. Massachusetts Institute of Technology
    For an insurance company, assessing risk exposure for Property Damage (PD), and Business Interruption (BI) for large commercial clients is difficult because of the heterogeneity of that exposure, within a single client (account), and between different divisions, and regions, where the client is active. Traditional risk assessment models attempt to scale up the single location approach used in personal lines: A large amount of data is collected to profile a sample of the locations and based on this information the risk is then inferred and somewhat subjectively assessed for the whole account. The assumption is that the risk characteristics at...

  7. Convergence of regulatory mutations into oncogenic pathways across multiple tumor types

    Murugadoss, Karthik
    Cancer sequencing efforts have largely focused on profiling somatic variants in the protein-coding genome and characterizing their functional impact. In this study, we develop a computational pipeline to identify non-coding mutational drivers across multiple tumor types. We describe the non-coding mutational profiles of 854 samples, spread across 15 tumor types, in the context of their respective tissue type-specific reference epigenomes, using recent pan-cancer whole-genome sequencing data. We develop a novel method to detect significantly recurrent non-coding mutations by reestimating the background mutation density while adjusting for epigenomic covariates. Existing databases on enhancer-gene links allow us to capture the convergence of...

  8. Convergence of regulatory mutations into oncogenic pathways across multiple tumor types

    Murugadoss, Karthik
    Cancer sequencing efforts have largely focused on profiling somatic variants in the protein-coding genome and characterizing their functional impact. In this study, we develop a computational pipeline to identify non-coding mutational drivers across multiple tumor types. We describe the non-coding mutational profiles of 854 samples, spread across 15 tumor types, in the context of their respective tissue type-specific reference epigenomes, using recent pan-cancer whole-genome sequencing data. We develop a novel method to detect significantly recurrent non-coding mutations by reestimating the background mutation density while adjusting for epigenomic covariates. Existing databases on enhancer-gene links allow us to capture the convergence of...

  9. The (travel) times they are a changing : a computational framework for the diagnosis of non-alcoholic fatty liver disease (NAFLD)

    Benjamin, Alex (Alex Robert)
    We propose and validate a non-invasive method to diagnose Non-Alcoholic Fatty Liver Disease (NAFLD). The proposed method is based on two fundamental concepts: 1) the speed of sound in a fatty liver is lower than that in a healthy liver and 2) the quality of an ultrasound image is maximized when the beamforming speed of sound used in image formation matches the speed in the medium under examination. The proposed method uses image brightness and sharpness as quantitative image-quality metrics to predict the true sound speed and capture the effects of fat infiltration, while accounting for the transmission through subcutaneous...

  10. The (travel) times they are a changing : a computational framework for the diagnosis of non-alcoholic fatty liver disease (NAFLD)

    Benjamin, Alex (Alex Robert)
    We propose and validate a non-invasive method to diagnose Non-Alcoholic Fatty Liver Disease (NAFLD). The proposed method is based on two fundamental concepts: 1) the speed of sound in a fatty liver is lower than that in a healthy liver and 2) the quality of an ultrasound image is maximized when the beamforming speed of sound used in image formation matches the speed in the medium under examination. The proposed method uses image brightness and sharpness as quantitative image-quality metrics to predict the true sound speed and capture the effects of fat infiltration, while accounting for the transmission through subcutaneous...

  11. Silence of the lamb waves

    Benjamin, Rishon Robert
    Roll-to-Roll (R2R) manufacturing has seen great interest in the recent decade due to the proliferation of personalized and wearable devices for monitoring a variety of biometrics. Given the sensitive nature of the potential applications of these sensors, the throughput of manufacturing due to increased demand, and the scale of the electrical components being manufactured, R2R flexible electronics manufacturing technologies require new sensing and measurement capabilities for defect detection and process control. The work presented herein investigates the use of ultrasound, specifically Lamb and longitudinal waves, as a sensing modality and measurement technique for thin film R2R manufacturing substrates. Contact (transducer-based)...

  12. Silence of the lamb waves

    Benjamin, Rishon Robert
    Roll-to-Roll (R2R) manufacturing has seen great interest in the recent decade due to the proliferation of personalized and wearable devices for monitoring a variety of biometrics. Given the sensitive nature of the potential applications of these sensors, the throughput of manufacturing due to increased demand, and the scale of the electrical components being manufactured, R2R flexible electronics manufacturing technologies require new sensing and measurement capabilities for defect detection and process control. The work presented herein investigates the use of ultrasound, specifically Lamb and longitudinal waves, as a sensing modality and measurement technique for thin film R2R manufacturing substrates. Contact (transducer-based)...

  13. Computational design and optimization of infrastructure policy in water and agriculture

    Alhassan, Abdulaziz (Abdulaziz Abdulrahman)
    Investments in infrastructure tend to be associated with high capital costs, creating a necessity for tools to prioritize and evaluate different infrastructure investment options. This thesis provides a survey of computational tools, and their applicability in fine-tuning infrastructure policy levers, prioritizing among different infrastructure investment options and finding optimal sizing parameters to achieve a certain objective. First, we explore the usability of Monti Carlo simulations to project future water demand in Saudi Arabia and then, we use the outcome as an input to a Mixed Integer Linear Program (MILP) that investigates the feasibility of seawater desalination for agricultural irrigation under...

  14. Computational design and optimization of infrastructure policy in water and agriculture

    Alhassan, Abdulaziz (Abdulaziz Abdulrahman)
    Investments in infrastructure tend to be associated with high capital costs, creating a necessity for tools to prioritize and evaluate different infrastructure investment options. This thesis provides a survey of computational tools, and their applicability in fine-tuning infrastructure policy levers, prioritizing among different infrastructure investment options and finding optimal sizing parameters to achieve a certain objective. First, we explore the usability of Monti Carlo simulations to project future water demand in Saudi Arabia and then, we use the outcome as an input to a Mixed Integer Linear Program (MILP) that investigates the feasibility of seawater desalination for agricultural irrigation under...

  15. Optimal approximations of coupling in multidisciplinary models

    Santos Baptista, Ricardo Miguel
    Design of complex engineering systems requires coupled analyses of the multiple disciplines affecting system performance. The coupling among disciplines typically contributes significantly to the computational cost of analyzing a system, and can become particularly burdensome when coupled analyses are embedded within a design or optimization loop. In many cases, disciplines may be weakly coupled, so that some of the coupling or interaction terms can be neglected without significantly impacting the accuracy of the system output. However, typical practice derives such approximations in an ad hoc manner using expert opinion and domain experience. In this thesis, we propose a new approach...

  16. Optimal approximations of coupling in multidisciplinary models

    Santos Baptista, Ricardo Miguel
    Design of complex engineering systems requires coupled analyses of the multiple disciplines affecting system performance. The coupling among disciplines typically contributes significantly to the computational cost of analyzing a system, and can become particularly burdensome when coupled analyses are embedded within a design or optimization loop. In many cases, disciplines may be weakly coupled, so that some of the coupling or interaction terms can be neglected without significantly impacting the accuracy of the system output. However, typical practice derives such approximations in an ad hoc manner using expert opinion and domain experience. In this thesis, we propose a new approach...

  17. Riemannian geometry of matrix manifolds for Lagrangian uncertainty quantification of stochastic fluid flows

    Feppon, Florian (Florian Jeremy)
    This work focuses on developing theory and methodologies for the analysis of material transport in stochastic fluid flows. In a first part, two dominant classes of techniques for extracting Lagrangian Coherent Structures are reviewed and compared and some improvements are suggested for their pragmatic applications on realistic high-dimensional deterministic ocean velocity fields. In the stochastic case, estimating the uncertain Lagrangian motion can require to evaluate an ensemble of realizations of the flow map associated with a random velocity flow field, or equivalently realizations of the solution of a related transport partial differential equation. The Dynamically Orthogonal (DO) approximation is applied...

  18. Riemannian geometry of matrix manifolds for Lagrangian uncertainty quantification of stochastic fluid flows

    Feppon, Florian (Florian Jeremy)
    This work focuses on developing theory and methodologies for the analysis of material transport in stochastic fluid flows. In a first part, two dominant classes of techniques for extracting Lagrangian Coherent Structures are reviewed and compared and some improvements are suggested for their pragmatic applications on realistic high-dimensional deterministic ocean velocity fields. In the stochastic case, estimating the uncertain Lagrangian motion can require to evaluate an ensemble of realizations of the flow map associated with a random velocity flow field, or equivalently realizations of the solution of a related transport partial differential equation. The Dynamically Orthogonal (DO) approximation is applied...

  19. Computational tools for enabling longitudinal skin image analysis

    Lee, Kang Qi Ian
    We present a set of computational tools that enable quantitative analysis of longitudinally acquired skin images: the assessment and characterization of the evolution of skin features over time. A framework for time-lapsed skin imaging is proposed. A nonrigid registration algorithm based on multiple plane detection for landmark identification accurately aligns pairs of longitudinal skin images. If dense and thick hairs are present, then nonrigid registration is used to reconstruct the skin texture of occluded regions by recording multiple images from the same area. Realistic reconstruction of occluded skin texture is aided by an automatic hair segmentation algorithm and guided painting...

  20. Computational tools for enabling longitudinal skin image analysis

    Lee, Kang Qi Ian
    We present a set of computational tools that enable quantitative analysis of longitudinally acquired skin images: the assessment and characterization of the evolution of skin features over time. A framework for time-lapsed skin imaging is proposed. A nonrigid registration algorithm based on multiple plane detection for landmark identification accurately aligns pairs of longitudinal skin images. If dense and thick hairs are present, then nonrigid registration is used to reconstruct the skin texture of occluded regions by recording multiple images from the same area. Realistic reconstruction of occluded skin texture is aided by an automatic hair segmentation algorithm and guided painting...

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