Now showing items 68-87 of 170

    • Lagrangian methods for ballistic impact simulations/ 

      Tupek, Michael Ronne (Massachusetts Institute of Technology, 2010)
      This thesis explores various Lagrangian methods for simulating ballistic impact with the ultimate goal of finding a universal, robust and scalable computational framework to assist in the design of armor systems. An overview ...
    • Learning symmetry-preserving interatomic force fields for atomistic simulations 

      Batzner, Simon Lutz. (Massachusetts Institute of Technology, 2019)
      Machine-Learning Interatomic Force-Fields have shown great promise in increasing time- and length-scales in atomistic simulations while retaining the high accuracy of the reference calculations that they are trained on. ...
    • A linear multigrid preconditioner for the solution of the Navier-Stokes equations using a discontinuous Galerkin discretization 

      Diosady, Laslo Tibor (Massachusetts Institute of Technology, 2007)
      A Newton-Krylov method is developed for the solution of the steady compressible Navier-Stokes equations using a Discontinuous Galerkin (DG) discretization on unstructured meshes. An element Line-Jacobi preconditioner is ...
    • Logistic regression for a better matching of buyers and suppliers in e-procurement 

      Tian, Shuo, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2010)
      The thesis aims to provide a way to identify better matches between buyers and suppliers who are using an e-procurement platform provided by a US based worldwide online market company. The goal is to enhance the shopping ...
    • Loss of coordination in competitive supply chains 

      Teo, Koon Soon (Massachusetts Institute of Technology, 2009)
      The loss of coordination in supply chains quantifies the inefficiency (i.e. the loss of total profit) due to the presence of competition in the supply chain. In this thesis, we discuss four models: one model with multiple ...
    • Loss pattern recognition and profitability prediction for insurers through machine learning 

      Wang, Ziyu, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2017)
      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 ...
    • Low rank decompositions for sum of squares optimization 

      Sun, Jia Li, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2006)
      In this thesis, we investigate theoretical and numerical advantages of a novel representation for Sum of Squares (SOS) decomposition of univariate and multivariate polynomials. This representation formulates a SOS problem ...
    • Low rank matrix completion 

      Nan, Feng, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2009)
      We consider the problem of recovering a low rank matrix given a sampling of its entries. Such problems are of considerable interest in a diverse set of fields including control, system identification, statistics and signal ...
    • LP-based subgradient algorithm for joint pricing and inventory control problems 

      Rao, Tingting (Massachusetts Institute of Technology, 2008)
      It is important for companies to manage their revenues and -reduce their costs efficiently. These goals can be achieved through effective pricing and inventory control strategies. This thesis studies a joint multi-period ...
    • The Markov chain Monte Carlo approach to importance sampling in stochastic programming 

      Ustun, Berk (Tevfik Berk) (Massachusetts Institute of Technology, 2012)
      Stochastic programming models are large-scale optimization problems that are used to facilitate decision-making under uncertainty. Optimization algorithms for such problems need to evaluate the expected future costs of ...
    • Massively parallel solver for the high-order Galerkin Least-Squares method 

      Yano, Masayuki, Ph. D. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2009)
      A high-order Galerkin Least-Squares (GLS) finite element discretization is combined with massively parallel implicit solvers. The stabilization parameter of the GLS discretization is modified to improve the resolution ...
    • Methods and applications in computational protein design 

      Biddle, Jason Charles (Massachusetts Institute of Technology, 2010)
      In this thesis, we summarize our work on applications and methods for computational protein design. First, we apply computational protein design to address the problem of degradation in stored proteins. Specifically, we ...
    • Methods for design optimization using high fidelity turbulent flow simulations 

      Talnikar, Chaitanya Anil (Massachusetts Institute of Technology, 2015)
      Design optimization with high-fidelity turbulent flow simulations can be challenging due to noisy and expensive objective function evaluations. The noise decays slowly as computation cost increases, therefore is significant ...
    • Model reduction for dynamic sensor steering : a Bayesian approach to inverse problems 

      Wogrin, Sonja (Massachusetts Institute of Technology, 2008)
      In many settings, distributed sensors provide dynamic measurements over a specified time horizon that can be used to reconstruct information such as parameters, states or initial conditions. This estimation task can be ...
    • Model simplification of chemical kinetic systems under uncertainty 

      Coles, Thomas Michael Kyte (Massachusetts Institute of Technology, 2011)
      This thesis investigates the impact of uncertainty on the reduction and simplification of chemical kinetics mechanisms. Chemical kinetics simulations of complex fuels are very computationally expensive, especially when ...
    • Modeling flow encountering abrupt topography using hybridizable discontinuous Galerkin projection methods 

      Vo, Johnathan Hiep (Massachusetts Institute of Technology, 2017)
      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 ...
    • Modeling the semiconductor industry dynamics 

      Wu, Kailiang (Massachusetts Institute of Technology, 2008)
      The semiconductor industry is an exciting and challenging industry. Strong demand at the application end, plus the high capital intensity and rapid technological innovation in manufacturing, makes it difficult to manage ...
    • Modeling travel time uncertainty in traffic networks 

      Chen, Daizhuo (Massachusetts Institute of Technology, 2010)
      Uncertainty in travel time is one of the key factors that could allow us to understand and manage congestion in transportation networks. Models that incorporate uncertainty in travel time need to specify two mechanisms: ...
    • Modelling pandemic influenza progression using Spatiotemporal Epidemiological Modeller (STEM) 

      Zhang, Hui, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2009)
      The purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease ...
    • Molecular dynamics-based approaches for mesoscale lubrication 

      Chandramoorthy, Nisha (Massachusetts Institute of Technology, 2016)
      Classical lubrication theory is unable to describe nanoscale flows due to the failure of two of its constitutive components: a) the Newtonian stress-strain rate relationship and b) the no-slip boundary condition. In this ...