Essays about: "reduced order modeling"

Showing result 1 - 5 of 57 essays containing the words reduced order modeling.

1. 1. A study of productivity measurement and modeling of inhaler production at AstraZeneca

   University essay from Linköpings universitet/Kommunikations- och transportsystem; Linköpings universitet/Tekniska fakulteten

   Author : Vilma Björk Öhhrfelt; Ebba Österman; [2023]
   Keywords : Produktivitet; produktivitetsmått; produktionsplanering; diskret händelsestyrd simulering; kapacitetsförändringar; produktionslogistik; Industriell ekonomi; Industriell ekonomi;

   Abstract : Production planning and evaluation can be performed using various tools. This study encompasses two main topics: productivity measurement and production simulation. The study was conducted at AstraZeneca, a pharmaceutical company, where their production of inhalers was examined. READ MORE

3. 2. When is Electric Freight Cost Competitive? : Computational modeling and simulation of total cost of ownership for electric truck fleets

   University essay from Linköpings universitet/Institutionen för ekonomisk och industriell utveckling

   Author : Anton Zackrisson; [2023]
   Keywords : electric freight; battery-electric trucks; total cost of ownership; decision making under deep uncertainty DMDU ; cost-competitiveness; exploratory modeling and analysis EMA ; EMA workbench; quasi-Monte Carlo method; VRP; EVRP; elektrifiering; godstransport; elektriska lastbilar; total ägandekostnad; kostnadskonkurrenskraft; ruttoptimering;

   Abstract : Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity.  Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. READ MORE

4. 3. Nonlinear Methods of Aerodynamic Data-driven Reduced Order Modeling

   University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

   Author : Arvid Forsberg; [2022]
   Keywords : machine learning; aerodynamics; autoencoder; kernel transformation; principal component analysis; nonlinear; regression; modeling; surrogate model; reduced order modeling; neural network;

   Abstract : Being able to accurately approximate outputs of computationally expensive simulations for arbitrary input parameters, also called missing points estimation, is central in many different areas of research and development with applications ranging from uncertainty propagation to control system design to name a few. This project investigates the potential of kernel transformations and nonlinear autoencoders as methods of improving the accuracy of the proper orthogonal decomposition method combined with regression. READ MORE

5. 4. An agent-based model approach to computational epidemiology

   University essay from KTH/Datavetenskap

   Author : Max Wiktorsson; Emil Franzell; [2022]
   Keywords : ;

   Abstract : The aim of this work was to compare different Non-pharmaceutical interventions (NPIs) in a simulated environment modeling Sweden with 10 000 000 (ten million) agents. Simulating the performance of these NPIs can be beneficial to policymakers and other government officials in order to give the power to make the right decision in the face of an epidemic. READ MORE

6. 5. Analyzing the Negative Log-Likelihood Loss in Generative Modeling

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Aleix Espuña I Fontcuberta; [2022]
   Keywords : Generative modeling; Normalizing flows; Generative Adversarial Networks; MaximumLikelihood Estimation; Real Non-Volume Preserving flow; Fréchet Inception Distance; Misspecification; Generativa metoder; Normalizing flows; Generative adversarial networks; Maximum likelihood-metoden; Real non-volume preserving flow; Fréchet inception distance; felspecificerade modeller;

   Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE