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Visar resultat 1 - 5 av 13 uppsatser som matchar ovanstående sökkriterier.

  1. 1. The Effect of Temperature Gradients During Intercritical Annealing of Advanced High Strength Steels : Method Development for Experimental Streamlining

    Master-uppsats, KTH/Materialvetenskap

    Författare :Helena Ek Jendrny; [2023]
    Nyckelord :AHSS; Gleeble; Intercritical annealing; Retained austenite; Medium Mn Steel; AHSS; Gleeble; interkritisk glödgning; austenit; Medium Mn stål;

    Sammanfattning : The third-generation advanced high strength steels, AHSS, represent an opportunity for today’s steel development, where lighter materials with maintained strength and toughness are in demand. The unique properties of these materials often stem from a tailored microstructure. LÄS MER

  3. 2. Investigating the Use of Digital Twins to Optimize Waste Collection Routes : A holistic approach towards unlocking the potential of IoT and AI in waste management

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Aarati Medehal; [2023]
    Nyckelord :Internet of Things; Industry 4.0; Smart Cities; Artificial Intelligence; Travelling Salesman problem; Vehicle Routing Problems; Digital Twins; Waste collection; Optimization; Metaheuristics algorithms; Ant Colony Optimization; Simulated Annealing; Particle Swarm; Tabu Search; Genetic Algorithm; Ontology; Digital Twin Definition Language; Internet of Things; Industri 4.0; Smarta städer; Artificiell intelligens; Travelling Salesman problem; Vehicle Routing Problems; Digitala tvillingar; Sophämtning; Optimering; Metaheuristika algoritmer; Ant Colony optimering; Simulerad glödgning; Partikelsvärm; Tabu-sökning; Genetisk algoritm; Ontologi; Digitala tvillingar defintitionsspråk;

    Sammanfattning : Solid waste management is a global issue that affects everyone. The management of waste collection routes is a critical challenge in urban environments, primarily due to inefficient routing. This thesis investigates the use of real-time virtual replicas, namely Digital Twins to optimize waste collection routes. LÄS MER

  4. 3. Application of ring statistics to characterise graphitisation of carbon fiber heat shields under atmospheric re-entry conditions

    Master-uppsats, KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanik

    Författare :Hamish Keay; [2023]
    Nyckelord :Aerospace; Heat shields; Re-entry; Graphitisation; Carbon fiber; Carbon phenolic; Ring statistics; Graph theory; Molecular Dynamics; återinträde; grafitisering; kolfiber; kolfenol; ringstatistik; grafteori; molekylär dynamik;

    Sammanfattning : Carbon fibers submitted to high temperatures (>2000 °C) experience a permanent increasein their thermal conductivity. This change has been attributed to a change in the molecularstructure due to graphitisation. LÄS MER

  5. 4. Structural modifications of polyester fibres induced by thermal and chemical treatments to obtain high-performance fibres

    Master-uppsats, KTH/Fiber- och polymerteknologi

    Författare :Kartikeya Sharma; [2021]
    Nyckelord :PET fibres; P3HB fibres; Radial gradient; Chemical modification; Thermal annealing; High-performance fibres; PET-fibrer; P3HB-fibrer; Radiell lutning; Kemisk modifiering; termisk glödgning; högpresterande fibrer;

    Sammanfattning : Del A: Polyetylentereftalat fibrer I detta arbete presenteras olika metoder för att framställa monofilament av polyetylentereftalat (PET) (diameter: 30-50 µm) med en radiell gradient. Nyutvecklad Raman-spektroskopiteknik har använts för att kartlägga dessa inducerade radiella gradienter i t.ex. kristallinitet. LÄS MER

  7. 5. On the effectiveness of ß-VAEs for imageclassification and clustering : Using a disentangled representation for Transfer Learning and Semi-Supervised Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Vittorio Maria Enrico Denti; [2020]
    Nyckelord :;

    Sammanfattning : Data labeling is a critical and costly process, thus accessing large amounts of labeled data is not always feasible. Transfer Learning (TL) and Semi-Supervised Learning (SSL) are two promising approaches to leverage both labeled and unlabeled samples. LÄS MER