Blar i Fakultet for ingeniørvitenskap (IV) på tittel
Viser treff 13330-13349 av 23494
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M.o.T. Mobilmelker og Torsk
(Bachelor thesis, 2023)Dagens situasjon på ODE sitt gjennomstrømninganlegg for torsk på Stadsbygd gjennomføres røkting av fiskekar ved et hevertsystem. På grunn av lave strømningshastigheter i karene fører dette til oppsamling av partikler på ... -
Machinability of Low-Lead and Lead-Free Brass Alloys
(Doctoral thesis, 2024) -
Machine Learning (ML)-Based Prediction and Compensation of Springback for Tube Bending
(Chapter, 2021)Bent tubes are extensively used in the manufacturing industry to meet demands for lightweight and high performance. As one of the most significant behaviors affecting the dimensional accuracy in tube bending, springback ... -
Machine learning algorithm for prediction of stuck pipe incidents using statistical data: case study in middle east oil fields
(Peer reviewed; Journal article, 2022)One of the most troublesome issues in the drilling industry is stuck drill pipes. Drilling activities will be costly and time-consuming due to stuck pipe issues. As a result, predicting a stuck pipe can be more useful. ... -
Machine Learning and Atomic Simulations to predict Nanoscale Ice Adhesion
(Master thesis, 2020)Det er kjent at overflateruhet påvirker hvor godt is fester seg til materialer, men de underliggende mekanismene er ikke fullstendig forstått. I denne masteroppgaven blir to tilnærminger, én fysikkbasert, og én svart ... -
Machine learning and CFD for mapping and optimization of CO2 ejectors
(Peer reviewed; Journal article, 2021)In this study, a novel simulation-based algorithm for CO2 ejector design and performance evaluation is presented. The algorithm is based on an automated Computational Fluid Dynamics (CFD) workflow that can account for ... -
Machine Learning and Computational Micromechanics Models for Multifunctional Cementitious Composites Reinforced by Graphene Derivatives: Mechanical and Functional properties
(Doctoral theses at NTNU;2024:284, Doctoral thesis, 2024)Cementitious composites (CCs), which include cement paste, mortar, and concrete, are widely used around the world, second only to water. They are essential for sustainable construction due to their wide availability, ... -
Machine Learning Approach for Hydrogen Safety in Confined Spaces: Forecasting Pressure Peaking Phenomenon
(Master thesis, 2023)Hydrogen is the most abundant element in the universe and has gained significant attention as a clean and renewable energy source. However, hydrogen also poses significant safety risks, especially when it is stored, ... -
A Machine Learning Approach to Analyze Natural Hazards Accidents Scenarios
(Peer reviewed; Journal article, 2022)Climate change has contributed to an increasing frequency and severity of natural hazards accidents over recent years, and the increasing trend is expected to continue and escalate. Globally, demographics are changing and ... -
A machine learning approach to predict chattering alarms
(Peer reviewed; Journal article, 2020)The alarm system plays a vital role to ensure safety and reliability in the process industry. Ideally, an alarm should inform the operator about critical conditions only and provide guidance to a set of corrective actions ... -
A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement
(Journal article; Peer reviewed, 2023) -
Machine learning assisted low-frequency model building for AVO inversion
(Master thesis, 2018)AVO inversion is a valuable tool to estimate absolute reservoir properties from prestack seismic data. The bandwidth limitation of the seismic requires that the missing low frequencies must be added to the inversion in ... -
Machine learning augmented reduced-order models for FFR-prediction
(Peer reviewed; Journal article, 2021)Computational predictions in cardiovascular medicine have largely relied on explicit models derived from physical and physiological principles. Recently, the application of artificial intelligence in cardiovascular medicine ... -
Machine Learning based Acoustic Anomaly Detection of Gas Leakages in Industrial Environments
(Master thesis, 2022)Målet med denne masteroppgaven var å utvikle en akustisk gasslekkasjedetektor basert på maskinlæring. Gasslekkasjer kan være frustrerende for industrielle anleggseiere da de fører til energiforbruk, høyere kostnader, økt ... -
Machine learning based digital twin framework for aquaculture net cage system
(Master thesis, 2022)I denne master oppgaven er det presentert et rammeverk for digital tvilling for fiskeoppdrettsanlegg ved å bruke numerisk simulering, maskin læring og sensor data. De numeriske simuleringene er utført med programvaren FhSim ... -
Machine Learning Based Heuristic Technique for Multi-response Machining Process
(Peer reviewed; Journal article, 2020)Manufacturing process variables influence the quality of products substantially. It is unquestionably difficult to model the manufacturing processes that include a large number of variables and responses. Development of ... -
Machine Learning Based Prediction of Nanoscale Ice Adhesion on Rough Surfaces
(Peer reviewed; Journal article, 2021)It is widely recognized that surface roughness plays an important role in ice adhesion strength, although the correlation between the two is far from understood. In this paper, two approaches, molecular dynamics (MD) ... -
A machine learning enabled ultra-fine grain design strategy of Mg–Mn-based alloys
(Peer reviewed; Journal article, 2023)Grain size is the critical characteristic of ultra-fine grain Magnesium (Mg), which is a concrete representation of the whole heat deformation procedure. In this paper, a design strategy was proposed to quantitatively ... -
Machine learning for predicting dimensions of extrusion blow molded parts: A comparison of three algorithms
(Journal article; Peer reviewed, 2023)In the perspective of feed-forward control through a manufacturing process chain, production data can be used downstream to correct subsequent processes and improve product quality. In an extrusion blow-moulding (EBM) use ... -
Machine Learning in Predictive Maintenance of Railway Infrastructures: Implementations and Challenges
(Master thesis, 2022)De nylige teknologiske fremskrittene av Industry 4.0 teknologier har skapt et skifte mot applikasjoner innen maskinlæring (ML) for prediktivt vedlikehold (PdM) og har blitt tatt i bruk av mange bransjer. Derimot finnes det ...