SINTEF Open
Not a member yet
11374 research outputs found
Sort by
Materials science and ontologies
Get PDFThis chapter starts by discussing the challenges in material innovation for manufacturing and the need for multidisciplinary approaches involving actors from many different communities. Interoperability is a key to address these challenges. The new paradigm of materials digitalisation is introduced, and how this can be supported by ontologies, continuing into the requirements that materials digitalisation poses on such ontologies. The Elementary Multiperspective Material Ontology is presented, as well as how this top-level ontology provides the semantic foundation for addressing interoperability and the requirements of materials digitalisation. As an application of these concepts, the key aspects of the flow of data and knowledge, including generation, documentation, management and final exploitation, are presented, and it is shown how they are facilitated by ontologies. Two use cases related to manufacturing are presented together with their challenges and the benefits of approaches based on ontologies and semantic data documentation. The chapter ends by presenting future perspectives and the increasing importance of standardisation and semantic interoperability.publishedVersio
Baselinerapport for Fagforbund-kohorten
Get PDFDet er lite av eksisterende forskning som handler om å forebygge helse- og velferdsproblemer som følge av arbeidet for de inkluderte yrkesgruppene. Det er også lite kunnskap om konkrete forebyggende HMS-tiltak, særlig når det gjelder psykososiale risikofaktorer. Forskningen som eksisterer i dag, selv om vi ser på forskning fra hele verden, kan i liten grad fortelle oss hva som bør gjøres for å redusere arbeidsrelatert sykefravær og få folk til å stå lenger i jobb. Det må satses mer på nasjonal forskning for å fremskaffe denne kunnskapen fra arbeidslivet i Norge. Baselineundersøkelsen viser at det er et stort potensial for forbedringer for alle de inkluderte yrkesgruppene. Det handler om å se ting i sammenheng, vurdere behovene og planlegge for fremtiden. Mye kan bli bedre med godt partssamarbeid, et mer systematisk og langsiktig og forebyggende HMS-arbeid og teknologi brukt på en slik måte at det reduserer arbeidsbelastningen heller enn å øke den.Baselinerapport for Fagforbund-kohortenpublishedVersio
An aquaculture risk model to understand the causes and consequences of Atlantic Salmon mass mortality events: A review
Get PDFMass mortality events (MMEs) are defined as the death of large numbers of fish over a short period of time. These events can result in catastrophic losses to the Atlantic salmon aquaculture industry and the local economy. However, they are challenging to understand because of their relative infrequency and the high number of potential factors involved. As a result, the causes and consequences of MMEs in Atlantic salmon aquaculture are not well understood. In this study, we developed a structural network of causal risk factors for MMEs for aquaculture and the communities that depend on Atlantic salmon aquaculture. Using the Interpretive Structural Modeling (ISM) technique, we analysed the causes of Atlantic salmon mass mortalities due to environmental (abiotic), biological (biotic) and nutritional risk factors. The consequences of MMEs were also assessed for the occupational health and safety of aquaculture workers and their implications for the livelihoods of local communities. This structural network deepens our understanding of MMEs and points to management actions and interventions that can help mitigate mass mortalities. MMEs are typically not the result of a single risk factor but are caused by the systematic interaction of risk factors related to the environment, fish diseases, feeding/nutrition and cage-site management. Results also indicate that considerations of health and safety risk, through pre- and post-event risk assessments, may help to minimize workplace injuries and eliminate potential risks of human fatalities. Company and government-assisted socio-economic measures could help mitigate post-mass mortality impacts. Appropriate and timely management actions may help reduce MMEs at Atlantic salmon cage sites and minimize the physical and social vulnerabilities of workers and local communities.publishedVersio
Operational cycles for maritime transportation: Consolidated methodology and assessments
No full textOperational cycles for maritime transportation is a new concept to improve the assessment of ships’ energy efficiency and offer benchmarking options among similar ship types and sizes. This work extends previous research to consolidate the methodology, bring more comprehensiveness, and provide a more holistic assessment of these operational cycles. The cycles are designed from noon reports from a fleet of around 300 container ships divided into eight size groups. The comparison between cycles derived from speed and draft with those based on main engine power identifies that the cycles based on speed and draft are more accurate and allow for estimating the Energy Efficiency Operational Index but require more data. The main-engine-power cycles are more effective in benchmarking through the Annual Efficiency Ratio. These cycles reduce the inherent variability of the carbon intensity indicator and present good opportunities as a benchmarking tool for strengthening the regulatory framework of international shipping.publishedVersio
Behovs- og gevinstanalyse av optimeringsverktøy for pasientreiseplanlegging
Get PDFFormålet med denne analysen er å være et beslutningsgrunnlag for Pasientreiser HF for en mulig fremtidig
anskaffelse av et reiseplanleggingsverktøy med optimeringsfunksjonalitet, dvs. et verktøy som både kan
automatisere planleggingsprosessen og også oppnå kvantifiserte forbedringer i utførelsen av
pasienttransport.
ISBN: 978-82-14-07016-3publishedVersio
Learning active manipulation to target shapes with model-free, long-horizon deep reinforcement learning
Get PDFWe investigate the active manipulation of objects using model-free and long-horizon DRL (Deep Reinforcement Learning) to achieve target shapes. Our proposed approach uses visual observations consisting of segmented images, to mitigate the sim-to-real gap. We address a long-horizon manipulation task requiring a sequence of accurate actions to achieve the target shapes using a robot arm with an RGB-D camera in eye-in-hand configuration, and an elongated, volumetric, elastoplastic object. We find similar objects in food, marine, and manufacturing domains. The aim is to actively manipulate the object into an arbitrary target shape using image observations. We trained a DRL agent using PPO (Proximal Policy Optimization) by running 768 parallel actors in simulation, for a total of 1,2M environment interactions, and tested this on 200 unseen target deformations. In three attempts, 82% of the trials achieved a greater than 90% overlap with the 200 target shapes. By relying on segmentation images as a visual observation space, we successfully transferred the agent to the real world without supplementary training. Our approach does not need any real-world manipulation examples nor fine-tuning in the real world. The robustness of our approach was demonstrated in simulation, and experimentally validated in the real world for specific manipulation tasks, achieving a 94.2% mean zero-shot overlap success rate on previously unseen target shapes.acceptedVersio
Black-boxing of Converter State-Space Models for Power System Eigenvalue Analysis
Get PDFState-space models are useful for a wide range of power system analyses relying on eigenvalue-based small-signal stability assessment. However, state-space models for detailed analysis of power converter dynamics are typically not provided to third-parties due to intellectual property (IP) concerns. This work illustrates how diagonalization of a state-space model will effectively obscure sensitive information about the system structure and parameters. Thus, diagonalization can be utilized as a safe method for providing black-boxed state-space models. The process is performed on an example system to clearly demonstrate that the information revealed in a diagonalized model is no more than what can be determined from system identification of a black-boxed time-domain model. A practical method of implementing this technique to provide linearized small-signal models across the full range of operating points in a compiled application is presented.Black-boxing of Converter State-Space Models for Power System Eigenvalue AnalysisacceptedVersio
Overview of maritime ICT standards for communication between ships and between ship and shore
Get PDFIncreasing digitalization in the society at large, including international ship operations, requires careful consideration of what communication system to deploy and how to use it. This includes basic communication basics, such as quality of service, whether the system supports fine grained API calls or only document transfers and how the system can be influenced by external factors, such as weather or geographic location. Wireless communication will be susceptible to a wide range of factors that can reduce the expected quality of service. It is also necessary to consider how the ICT architecture is implemented in a larger system that includes the ship. In many cases, one will want to reduce direct ship to shore communication to only trusted parties on shore, e.g. only the owner or the manager. While ships use a wide range of dedicated communication systems, most of these are used for very specific purposes and cannot be used for general internet type communication. Internet connectivity will normally be limited to various satellite communication systems or mobile data when close to shore. When access to internet has been established, there are also several different protocol specifications that can be used. The different protocols have different features that make them suited for different applications. Some protocols may be best suited for general data acquisition, others for implementation of service APIs to service providers on shore, while other may be better for remote control and monitoring. The data models employed by the different protocols also differ. Of particular interest is the abstract and mainly semantic IMO Reference Data Model (“IMO Compendium”) that form the sematic baseline for several other technical standards.Overview of maritime ICT standards for communication between ships and between ship and shorepublishedVersio
Innovative heat exchanger design using extruded aluminium profiles for PCM-based TES systems
Get PDFWe introduce an innovative heat exchanger design for phase change materials (PCM)-based thermal energy storage (TES) solutions. With buildings and industries facing peak energy demands and high costs, PCM-TES offers an efficient and sustainable solution. The novel heat exchanger design replaces conventional stainless-steel pillow-plates with extruded aluminium profiles, demonstrating enhanced affordability, competitiveness, and environmental sustainability. Achieving Technology Readiness Level 4 (TRL4), the proof-of-concept unit showcases a TES capacity of 160 Wh. This advancement addresses the challenge of low heat transfer rates, providing a cost-efficient solution for large-scale storage facilities. With a pending patent and plans for further development, this innovation promises to revolutionize PCM-TES technology, contributing to a greener and more energy-efficient future.acceptedVersio
Comparison of time-invariant and adaptive linear grey-box models for model predictive control of residential buildings
Get PDFModel predictive control (MPC) is a promising optimal control technique for activating building energy flexibility using its thermal mass. The performance of the MPC controller is directly related to the accuracy of the model prediction. Grey-box models, based on physical laws and calibrated on measurement data, are commonly used to represent the building thermal dynamics in MPC. Most research works use Linear Time-Invariant (LTI) grey-box models even though weather conditions vary significantly throughout the heating season. This is critical as inaccurate model prediction can lead to a lower performance of the MPC controller. This study introduces two adaptive MPC schemes to overcome this limitation of LTI models. The first one, called the Partially Adaptive MPC, only updates the effective window area of the prediction model. The second one, called the Fully Adaptive MPC, updates all the parameters of the grey-box model. The adaptive MPC performance is compared with MPC using LTI models in two different tests. The simulation-based results show that MPC based on LTI performs well if the control model is trained during a period with similar weather conditions as the period when the MPC will be applied. The Partially Adaptive MPC is unable to deliver satisfactory prediction performance due to the limited number of parameters that are updated. The Fully Adaptive MPC has the best performance compared to the other MPCs, especially as it avoids thermal comfort violations.publishedVersio