We report on a first field test in which miniaturized sensor motes were used to explore and inspect an operational pipeline by performing in situ measurements. The spherical sensor motes with a diameter of 39 mm were equipped with an inertial measurement unit (IMU) measuring 3-D acceleration, rotation, and magnetic field, as well as an ultrasound emitter. The motes were injected into the pipeline and traversed a 260-m section of it with the flow of water. After the extraction of the motes from the pipeline, the recorded IMU data were read out for the off-line analysis. Unlike dead-reckoning techniques, we analyze the IMU data to reveal structural information about the pipeline and locate pipe components, such as hydrants and junctions. The recorded data show different and distinct patterns that are a result of the fluid dynamics and the interaction with the pipeline. Using the magnetic data, pipe sections made from different materials and pipe components are identified and localized. A preliminary analysis on the motes' interaction with the pipeline shows differences in pipe wall roughness and locates structural anomalies. The results of this field test show that sensor motes can be used as a versatile and cost-effective tool for exploration and inspection of a wide variety of pipelines.
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The main goal of this study is to identify knowledge gaps and uncertainties in Quantitative Risk Assessments (QRA) for CO2 pipelines and to assess to what extent those gaps and uncertainties affect the final outcome of the QRA. The impact of methodological choices and uncertain values for input parameters on the results of QRA’s have been assessed through an extensive literature review and by using commercially available release, dispersion and effect models. It is made apparent that over the full life cycle of a QRA knowledge gaps and uncertainties are present that may have large scale impact on the accuracy of assessing risks of CO2 pipelines. These encompass the invalidated release and dispersion models, the currently used failure rates, choosing the type of release to be modeled and the dose-effect relationships assumed. Also recommendations are presented for the improvement of QRA’s for CO2 pipelines.
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Biogas is produced from biomass by means of digestion. Treated to so-called ‘green gas’, it can replace natural gas. Alternatively, biogas can be used to produce electrical power and heat in a combined heat power (CHP) installation. In 2014 global biogas production was only 1% of natural gas production. In the future, biogas is expected to play a role in specific applications, e.g. to provide flexibility in electricity supply
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Collaboratively editing game worlds and the underlying asset version management techniques present us with many challenges when using a traditional Version Control System (VCS). This paper suggests a new method that will aid in the tracking, branching, and selection of asset versions within a game development pipeline. A prototype has been developed which demonstrated im-provements in both productivity and usability providing greater visibility of incremental asset changes and alterations to their relationships which equated to approximately a 30% better user experience when compared to an existing industry VCS.
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Hydrogen (H2) is a key element in the Dutch energy transition, considered a sources of flexibility to balance the variable renewable energy sources, facilitating its integration into the energy system. But also as an energy carrier. Both the gas and electricity transmission operators (TSO) have the vision to interconnect their networks with H2, by distributing the green H2 produced with offshore electrolysers into high pressure gas pipelines to relive the overload electric network. The planned compressed H2 pipelines cross the north of North-Holland region, offering a backbone for a H2 economy. Furthermore, at regional level there are already a big number of privet-public H2 developments, among them the DuWaAl, which is a H2 production-demand chain, consists of 1) An H2 mill, 2) 5 filling stations in the region and 3) a large fleet of trucks and other users. Because of these developments, the North-Holland region needs a better insight into the position that H2 could fulfil in the local energy system to contribute to the energy transition. The aim of this research is to analyse these H2 economy, from the emergent to settled, by identifying early and potential producer- consumer, considering the future infrastructure requirements, and exploring economy-environmental impacts of different supply paths
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A model to describe biogas transport costs in a regional grid is presented. In the model biogas is collected to a central location by transport through dedicated pipelines. Costs have been calculated for two different lay-outs of the grid i.e. star and fishbone lay-out. The costs depend on the covered area and the size of the digesters. Model results show that in a star layout transport costs for small scale digesters are much higher than costs for large scale digesters and costs in a fishbone lay-out are lower than costs in a star lay-out.
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The past two years I have conducted an extensive literature and tool review to answer the question: “What should software engineers learn about building production-ready machine learning systems?”. During my research I noted that because the discipline of building production-ready machine learning systems is so new, it is not so easy to get the terminology straight. People write about it from different perspectives and backgrounds and have not yet found each other to join forces. At the same time the field is moving fast and far from mature. My focus on material that is ready to be used with our bachelor level students (applied software engineers, profession-oriented education), helped me to consolidate everything I have found into a body of knowledge for building production-ready machine learning (ML) systems. In this post I will first define the discipline and introduce the terminology for AI engineering and MLOps.
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In my previous post on AI engineering I defined the concepts involved in this new discipline and explained that with the current state of the practice, AI engineers could also be named machine learning (ML) engineers. In this post I would like to 1) define our view on the profession of applied AI engineer and 2) present the toolbox of an AI engineer with tools, methods and techniques to defy the challenges AI engineers typically face. I end this post with a short overview of related work and future directions. Attached to it is an extensive list of references and additional reading material.
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This article analyzes how a city can generate instrumental, intrinsic, and institutional value from its event-related networks and platforms, based on the Hieronymus Bosch 500 program in the Dutch city of ‘s-Hertogenbosch (Den Bosch). Interviews with key stakeholders traced program dynamics over more than a decade to reveal processes of network and platform development, encapsulated in a conceptual model of strategic value creation. The results indicate that networks served to generate flows of resources, while programming helped develop platforms for knowledge generation and dissemination, helping to focus attention on the city. The Bosch 500 Foundation managing the program played an effective role in developing and supporting networks, which in turn generated significant short-term instrumental and intrinsic value. However, the failure to establish a sustainable city-wide platform related to the Bosch program caused institutional value destruction, which many saw as a missed opportunity. The study of networks and platforms can benefit from a longitudinal approach as well as a broader, contextual view of event networks.
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