10,336 research outputs found

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    The biology and general ecology of the Koaro (Galaxias brevipinnis) in some tributary streams of Lake Taupo

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    The ecology and general biology of Galaxias brevipinnis were studied in three tributary streams of Lake Taupo between May 1988 and April 1989. Adult koaro were found in relatively high densities in the Waipehi and Omori streams but in low densities in the larger Waiotaka stream. The results of population estimation studies suggest that the distribution and abundance of koaro is negatively correlated with that of trout. There was a general decline in the population density of stream-resident koaro in the winter months. Juvenile koaro were found to migrate into the tributaries from August to December, with migrations being at a peak in October and November. Population length-frequency distributions and otoliths used to age koaro indicated that there were up to 5 age classes. Growth was allometric and was adequately described by the von Bertalanffy equation after the first year of life. Koaro were found to be in best condition in the Spring and lowest in Winter. Spawning appeared to occur from December through to April peaking in late Summer to early in the Waipehi Stream was Autumn. The mean fecundity of koaro approximately 5500. A sex-ratio of approximately 1:1 (males: females) were found in the koaro populations in the Omori and Waipehi streams, but during spawning there were always more ripe males than gravid females. There was considerable overlap in the diets of both koaro and juvenile rainbow trout in the Waipehi and Omori streams, with invertebrates being consumed according to their relative abundance in the benthos. Ephemeroptera larvae were numerically the most important food item in the diet of both species. However, by weight, fish (juvenile koaro) were the most important food · item in the diet of koaro and rainbow trout in the Waipehi stream. In the Omori stream in Winter, trout eggs were the most important food item in terms of weight. Terrestrial prey was found to be of relatively minor importance in the diets of koaro and rainbow trout in the Waipehi and Omori streams

    Full stack development toward a trapped ion logical qubit

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    Quantum error correction is a key step toward the construction of a large-scale quantum computer, by preventing small infidelities in quantum gates from accumulating over the course of an algorithm. Detecting and correcting errors is achieved by using multiple physical qubits to form a smaller number of robust logical qubits. The physical implementation of a logical qubit requires multiple qubits, on which high fidelity gates can be performed. The project aims to realize a logical qubit based on ions confined on a microfabricated surface trap. Each physical qubit will be a microwave dressed state qubit based on 171Yb+ ions. Gates are intended to be realized through RF and microwave radiation in combination with magnetic field gradients. The project vertically integrates software down to hardware compilation layers in order to deliver, in the near future, a fully functional small device demonstrator. This thesis presents novel results on multiple layers of a full stack quantum computer model. On the hardware level a robust quantum gate is studied and ion displacement over the X-junction geometry is demonstrated. The experimental organization is optimized through automation and compressed waveform data transmission. A new quantum assembly language purely dedicated to trapped ion quantum computers is introduced. The demonstrator is aimed at testing implementation of quantum error correction codes while preparing for larger scale iterations.Open Acces

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    Industry 4.0: product digital twins for remanufacturing decision-making

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    Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored

    Estudo do IPFS como protocolo de distribuição de conteúdos em redes veiculares

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    Over the last few years, vehicular ad-hoc networks (VANETs) have been the focus of great progress due to the interest in autonomous vehicles and in distributing content not only between vehicles, but also to the Cloud. Performing a download/upload to/from a vehicle typically requires the existence of a cellular connection, but the costs associated with mobile data transfers in hundreds or thousands of vehicles quickly become prohibitive. A VANET allows the costs to be several orders of magnitude lower - while keeping the same large volumes of data - because it is strongly based in the communication between vehicles (nodes of the network) and the infrastructure. The InterPlanetary File System (IPFS) is a protocol for storing and distributing content, where information is addressed by its content, instead of its location. It was created in 2014 and it seeks to connect all computing devices with the same system of files, comparable to a BitTorrent swarm exchanging Git objects. It has been tested and deployed in wired networks, but never in an environment where nodes have intermittent connectivity, such as a VANET. This work focuses on understanding IPFS, how/if it can be applied to the vehicular network context, and comparing it with other content distribution protocols. In this dissertation, IPFS has been tested in a small and controlled network to understand its working applicability to VANETs. Issues such as neighbor discoverability times and poor hashing performance have been addressed. To compare IPFS with other protocols (such as Veniam’s proprietary solution or BitTorrent) in a relevant way and in a large scale, an emulation platform was created. The tests in this emulator were performed in different times of the day, with a variable number of files and file sizes. Emulated results show that IPFS is on par with Veniam’s custom V2V protocol built specifically for V2V, and greatly outperforms BitTorrent regarding neighbor discoverability and data transfers. An analysis of IPFS’ performance in a real scenario was also conducted, using a subset of STCP’s vehicular network in Oporto, with the support of Veniam. Results from these tests show that IPFS can be used as a content dissemination protocol, showing it is up to the challenge provided by a constantly changing network topology, and achieving throughputs up to 2.8 MB/s, values similar or in some cases even better than Veniam’s proprietary solution.Nos últimos anos, as redes veiculares (VANETs) têm sido o foco de grandes avanços devido ao interesse em veículos autónomos e em distribuir conteúdos, não só entre veículos mas também para a "nuvem" (Cloud). Tipicamente, fazer um download/upload de/para um veículo exige a utilização de uma ligação celular (SIM), mas os custos associados a fazer transferências com dados móveis em centenas ou milhares de veículos rapidamente se tornam proibitivos. Uma VANET permite que estes custos sejam consideravelmente inferiores - mantendo o mesmo volume de dados - pois é fortemente baseada na comunicação entre veículos (nós da rede) e a infraestrutura. O InterPlanetary File System (IPFS - "sistema de ficheiros interplanetário") é um protocolo de armazenamento e distribuição de conteúdos, onde a informação é endereçada pelo conteúdo, em vez da sua localização. Foi criado em 2014 e tem como objetivo ligar todos os dispositivos de computação num só sistema de ficheiros, comparável a um swarm BitTorrent a trocar objetos Git. Já foi testado e usado em redes com fios, mas nunca num ambiente onde os nós têm conetividade intermitente, tal como numa VANET. Este trabalho tem como foco perceber o IPFS, como/se pode ser aplicado ao contexto de rede veicular e compará-lo a outros protocolos de distribuição de conteúdos. Numa primeira fase o IPFS foi testado numa pequena rede controlada, de forma a perceber a sua aplicabilidade às VANETs, e resolver os seus primeiros problemas como os tempos elevados de descoberta de vizinhos e o fraco desempenho de hashing. De modo a poder comparar o IPFS com outros protocolos (tais como a solução proprietária da Veniam ou o BitTorrent) de forma relevante e em grande escala, foi criada uma plataforma de emulação. Os testes neste emulador foram efetuados usando registos de mobilidade e conetividade veicular de alturas diferentes de um dia, com um número variável de ficheiros e tamanhos de ficheiros. Os resultados destes testes mostram que o IPFS está a par do protocolo V2V da Veniam (desenvolvido especificamente para V2V e VANETs), e que o IPFS é significativamente melhor que o BitTorrent no que toca ao tempo de descoberta de vizinhos e transferência de informação. Uma análise do desempenho do IPFS em cenário real também foi efetuada, usando um pequeno conjunto de nós da rede veicular da STCP no Porto, com o apoio da Veniam. Os resultados destes testes demonstram que o IPFS pode ser usado como protocolo de disseminação de conteúdos numa VANET, mostrando-se adequado a uma topologia constantemente sob alteração, e alcançando débitos até 2.8 MB/s, valores parecidos ou nalguns casos superiores aos do protocolo proprietário da Veniam.Mestrado em Engenharia de Computadores e Telemátic

    Visual Servo Based Space Robotic Docking for Active Space Debris Removal

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    This thesis developed a 6DOF pose detection algorithm using machine learning capable of providing the orientation and location of an object in various lighting conditions and at different angles, for the purposes of space robotic rendezvous and docking control. The computer vision algorithm was paired with a virtual robotic simulation to test the feasibility of using the proposed algorithm for visual servo. This thesis also developed a method for generating virtual training images and corresponding ground truth data including both location and orientation information. Traditional computer vision techniques struggle to determine the 6DOF pose of an object when certain colors or edges are not found, therefore training a network is an optimal choice. The 6DOF pose detection algorithm was implemented on MATLAB and Python. The robotic simulation was implemented on Simulink and ROS Gazebo. Finally, the generation of training data was done with Python and Blender
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