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In this paper, a 256-channel, 10-GHz arrayed waveguide gratings demultiplexer for ultra-dense wavelength division multiplexing was designed using an in-house developed tool called AWG-Parameters. The AWG demultiplexer was designed for a central wavelength of 1550 nm and the structure was simulated in PHASAR tool from Optiwave. Two different AWG designs were developed and the influence of the design parameters on the AWG performance was studied.
The paper shows concepts of optical splitting based on three dimensional (3D) optical splitters based on multimode interference principle. This paper is focused on the design, fabrication and characterization of 3D MMI splitter with formed output waveguides based on IP-Dip polymer for direct application on optical fiber. The MMI optical splitter was simulated and fabricated using direct laser writing process. Output characteristics were characterized by highly resolved near-field scanning optical microscope (NSOM) and compared with 3D MMI splitter without output waveguides.
In this paper, we propose and simulate a new type of three-dimensional (3D) optical splitter based on multimode interference (MMI) for the wavelength of 1550 nm. The splitter was proposed on the square basis with the width of 20 x 20 µm2 using the IP-Dip polymer as a standard material for 3D laser lithography. We present the optical field distribution in the proposed MMI splitter and its integration possibility on optical fiber. The design is aimed to the possible fabrication process using the 3D laser lithography for forthcoming experiments.
In this paper, we document optical splitters based on Y-branch and also on MMI splitting principle. The 1×4 Y-branch splitter was prepared in 3D geometry fully from polymer approaching the single mode transmission at 1550 nm. We also prepared new concept of 1×4 MMI optical splitter. Their optical properties and character of output optical field were measured by near-field scanning optical microscope. Splitting properties and optical outputs of both splitters are very promising and increase an attractiveness of presented 3D technology and polymers.
We present a new concept of 3D polymer-based 1 × 4 beam splitter for wavelength splitting around 1550 nm. The beam splitter consists of IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding. The splitter was designed and simulated with two different photonics tools and the results show high splitting ratio for single-mode and multi-mode operation with low losses. Based on the simulations, a 3D beam splitter was designed and realized using direct laser writing (DLW) process with adaptation to coupling to standard single-mode fiber. With respect to the technological limits, the multi-mode splitter having core of (4 × 4) μm 2 was designed and fabricated together with supporting stable mechanical construction. Splitting properties were investigated by intensity monitoring of splitter outputs using optical microscopy and near-field scanning optical microscopy. In the development phase, the optical performance of fabricated beam splitter was examined by splitting of short visible wavelengths using red light emitting diode. Finally, the splitting of 1550 nm laser light was studied in detail by near-field measurements and compared with the simulated results. The nearly single-mode operation was observed and the shape of propagating mode and mode field diameter was well recognized.
Power plant operators increasingly rely on predictive models to diagnose and monitor their systems. Data-driven prediction models are generally simple and can have high precision, making them superior to physics-based or knowledge-based models, especially for complex systems like thermal power plants. However, the accuracy of data-driven predictions depends on (1) the quality of the dataset, (2) a suitable selection of sensor signals, and (3) an appropriate selection of the training period. In some instances, redundancies and irrelevant sensors may even reduce the prediction quality.
We investigate ideal configurations for predicting the live steam production of a solid fuel-burning thermal power plant in the pulp and paper industry for different modes of operation. To this end, we benchmark four machine learning algorithms on two feature sets and two training sets to predict steam production. Our results indicate that with the best possible configuration, a coefficient of determination of R^2 = 0.95 and a mean absolute error of MAE=1.2 t/h with an average steam production of 35.1 t/h is reached. On average, using a dynamic dataset for training lowers MAE by 32% compared to a static dataset for training. A feature set based on expert knowledge lowers MAE by an additional 32 %, compared to a simple feature set representing the fuel inputs. We can conclude that based on the static training set and the basic feature set, machine learning algorithms can identify long-term changes. When using a dynamic dataset the performance parameters of thermal power plants are predicted with high accuracy and allow for detecting short-term problems.
This thesis aims to support the product development process. Therefore, an approach is developed, implemented as a prototype and evaluated, for automated solution space exploration of formally predefined design automation tasks holding the product knowledge of engineers. For this reason, a classification of product development tasks related to the representation of the mathematical model is evaluated based on the parameters defined in this thesis. In a second step, the mathematical model should be solved. A Solver is identified able to handle the given problem class.
Due to the context of this work, System Modelling Language (SysML) is chosen for the product knowledge formalisation. In the next step the given SysML model has to be translated into an object-oriented model. This translation is implemented by extracting information of a ".xml"-file using the XML Metadata Interchanging (XMI) standard. The information contained in the file is structured using the Unified Modelling Language (UML) profile for SysML. Afterwards a mathematical model in MiniZinc language is generated. MiniZinc is a mathematical modelling language interpretable by many different Solvers. The generated mathematical model is classified related to the Variable Type and Linearity of the Constraints and Objective of the generated mathematical model. The output is stored in a ".txt"-file.
To evaluate the functionality of the prototype, time consumption of the different performed procedures is measured. This data shows that models containing Continuous Variables need a longer time to be classified and optimised. Another observation shows that the transformation into an object-oriented model and the translation of this model into a mathematical representation are dependent on the number of SysML model elements. Using MiniZinc resulted in the restriction that models which use non-linear functions and Boolean Expressions cannot be solved. This is because the implementation of non-linear Solvers at MiniZinc is still in the development phase. An investigation of the optimally of the results, provided by the Solvers, was left for further work.
The Digital Factory Vorarlberg is the youngest Research Center of Vorarlberg University of Applied Sciences. In the lab of the research center a research and learning factory has been established for educating students and employees of industrial partners. Showcases and best practice scenarios for various topics of digitalization in the manufacturing industry are demonstrated. In addition, novel methods and technologies for digital production, cloud-based manufacturing, data analytics, IT- and OT-security or digital twins are being developed. The factory comprises only a minimum core of logistics and fabrication processes to guarantee manageability within an academic setup. As a product, fidget spinners are being fabricated. A webshop allows customers to individually design their products and directly place orders in the factory. A centralized SCADA-System is the core data hub for the factory. Various data analytic tools and methods and a novel database for IoT-applications are connected to the SCADA-System. As an alternative to on premise manufacturing, orders can be pushed into a cloud-based manufacturing platform, which has been developed at the Digital Factory. A broker system allows fabrication in distributed facilities and offers various optimization services. Concepts, such as outsourcing product configuration to customers or new types of engineering services in cloud-based manufacturing can be explored and demonstrated. In this paper, we present the basic concept of the Digital Factory Vorarlberg, as well as some of the newly developed topics.