210 research outputs found
Heat Pump with Two Heat Sources on Different Temperature Levels
Aim of the project is the development of a new heat pump system with economizing that is able to improve the heating performance using two or more different heat sources. These heat sources preferably on different temperature levels are incorporated in the system with minimal loss of exergy, by adding the heat at different pressure levels. Applications are i.e. buildings with heat pump and a solar thermal collector. While solar thermal systems can be used for heating and domestic hot water in summer, they fail to produce sufficient temperatures in fall and spring. When the solar collectors are also connected to the heat pump, they are able to supply temperatures higher than ambient at a medium temperature level. This heat at medium temperature can be used to improve the efficiency of an air source heat pump using the here proposed cycle. Existing systems using two heat sources are either inefficient or need large amounts of waste heat, while the proposed cycle can also use very small amounts of waste heat up to 40% of the total heat input. Other heat sources like process waste heat or exhaust air from a building are possible. Depending on the amount of waste heat and the temperature level of the heat pump cycle, efficiency and heating capacity improvements of 20-30% are possible. Oil management and control of the system are the main challenges when implementing it in the field. The paper will present the idea of the new cycle and its application in heat pump and refrigeration systems together with simulation results that show the effects of different parameters
Region-based Multimedia Indexing and Retrieval Framework
Many systems have been proposed for automatic description and indexing of digital data, for posterior retrieval. One of such content-based indexing-and-retrieval systems, and the one used as a framework in this thesis, is the MUVIS system, which was developed at Tampere University of Technology, in Finland. Moreover, Content-based Image Retrieval (CBIR) utilising frame-based and region-based features has been a dynamic research area in the past years. Several systems have been developed using their specific segmentation, feature extraction, and retrieval methods.
In this thesis, a framework to model a regionalised CBIR framework is presented. The framework does not specify or fix the segmentation and local feature extraction methods, which are instead considered as “black-boxes” so as to allow the application of any segmentation method and visual descriptor. The proposed framework adopts a grouping approach in order to correct possible over- segmentation faults and a spatial feature called region proximity is introduced to describe regions topology in a visual scene by a block-based approach.
Using the MUVIS system, a prototype system of the proposed framework is implemented as a region-based feature extraction module, which integrates simple colour segmentation and region-based feature description based on colour and texture. The spatial region
proximity feature represents regions and describes their topology by a novel metric proposed in this thesis based on the block-based approach and average distance calculation.
After the region-based feature extraction step, a feature vector is formed which holds information about all image regions with their local low-level and spatial properties. During the retrieval process, those feature vectors are used for computing the (dis-)similarity distances between two images, taking into account each of their individual components. In this case a many-to-one matching scheme between regions characterised by a similarity maximisation approach is integrated into a query-by-example scheme.
Retrieval performance is evaluated between frame-based feature combination and the proposed framework with two different grouping approaches. Experiments are carried out on synthetic and natural image databases and the results indicate that a promising retrieval performance can be obtained as long as a reasonable segmentation quality is obtained. The integration of the region proximity feature further improves the retrieval performance especially for divisible, object-based image content.
Finally, frame-based and region-based texture extraction schemes are compared to evaluate the effect of a region on the texture description and retrieval performance utilising the proposed framework. Results show that significant degradations over the retrieval performance occur on region-based texture descriptors compared with the frame-based approaches
Advanced techniques for classification of polarimetric synthetic aperture radar data
With various remote sensing technologies to aid Earth Observation, radar-based imaging is one of them gaining major interests due to advances in its imaging techniques in form of syn-thetic aperture radar (SAR) and polarimetry. The majority of radar applications focus on mon-itoring, detecting, and classifying local or global areas of interests to support humans within their efforts of decision-making, analysis, and interpretation of Earth’s environment.
This thesis focuses on improving the classification performance and process particularly concerning the application of land use and land cover over polarimetric SAR (PolSAR) data. To achieve this, three contributions are studied related to superior feature description and ad-vanced machine-learning techniques including classifiers, principles, and data exploitation.
First, this thesis investigates the application of color features within PolSAR image classi-fication to provide additional discrimination on top of the conventional scattering information and texture features. The color features are extracted over the visual presentation of fully and partially polarimetric SAR data by generation of pseudo color images. Within the experiments, the obtained results demonstrated that with the addition of the considered color features, the achieved classification performances outperformed results with common PolSAR features alone as well as achieved higher classification accuracies compared to the traditional combination of PolSAR and texture features.
Second, to address the large-scale learning challenge in PolSAR image classification with the utmost efficiency, this thesis introduces the application of an adaptive and data-driven supervised classification topology called Collective Network of Binary Classifiers, CNBC. This topology incorporates active learning to support human users with the analysis and interpretation of PolSAR data focusing on collections of images, where changes or updates to the existing classifier might be required frequently due to surface, terrain, and object changes as well as certain variations in capturing time and position. Evaluations demonstrated the capabilities of CNBC over an extensive set of experimental results regarding the adaptation and data-driven classification of single as well as collections of PolSAR images. The experimental results verified that the evolutionary classification topology, CNBC, did provide an efficient solution for the problems of scalability and dynamic adaptability allowing both feature space dimensions and the number of terrain classes in PolSAR image collections to vary dynamically.
Third, most PolSAR classification problems are undertaken by supervised machine learn-ing, which require manually labeled ground truth data available. To reduce the manual labeling efforts, supervised and unsupervised learning approaches are combined into semi-supervised learning to utilize the huge amount of unlabeled data. The application of semi-supervised learning in this thesis is motivated by ill-posed classification tasks related to the small training size problem. Therefore, this thesis investigates how much ground truth is actually necessary for certain classification problems to achieve satisfactory results in a supervised and semi-supervised learning scenario. To address this, two semi-supervised approaches are proposed by unsupervised extension of the training data and ensemble-based self-training. The evaluations showed that significant speed-ups and improvements in classification performance are achieved. In particular, for a remote sensing application such as PolSAR image classification, it is advantageous to exploit the location-based information from the labeled training data.
Each of the developed techniques provides its stand-alone contribution from different viewpoints to improve land use and land cover classification. The introduction of a new fea-ture for better discrimination is independent of the underlying classification algorithms used. The application of the CNBC topology is applicable to various classification problems no matter how the underlying data have been acquired, for example in case of remote sensing data. Moreover, the semi-supervised learning approach tackles the challenge of utilizing the unlabeled data. By combining these techniques for superior feature description and advanced machine-learning techniques exploiting classifier topologies and data, further contributions to polarimetric SAR image classification are made. According to the performance evaluations conducted including visual and numerical assessments, the proposed and investigated tech-niques showed valuable improvements and are able to aid the analysis and interpretation of PolSAR image data. Due to the generic nature of the developed techniques, their applications to other remote sensing data will require only minor adjustments
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Tuning of Smart Multifunctional Polymer Coatings Made by Zwitterionic Phosphorylcholines
In the last years, the generation of multifunctional coatings has been moved into the focus of interface modifications to expand the spectrum of material applications and to introduce new smart properties. Herein a promising multifunctional and universally usable coating with simultaneous antifouling, easy-to-clean, and anti-fog functionality is presented based on smart polymer films consisting of copolymers with 2-methacryloyloxyethyl phosphorylcholine (MPC), realizing the function of the film and photoreactive 4-benzophenyl methacrylate (BPO), which is responsible for stability and crosslinking. The easy-to-clean effect is demonstrated qualitatively and quantitatively by oil droplet detachment experiments. The antifouling behavior against different germs is investigated by cell adhesion experiments. Furthermore the anti-fog performance is shown by breathing on the surfaces. To study the influence of the different amounts of copolymerized BPO, the grafted films are characterized by atomic force microscopy (AFM), infrared spectroscopy (ATR-FTIR), as well as contact angle measurements. In situ spectroscopic ellipsometry is performed to investigate the swelling behavior of the thin films as a function of the time of UV-irradiation. It is found that a degree of swelling of 15 and a water contact angle of less than 12° are the key parameters necessary for the generation of multifunctional coatings. © 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei
Das Experiment in Schule und Wissenschaft - ein „Nature of Science“ - Aspekt explizit in einem Projekt im Schülerlabor
Viele Schülerlabore verfolgen mehr oder weniger explizit das Ziel, Ansichten über Naturwissenschaften (engl. Nature of Science: NoS) von Schülerinnen und Schülern „positiv“ zu beeinflussen und somit das oft inadäquate Bild von Naturwissenschaften zu „verbessern“. Studien zeigten jedoch, dass adäquate Ansichten über NoS nicht ohne eine explizite Thematisierung vermittelt werden können, was in der Regel bei den meisten Schülerlaboren aber nicht erfolgt. Deshalb wurde ein Schülerlaborprojekt zur Plasmaphysik (Experimente mit der Plasmakugel) entwickelt, welches Wissen über Physik mit Reflexionen über NoS direkt verbindet und explizit thematisiert. Im Fokus stehen dabei Ansichten über die Erkenntnisgewinnung durch Experimente in Schule und Wissenschaft. Neben dem eigenen Experimentieren im Schülerlabor erhalten die Schülerinnen und Schüler Einblicke in „echte“ Labore und Arbeitsweisen der Forscher und diskutieren in Interviews mit diesen über Fachinhalte und Wege der Erkenntnisgewinnung. Abschließend werden die gewonnenen Eindrücke im Schülerlabor kritisch reflektiert und diskutiert. Im Beitrag werden das Projekt und Erfahrungen aus der Durchführung vorgestellt
Das Experiment in Schule und Wissenschaft - ein „Nature of Science“ - Aspekt explizit in einem Projekt im Schülerlabor
Viele Schülerlabore verfolgen mehr oder weniger explizit das Ziel, Ansichten über Naturwissenschaften (engl. Nature of Science: NoS) von Schülerinnen und Schülern „positiv“ zu beeinflussen und somit das oft inadäquate Bild von Naturwissenschaften zu „verbessern“. Studien zeigten jedoch, dass adäquate Ansichten über NoS nicht ohne eine explizite Thematisierung vermittelt werden können, was in der Regel bei den meisten Schülerlaboren aber nicht erfolgt. Deshalb wurde ein Schülerlaborprojekt zur Plasmaphysik (Experimente mit der Plasmakugel) entwickelt, welches Wissen über Physik mit Reflexionen über NoS direkt verbindet und explizit thematisiert. Im Fokus stehen dabei Ansichten über die Erkenntnisgewinnung durch Experimente in Schule und Wissenschaft. Neben dem eigenen Experimentieren im Schülerlabor erhalten die Schülerinnen und Schüler Einblicke in „echte“ Labore und Arbeitsweisen der Forscher und diskutieren in Interviews mit diesen über Fachinhalte und Wege der Erkenntnisgewinnung. Abschließend werden die gewonnenen Eindrücke im Schülerlabor kritisch reflektiert und diskutiert. Im Beitrag werden das Projekt und Erfahrungen aus der Durchführung vorgestellt
Collective Network of Binary Classifier Framework for Polarimetric SAR Image Classification: An Evolutionary Approach
Probing carbonyl–water hydrogen-bond interactions in thin polyoxazoline brushes
Temperature-responsive oxazoline-based polymer brushes have gained increased attention as biocompatible surfaces. In aqueous environment, they can be tuned between hydrophilic and hydrophobic behavior triggered by a temperature stimulus. This transition is connected with changes in molecule–solvent interactions and results in a switching of the brushes between swollen and collapsed states. This work studies the temperature-dependent interactions between poly(2-oxazoline) brushes and water. In detail, thermoresponsive poly(2-cyclopropyl-2-oxazoline), nonresponsive hydrophilic poly(2-methyl-2-oxazoline), as well as a copolymer of the two were investigated with in situinfrared ellipsometry. Focus was put on interactions of the brushes’ carbonyl groups with water molecules. Different polymer–water interactions could be observed and assigned to hydrogen bonding between C=O groups and water molecules. The switching behavior of the brushes in the range of 20–45°C was identified by frequency shifts and intensity changes of the amide I band
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Probing carbonyl-water hydrogen-bond interactions in thin polyoxazoline brushes
Temperature-responsive oxazoline-based polymer brushes have gained increased attention as biocompatible surfaces. In aqueous environment, they can be tuned between hydrophilic and hydrophobic behavior triggered by a temperature stimulus. This transition is connected with changes in molecule–solvent interactions and results in a switching of the brushes between swollen and collapsed states. This work studies the temperature-dependent interactions between poly(2-oxazoline) brushes and water. In detail, thermoresponsive poly(2-cyclopropyl-2-oxazoline), nonresponsive hydrophilic poly(2-methyl-2-oxazoline), as well as a copolymer of the two were investigated with in situ infrared ellipsometry. Focus was put on interactions of the brushes' carbonyl groups with water molecules. Different polymer–water interactions could be observed and assigned to hydrogen bonding between C=O groups and water molecules. The switching behavior of the brushes in the range of 20–45 °C was identified by frequency shifts and intensity changes of the amide I band
High Temperature Heat Pumps: Market Overview, State of the Art, Research Status, Refrigerants, and Application Potentials
This study reviews the current state of the art of high temperature heat pumps (HTHPs) with heat sink temperatures of 90 to 160°C. The focus is on the analysis of heat pump cycles, suitable refrigerants, and the operating ranges of commercially available HTHPs and heat pumps at the research status. More than 20 HTHP models from 13 manufacturers have been identified on the market that are able to provide heat sink temperatures of at least 90°C. Only a few heat pump suppliers have already managed to exceed 120°C. Large application potentials have been recognized particularly in the food, paper, metal, and chemical industries, especially in drying, pasteurizing, sterilizing, evaporation, and distillation processes. The heating capacities range from about 20 kW to 20 MW. The refrigerants used are mainly R245fa, R717, R744, R134a, and R1234ze(E). Most circuits are single-stage and differ primarily in the applied refrigerant and compressor type. Internal heat exchangers (IHX) are used to ensure sufficient superheating. Process optimization is achieved with economizer cycles or two-stage turbo compressors with intermediate vapor injection. Two-stage cascade cycles or open flash economizers are also used in commercial HTHPs. The COP values range from about 1.6 to 5.8 at temperature lifts of 130 to 40 K, respectively. Several research projects push the limits of the achievable COPs and heat sink temperatures to higher levels. Groups in Austria, Germany, France, Norway, the Netherlands, Switzerland, Japan, Korea, and China are active in the experimental research of HTHPs. Several laboratory scale HTHPs have been built to demonstrate the technical feasibility of sink temperatures above 120°C. The heat pump cycles examined are mainly single-stage and in some cases contain an IHX for superheating or an economizer for vapor injection into the compressor. The investigated refrigerants are R1336mzz(Z), R718, R245fa, R1234ze(Z), R600, and R601. R1336mzz(Z) enables exceptionally high heat sink temperatures of up to 160°C. The experimentally obtained COPs at 120°C heat sink temperature vary between about 5.7 and 6.5 at 30 K temperature lift and 2.2 and 2.8 at 70 K lift. New environmental friendly refrigerants with low GWP and improved components lead to a need for research on optimized cycles. The high level of research activity and the large number of demonstration R&D projects indicate that HTHPs with a heat sink temperature of 160°C will reach market maturity in the next few years. However, despite the great application potential, other competing heating technologies and most importantly low prices for fossil fuels are still hindering the wider spread of HTHPs in industry
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