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The synchronization of power generators is an important condition for the proper functioning of a power system, in which the fluctuations in frequency and the phase angle differences between the generators are sufficiently small when subjected to stochastic disturbances. Serious fluctuations can prompt desynchronization, which may lead to widespread power outages. Here, we model the stochastic disturbance by a Brownian motion process in the linearized system of the non-linear power systems and characterize the fluctuations by the variances of the frequency and the phase angle differences in the invariant probability distribution. We propose a method to calculate the variances of the frequency and the phase angle differences. For the system with uniform disturbance-damping ratio, we derive explicit formulas for the variance matrices of the frequency and the phase angle differences. It is shown that the fluctuation of the frequency at a node depends on the disturbance-damping ratio and the inertia at this node only, and the fluctuations of the phase angle differences in the lines are independent of the inertia. In particular, the synchronization stability is related to the cycle space of the network. We reveal the influences of constructing new lines and increasing capacities of lines on the fluctuations in the phase angle differences in the existing lines. The results are illustrated for the transmission system of Shandong Province of China. For the system with non-uniform disturbance-damping ratio, we further obtain bounds of the variance matrices., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Mathematical Physics

The synchronization stability of a complex network system of coupled phase oscillators is discussed. In case the network is affected by disturbances, a stochastic linearized system of the coupled phase oscillators may be used to determine the fluctuations of phase differences in the lines between the nodes and to identify the vulnerable lines that may lead to desynchronization. The main result is the derivation of the asymptotic variance matrices of the phase differences which characterizes the severity of the fluctuations. It is found that the cycle space of the graph of the system plays a role in this characterization. With theory of the cycle space, the effect of forming small cycles on the fluctuations is evaluated. It is proven that adding a new line or increasing the coupling strength of a line affects the fluctuations in the lines in any cycle including this line, while it does not affect the fluctuations in the other lines. In particular, if the phase differences at the synchronous state are not changed by these actions, then the affected fluctuations reduce., Mathematical Physics

This thesis mainly studies the causality in natural language processing. Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. In view of the lack of a dataset that can be used for causality-related research, in this thesis, we first build a first-of-its-kind, fine-grained causal reasoning dataset - FineCR, that contains new causality relations such as enable and prevent, with the help of human annotators. Our dataset contains human annotations of 25K cause-effect event pairs and 24K question-answering pairs within multi-sentence samples, where each can contain multiple causal relationships. To study current NLP models' ability to deal with the causality-related dataset and to figure out the problems that still exist, we define a series of NLP tasks based on FineCR, including causality detection, causality event extraction and causality question answering. Our experimental results with state-of-the-art deep learning models prove that there is still much room for improvement on those causal reasoning tasks. We found that those models have different shortcomings for different tasks. For the causality detection task, current classification models are easily affected by keywords, while the model cannot accurately extract the events for the causality event extraction task. And for the causality question answering task, it is sometimes difficult for the model to find the corresponding answer due to its inability to understand the semantics well. Those discoveries indicate the need to design better solutions to event causality research. In conclusion, our novel datasets and tasks provide a challenging benchmark for evaluating models' causal ability, and the experimental results shed light on future directions for improving neural language models., Computer Science

Elevation resolution is an important indicator in tomographic SAR imaging as it represents the ability to discriminate closed targets in elevation. In general, the elevation resolution is proportional to the length of the elevation aperture. However, as the elevation aperture increases, the geometric consistency of the image will undesirably deteriorate and hence fails the image coregistration approach required by the traditional super-resolution tomographic imaging. In this paper, a new super-resolution tomographic imaging method is proposed to overcome the inconsistency problem caused by the large elevation aperture. The core strategy is to get rid of two-dimensional image coregistration by applying a three-dimensional (3D) back projection like imaging manner: the 3D space is firstly divided into a 3D imaging grid, each of which is individually imaged via compressive sensing for super-resolution. The effectiveness of the proposed approach is evaluated by both computer simulations and real P-band UAV SAR data., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

Current news datasets merely focus on text features on the news and rarely leverage the feature of images, excluding numerous essential features for news classification. In this paper, we propose a new dataset, N24News, which is generated from New York Times with 24 categories and contains both text and image information in each news. We use a multitask multimodal method and the experimental results show multimodal news classification performs better than text-only news classification. Depending on the length of the text, the classification accuracy can be increased by up to 8.11%. Our research reveals the relationship between the performance of a multimodal classifier and its sub-classifiers, and also the possible improvements when applying multimodal in news classification. N24News is shown to have great potential to prompt the multimodal news studies., Water Resources, Web Information Systems

This thesis mainly studies the causality in natural language processing. Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. In view of the lack of a dataset that can be used for causality-related research, in this thesis, we first build a first-of-its-kind, fine-grained causal reasoning dataset - FineCR, that contains new causality relations such as enable and prevent, with the help of human annotators. Our dataset contains human annotations of 25K cause-effect event pairs and 24K question-answering pairs within multi-sentence samples, where each can contain multiple causal relationships. To study current NLP models' ability to deal with the causality-related dataset and to figure out the problems that still exist, we define a series of NLP tasks based on FineCR, including causality detection, causality event extraction and causality question answering. Our experimental results with state-of-the-art deep learning models prove that there is still much room for improvement on those causal reasoning tasks. We found that those models have different shortcomings for different tasks. For the causality detection task, current classification models are easily affected by keywords, while the model cannot accurately extract the events for the causality event extraction task. And for the causality question answering task, it is sometimes difficult for the model to find the corresponding answer due to its inability to understand the semantics well. Those discoveries indicate the need to design better solutions to event causality research. In conclusion, our novel datasets and tasks provide a challenging benchmark for evaluating models' causal ability, and the experimental results shed light on future directions for improving neural language models., Computer Science

Pumping is the most common technique used to transport fresh concrete in construction sites. The large-scale use of concrete all over the world makes the pumping increasingly important. A wide variety of additives and admixtures are incorporated into modern concrete in order for sustainable development. The performance of modern concrete is rather complex and its pumping behavior differs significantly from that of conventional concrete, especially in the fresh stage. This paper presents a comprehensive overview on the state of the art of concrete pumping. The models and methods used for characterizing the concrete pumpability and lubrication layer are described. The factors influencing the pumping behavior are discussed. A couple of ultra-high pumping engineering of concrete conducted in China are introduced., Accepted Author Manuscript, Materials and Environment

Rheological properties are of significant importance in successful placement and performance of self-compacting concrete (SCC). In this work, the rheological properties of SCC, combined with a powder-viscosity modifying admixture, were investigated based on a series of experimental studies. The modified Bingham model was applied to determine the rheological parameters and shear thickening behavior of SCC. The effects of mixing procedures, including charging sequence, mixing time and mixing speed, were analyzed. The results show that the shear thickening of SCC is reduced by first mixing the aggregate and water and then adding other raw materials. The direct contact between aggregate and water leads to a large amount of free water to be adsorbed by the aggregate system, resulting in an increase of the yield stress. In order to ensure an excellent fluidity and a low shear thickening behavior of SCC, the mixing time should be controlled at 4-5 min and the mixing speed at 30-45 r/min., Materials and Environment

Pumping is the most common technique used to transport fresh concrete in construction sites. The large-scale use of concrete all over the world makes the pumping increasingly important. A wide variety of additives and admixtures are incorporated into modern concrete in order for sustainable development. The performance of modern concrete is rather complex and its pumping behavior differs significantly from that of conventional concrete, especially in the fresh stage. This paper presents a comprehensive overview on the state of the art of concrete pumping. The models and methods used for characterizing the concrete pumpability and lubrication layer are described. The factors influencing the pumping behavior are discussed. A couple of ultra-high pumping engineering of concrete conducted in China are introduced., Accepted Author Manuscript, Materials and Environment

Rheological properties are of significant importance in successful placement and performance of self-compacting concrete (SCC). In this work, the rheological properties of SCC, combined with a powder-viscosity modifying admixture, were investigated based on a series of experimental studies. The modified Bingham model was applied to determine the rheological parameters and shear thickening behavior of SCC. The effects of mixing procedures, including charging sequence, mixing time and mixing speed, were analyzed. The results show that the shear thickening of SCC is reduced by first mixing the aggregate and water and then adding other raw materials. The direct contact between aggregate and water leads to a large amount of free water to be adsorbed by the aggregate system, resulting in an increase of the yield stress. In order to ensure an excellent fluidity and a low shear thickening behavior of SCC, the mixing time should be controlled at 4-5 min and the mixing speed at 30-45 r/min., Materials and Environment

In a high-power white light emitting diode (LED) package, the phosphor/silicone composite is typically used for photometric and colorimetric conversions, ultimately producing the white light. However, the phosphor/silicone composite is always exposed under harsh environments with high temperature, high blue light irradiation and high moisture when the LED operates. Therefore, its reliability issue has become one of the critical bottlenecks to improve the lifetime of a high-power white LED package. As the curing process and mechanical behavior of phosphor/silicone composite essentially determine its reliability, this paper firstly uses an in situ viscosity monitoring approach combined with Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy (FTIR) analysis to explain the curing mechanism of a phosphor/silicone composite by taking the effects of temperature and phosphor mass fraction into consideration. Then, the mechanical properties of phosphor/silicone composites aged under a long-term high moisture condition are evaluated by using the tensile test. Meanwhile, the finite element (FE) simulations, the Mori-Tanaka theoretical estimations and the microstructure analysis are applied to investigate the high moisture induced degradation mechanisms. The results show that: (1) the in situ measured isothermal viscosity curves of both pristine silicone and phosphor/silicone composites follow the Arrhenius empirical model, and high temperature and high phosphor mass fraction can increase the curing rate; (2) the hydrosilylation reaction between silicones determines the curing mechanism of phosphor/silicone composite; (3) the tensile test, FE simulation and Mori-Tanaka theoretical prediction results confirm that the Young's modulus of phosphor/silicone composite increases by gradually adding phosphors; and (4) the Young's modulus of phosphor/silicone composite increases after the high moisture ageing test, which can be attributed to the oxida, Electronic Components, Technology and Materials

In a high-power white light emitting diode (LED) package, the phosphor/silicone composite is typically used for photometric and colorimetric conversions, ultimately producing the white light. However, the phosphor/silicone composite is always exposed under harsh environments with high temperature, high blue light irradiation and high moisture when the LED operates. Therefore, its reliability issue has become one of the critical bottlenecks to improve the lifetime of a high-power white LED package. As the curing process and mechanical behavior of phosphor/silicone composite essentially determine its reliability, this paper firstly uses an in situ viscosity monitoring approach combined with Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy (FTIR) analysis to explain the curing mechanism of a phosphor/silicone composite by taking the effects of temperature and phosphor mass fraction into consideration. Then, the mechanical properties of phosphor/silicone composites aged under a long-term high moisture condition are evaluated by using the tensile test. Meanwhile, the finite element (FE) simulations, the Mori-Tanaka theoretical estimations and the microstructure analysis are applied to investigate the high moisture induced degradation mechanisms. The results show that: (1) the in situ measured isothermal viscosity curves of both pristine silicone and phosphor/silicone composites follow the Arrhenius empirical model, and high temperature and high phosphor mass fraction can increase the curing rate; (2) the hydrosilylation reaction between silicones determines the curing mechanism of phosphor/silicone composite; (3) the tensile test, FE simulation and Mori-Tanaka theoretical prediction results confirm that the Young's modulus of phosphor/silicone composite increases by gradually adding phosphors; and (4) the Young's modulus of phosphor/silicone composite increases after the high moisture ageing test, which can be attributed to the oxida, Electronic Components, Technology and Materials