Investigation of Gas Migration in saturated Argillaceous Rock

Gas migration in saturated argillaceous rock is studied in this work. Dependent on the pressure level the gas transport process is controlled by different mechanisms. Gas injection tests have been carried to investigate the gas transport process in low permeable argillaceous rock. We focus on the Opalinus Clay, which has been widely researched and is important for searching possible host rock of the radioactive waste disposal. Gas injection tests at different scales (laboratory, in-situ borehole and in-situ tunnel test) are intensively investigated in this work. The measurements of the tests are analysed and interpreted with numerical modelling method. A coupled multi-phase flow and mechanical model has been developed and implemented in the scientific computed codes OpenGeoSys (OGS). In the applied numerical model the relationship between capillary pressure and water saturation degree is described with van Genuchten model. The Darcy’s law is used for the phase flux, and the relative permeability of both water and gas phase is considered. The deformation process is calculated with elastic perfect-plastic model. The anisotropic hydraulic and mechanic behaviours of the Opalinus Clay are involved in the numerical model. The hydraulic anisotropy is controlled by the permeability tensor. The elastic deformation process is modelled by generalized Hooke’s law. The plastic behaviour is calculated with return mapping algorithm, and the anisotropy is considered with a so called microstructure tensor method. The permeability change during the gas injection is described using pressure dependent or deformation dependent approach. With considering the permeability evolution the measured data can be in the numerical model quantitatively represented, and test observations can be interpreted. Under laboratory condition it can be determined that the specimen permeability is reduced during compression. The significant permeability increase takes places when the gas injection pressure higher than the confining pressure. By the in-situ tests damage zone can be generated due to the drilling of boreholes and tunnel. The highly permeable areas dominate the hydraulic process. Fluid flows through the damaged zone into the not sealed section, e.g. the seismic observation boreholes by the in-situ borehole tests and the section out of the megapacker by the in-situ tunnel tests. In this work, the two phase flow controlled and pathway dilatancy controlled gas migration mechanisms are successfully simulated. The developed numerical model can be used to investigate the gas injection tests at different scales and conditions

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency

Investigation of Gas Migration in saturated Argillaceous Rock

Gas migration in saturated argillaceous rock is studied in this work. Dependent on the pressure level the gas transport process is controlled by different mechanisms. Gas injection tests have been carried to investigate the gas transport process in low permeable argillaceous rock. We focus on the Opalinus Clay, which has been widely researched and is important for searching possible host rock of the radioactive waste disposal. Gas injection tests at different scales (laboratory, in-situ borehole and in-situ tunnel test) are intensively investigated in this work. The measurements of the tests are analysed and interpreted with numerical modelling method. A coupled multi-phase flow and mechanical model has been developed and implemented in the scientific computed codes OpenGeoSys (OGS). In the applied numerical model the relationship between capillary pressure and water saturation degree is described with van Genuchten model. The Darcy’s law is used for the phase flux, and the relative permeability of both water and gas phase is considered. The deformation process is calculated with elastic perfect-plastic model. The anisotropic hydraulic and mechanic behaviours of the Opalinus Clay are involved in the numerical model. The hydraulic anisotropy is controlled by the permeability tensor. The elastic deformation process is modelled by generalized Hooke’s law. The plastic behaviour is calculated with return mapping algorithm, and the anisotropy is considered with a so called microstructure tensor method. The permeability change during the gas injection is described using pressure dependent or deformation dependent approach. With considering the permeability evolution the measured data can be in the numerical model quantitatively represented, and test observations can be interpreted. Under laboratory condition it can be determined that the specimen permeability is reduced during compression. The significant permeability increase takes places when the gas injection pressure higher than the confining pressure. By the in-situ tests damage zone can be generated due to the drilling of boreholes and tunnel. The highly permeable areas dominate the hydraulic process. Fluid flows through the damaged zone into the not sealed section, e.g. the seismic observation boreholes by the in-situ borehole tests and the section out of the megapacker by the in-situ tunnel tests. In this work, the two phase flow controlled and pathway dilatancy controlled gas migration mechanisms are successfully simulated. The developed numerical model can be used to investigate the gas injection tests at different scales and conditions

Artificial Intelligence Aided Receiver Design for Wireless Communication Systems

Physical layer (PHY) design in the wireless communication field realizes gratifying achievements in the past few decades, especially in the emerging cellular communication systems starting from the first generation to the fifth generation (5G). With the gradual increase in technical requirements of large data processing and end-to-end system optimization, introducing artificial intelligence (AI) in PHY design has cautiously become a trend. A deep neural network (DNN), one of the population techniques of AI, enables the utilization of its ‘learnable’ feature to handle big data and establish a global system model. In this thesis, we exploited this characteristic of DNN as powerful assistance to implement two receiver designs in two different use-cases. We considered a DNN-based joint baseband demodulator and channel decoder (DeModCoder), and a DNN-based joint equalizer, baseband demodulator, and channel decoder (DeTecModCoder) in two single operational blocks, respectively. The multi-label classification (MLC) scheme was equipped to the output of conducted DNN model and hence yielded lower computational complexity than the multiple output classification (MOC) manner. The functional DNN model can be trained offline over a wide range of SNR values under different types of noises, channel fading, etc., and deployed in the real-time application; therefore, the demands of estimation of noise variance and statistical information of underlying noise can be avoided. The simulation performances indicated that compared to the corresponding conventional receiver signal processing schemes, the proposed AI-aided receiver designs have achieved the same bit error rate (BER) with around 3 dB lower SNR

Service Life Prediction of Basalt Fiber Reinforced Concrete under Salt Freeze-thaw Cycles

To address the reduced durability of concrete structures under salt freeze-thaw erosion in Northwest China, basalt fiber reinforced concrete and common concrete with different mixing amounts were selected to predict their service life in three freeze-thaw conditions. Results showed that the damage on concrete under fresh water freeze-thaw condition is lower than that caused by salt freeze-thaw erosion, the addition of basalt fiber can effectively slow down the degradation of mechanical properties of concrete under salt freeze-thaw erosion, and the lowest degradation rate is reached when the content of basalt fiber is 0.15%. Fiber hinders the expansion of cracks and reduces the pores, and in turn improves the frost resistance durability of concrete. The service life prediction results obtained with Gray Model and Weibull Model are roughly similar, among which, Gray Model needs less sample volume, while Weibull Model presents more accurate prediction results

Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation

Most recent approaches use the sequence-to-sequence model for paraphrase generation. The existing sequence-to-sequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words. Therefore, the generated sentences are often grammatically correct but semantically improper. In this work, we introduce a novel model based on the encoder-decoder framework, called Word Embedding Attention Network (WEAN). Our proposed model generates the words by querying distributed word representations (i.e. neural word embeddings), hoping to capturing the meaning of the according words. Following previous work, we evaluate our model on two paraphrase-oriented tasks, namely text simplification and short text abstractive summarization. Experimental results show that our model outperforms the sequence-to-sequence baseline by the BLEU score of 6.3 and 5.5 on two English text simplification datasets, and the ROUGE-2 F1 score of 5.7 on a Chinese summarization dataset. Moreover, our model achieves state-of-the-art performances on these three benchmark datasets.Comment: arXiv admin note: text overlap with arXiv:1710.0231

Distributed localization of a RF target in NLOS environments

We propose a novel distributed expectation maximization (EM) method for non-cooperative RF device localization using a wireless sensor network. We consider the scenario where few or no sensors receive line-of-sight signals from the target. In the case of non-line-of-sight signals, the signal path consists of a single reflection between the transmitter and receiver. Each sensor is able to measure the time difference of arrival of the target's signal with respect to a reference sensor, as well as the angle of arrival of the target's signal. We derive a distributed EM algorithm where each node makes use of its local information to compute summary statistics, and then shares these statistics with its neighbors to improve its estimate of the target localization. Since all the measurements need not be centralized at a single location, the spectrum usage can be significantly reduced. The distributed algorithm also allows for increased robustness of the sensor network in the case of node failures. We show that our distributed algorithm converges, and simulation results suggest that our method achieves an accuracy close to the centralized EM algorithm. We apply the distributed EM algorithm to a set of experimental measurements with a network of four nodes, which confirm that the algorithm is able to localize a RF target in a realistic non-line-of-sight scenario.Comment: 30 pages, 11 figure