ALBERT

Description: Urban areas play an important role in the global carbon cycle, and human-induced carbon emissions from urban areas urgently need to be reduced. Therefore, understanding the relationship between carbon sources and sinks is the first step toward mitigating the effect of urban areas on climate change. Combined with the land use and land cover (LULC) empirical coefficients and statistical methods, urban carbon and oxygen balances in Beijing were evaluated. In this study, the carbon sequestration and oxygen emission capabilities of various LULC types were calculated, and the partitioning of carbon emissions and oxygen consumption in Beijing were estimated. The evaluation results indicated that the ecosystem services from the LULC in an area were not adequate to offset the urban carbon emissions and oxygen consumption. The areas with a high capacity for carbon sequestration and oxygen emissions were primarily distributed in the exurban districts of Beijing, and the carbon and oxygen balances in the exurban districts were superior to those of core urban areas. Industrial fossil fuel consumption dominated all of the human-induced carbon sources. The methods developed in this research were shown to be viable for the quantitative evaluation of urban ecosystem carbon and oxygen balances.

Description: A plasmonic temperature-sensing structure, based on a metal-insulator-metal (MIM) waveguide with dual side-coupled hexagonal cavities, is proposed and numerically investigated by using the finite-difference time-domain (FDTD) method in this paper. The numerical simulation results show that a resonance dip appears in the transmission spectrum. Moreover, the full width of half maximum (FWHM) of the resonance dip can be narrowed down, and the extinction ratio can reach a maximum value by tuning the coupling distance between the waveguide and two cavities. Based on a linear relationship between the resonance dip and environment temperature, the temperature-sensing characteristics are discussed. The temperature sensitivity is influenced by the side length and the coupling distance. Furthermore, for the first time, two concepts—optical spectrum interference (OSI) and misjudge rate (MR)—are introduced to study the temperature-sensing resolution based on spectral interrogation. This work has some significance in the design of nanoscale optical sensors with high temperature sensitivity and a high sensing resolution.

Description: As one of the most effective approaches in dealing with the energy crisis, combined electricity and natural gas systems have become more and more popular worldwide. To take full advantages of such hybrid energy networks, a proper operation and control method is required. In this paper, a novel approach coordinating combined heating and power generation is proposed. First, state excursion rate, a criterion describing the deviation of system operation, is defined for system state evaluation. Then, thermal energy storage is allocated to provide more and better operation modes for combined generation. By investigating the state excursion rate of hybrid energy systems, the optimal operation mode is chosen through an analytical strategy. Case studies on hybrid energy networks show that all state variables, including voltages in electric systems and pressures in gas networks, are adjusted to follow proper operation constraints by the implementations of the proposed strategy. In addition to providing sufficient auxiliary services for hybrid systems, it is also possible to maintain the economic and energy-efficient benefits of energy supply. This study provides an effective method to utilize the regulation capability of combined heating and power generations, which is a technical basis of energy internet.

Description: Remote Sensing, Vol. 10, Pages 622: A Framelet-Based Iterative Pan-Sharpening Approach Remote Sensing doi: 10.3390/rs10040622 Authors: Zi-Yao Zhang Ting-Zhu Huang Liang-Jian Deng Jie Huang Xi-Le Zhao Chao-Chao Zheng Pan-sharpening is used to fuse multispectral images and panchromatic images to produce a multispectral image with high spatial resolution. In this paper, we design a new iterative method based on framelet for pan-sharpening. The proposed model takes advantage of the upsampled multispectral image and a linear relation between the panchromatic image and the latent high-resolution multispectral image. Since the sparsity of the pan-sharpened image under a B-spline framelet transform is assumed, we regularize the model by penalizing l 1 norm of a framelet based term. The model is solved by a designed algorithm based on alternating direction method of multipliers (ADMM). For better performance, we propose an iterative strategy to pick up more spectral and spatial details. Experiments on four datasets demonstrate that the proposed method outperforms several existing pan-sharpening methods.

Description: Materials, Vol. 11, Pages 492: Synthesis and Characterization of Highly Sensitive Hydrogen (H2) Sensing Device Based on Ag Doped SnO2 Nanospheres Materials doi: 10.3390/ma11040492 Authors: Zhaorui Lu Qu Zhou Lingna Xu Yingang Gui Zhongyong Zhao Chao Tang Weigen Chen In this paper, pure and Ag-doped SnO2 nanospheres were synthesized by hydrothermal method and characterized via X-ray powder diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectra (XPS), respectively. The gas sensing performance of the pure, 1 at.%, 3 at.%, and 5 at.% Ag-doped SnO2 sensing devices toward hydrogen (H2) were systematically evaluated. The results indicated that compared with pure SnO2 nanospheres, Ag-doped SnO2 nanospheres could not only decrease the optimum working temperature but also significantly improve H2 sensing such as higher gas response and faster response-recovery. Among all the samples, the 3 at.% Ag-doped SnO2 showed the highest response 39 to 100 μL/L H2 at 300 °C. Moreover, its gas sensing mechanism was discussed, and the results will provide reference and theoretical guidance for the development of high-performance SnO2-based H2 sensing devices.

Description: Energies, Vol. 10, Pages 2022: Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine Energies doi: 10.3390/en10122022 Authors: Zhongyong Zhao Chao Tang Qu Zhou Lingna Xu Yingang Gui Chenguo Yao A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.

Description: An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs) and demanders (represented by DisCOs) compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP) and each rival’s bidding strategy as common knowledge (in dynamic game market models), and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models), which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC) algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n). The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare compared with traditional reinforcement learning methods.

Description: Materials, Vol. 11, Pages 248: Optimized Calibration Procedure of the Damage Parameters of AA6082-T6 Sheets Materials doi: 10.3390/ma11020248 Authors: Fan Xu Hao Zhang Shengdun Zhao Chao Chen Miao Cao Wei Chen The constitutive equation of AA6082-T6 sheets is investigated by an extended Rousselier damage model. Previous research is mainly comprised of single-pull test specimens, notched tensile specimens, tensile specimens with a hole, and shear specimens. To decrease the natural material errors, a new specimen is used. In this paper, a clinched joint is regarded as a specimen to calibrate the initial void volume fraction k ω and the shear damage parameter f 0 by using the orthogonal analysis method, which can reduce the simulation times and accuracy. It also reveals that the initial void volume fraction f 0 affects the void volume fraction in the neck and the groove of the clinched joint, and the shear damage parameter k ω affects just the void volume fraction f in the neck of the clinched joint. It checks the force-displacement curve, shape of the clinched joint, and the fracture location, and approves that these damage parameters can describe the deformation process, fracture location, and shape of the clinched joint.

Description: Remote Sensing, Vol. 10, Pages 403: An Orthogonal Projection Algorithm to Suppress Interference in High-Frequency Surface Wave Radar Remote Sensing doi: 10.3390/rs10030403 Authors: Zezong Chen Fei Xie Chen Zhao Chao He High-frequency surface wave radar (HFSWR) has been widely applied in sea-state monitoring, and its performance is known to suffer from various unwanted interferences and clutters. Radio frequency interference (RFI) from other radiating sources and ionospheric clutter dominate the various types of unwanted signals because the HF band is congested with many users and the ionosphere propagates interference from distant sources. In this paper, various orthogonal projection schemes are summarized, and three new schemes are proposed for interference cancellation. Simulations and field data recorded by experimental multi-frequency HFSWR from Wuhan University are used to evaluate the cancellation performances of these schemes with respect to both RFI and ionospheric clutter. The processing results may provide a guideline for identifying the appropriate orthogonal projection cancellation schemes in various HFSWR applications.