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Shale gas loss by leakage directly affects the accurate measurement of shale gas content during drilling and coring. To accurately calculate shale gas loss, in combination with the actual situation of the shale coring, considering the influence factors of the main occurrence state of shale gas (free state and adsorption state), by means of treating the three stages of the shale well core removal, ground exposure, and water bath heating and desorption as a process of desorption that changes with confining pressure, an indoor shale gas loss simulation experiment method was independently designed to determine shale gas loss. Two sets of samples with large differences in physical properties in eastern Sichuan were selected for the shale gas loss simulation experiment. We proposed to use the error reduction rate of shale gas loss (the percentage of the difference between the shale gas loss obtained by the simulation experiment method and the rate obtained by the improved USBM method and curve fitting method and the amount of gas loss of core injected) to verify the accuracy of the simulation experiment method. The results show that compared with the improved USBM method, the average error reduction rate of cores by the experiment method were: 8.64%. Compared with the curve fitting method, the average error reduction rate of cores by the experiment method were 25.11%, which proved that the shale gas loss simulation experiment method had higher accuracy.

Introduction: In order to promote the consumption of renewable energy, reduce carbon emissions, and take into account the uncertainty of renewable energy output and load fluctuations in the new power system that can affect the normal operation of market mechanism, a two-stage low-carbon optimization scheduling method for power system that considers demand response under multiple uncertainties is proposed in this paper.Methods: Uncertain scene sets are generated through Latin hypercube sampling and heuristic synchronous backpropagation method is used to reduce scenes to obtain typical scenes and their probabilities. Then, a one-stage optimization model is established with the goal of maximizing energy efficiency and corresponding demand response strategies are obtained. Green certificate carbon trading joint mechanism model consisting of tiered green certificate trading and time-sharing tiered carbon trading are established, and the output of two-stage units are optimized with the goal of minimizing comprehensive operating costs.Result: The simulation results show that the carbon emissions are decreased by 251.57 tons, the consumption rate of renewable energy is increased by 8.64%, and the total costs are decreased by 124.0612 million yuan.Discussion: From this, it can be seen that the dual layer low-carbon optimization scheduling strategy for power system considering demand response under multiple uncertainties can effectively reduce the operating costs and carbon emissions of the system, while balancing the economic and environmental aspects of power system operation.

This study explores the impact of public concerns on green innovation in China’s automotive industry and examines whether the effect varies based on firm size, ownership, and time phase. The study investigates 151 automobile enterprises and provides a novel, large-scale, and data-based perspective and estimation method for exploring critical factors of green innovation. By applying transition probabilities matrix (TPM) model, this paper finds that for different-sizes automotive enterprises there are significant differences in innovation sustainability, non-innovation sustainability, and liquidity between innovation and non-innovation, and such differences also exist for state-owned and non-state-owned enterprises. Then, based on the dynamic panel random probit (DPRP) model, the paper further analyzes the possible reasons for these differences, and particularly focuses on exploring the impact of public environmental concern on the environmental technology innovation. The empirical results show: 1) public concerns encourages green innovation emerging in all automotive firms, but only affects innovation persistence in medium and large companies. 2) public concerns encourages non-innovator state-owned companies to become innovators and motivates them to maintain continuous innovation. 3) the impact of public concerns changes over time. In the periods of 2002–2007 and 2012–2013, the role of public concerns is not significant. However, in the 2007–2012 period, public concerns significantly stimulate enterprises to move from non-innovators to innovators and promotes continuous innovation.

Lithium-ion batteries are widely employed in industries and daily life. Research on the state of health (SOH) of batteries is essential for grasping the performance of batteries, better guiding battery health management, and avoiding safety mishaps caused by battery aging. Nowadays, most research adopts a data-driven artificial intelligence approach to assess SOH. However, the majority of approaches are based on entire voltage, current, or temperature curves. In reality, voltage, current, and temperature are frequently presented in segments, leading to the limited flexibility and slow analysis speed of the traditional techniques. This study solves the problem by dividing the whole voltage curve into many typical kinds of segments with equal timescales based on different typical voltage beginning points. On this foundation, the temporal convolution network (TCN) is used to create a sub-model of SOH estimation for several typical kinds of segments. In addition, the sub-models are fused using the bootstrap aggregating (Bagging) approach to boost accuracy. Finally, this research uses a publicly available dataset from Oxford to demonstrate the effectiveness of the suggested strategy.

The electrical machine is one of the key components for submerged liquefied natural gas (LNG) pumps. This study deals with a cryogenic permanent magnet synchronous motor (CPMSM) for submerged LNG pumps. An 18.5-kW CPMSM prototype was developed according to the needs of users. The basic design of the CPMSM was proposed by using a cryogenic temperature (CT) design method. To analyze the operational performance accurately, simulation modeling and analysis are carried out, and a liquid nitrogen (−196°C) experimental platform is built. The test results verify the rationality of the design and the accuracy of the simulation. Based on the simulation and experimental data, the working characteristics and mechanical properties of the prototype in liquid nitrogen are analyzed. In addition, the performance of the prototype operating in liquid nitrogen (−196°C) and LNG (−161°C) are compared and analyzed, and the results show that the operating characteristics of the prototype in the two fluid environments are similar.

Transactive energy systems (TESs) combine both economical and control mechanisms, and have become promising solutions to integrate distributed energy resources (DERs) in modern power systems. This article will introduce the basic concept of a TES, including its definition, process, time scale, and benefits. The configuration of the TES is then described in detail from the perspectives of the physical system, information system, transaction system, and regulatory system. The transaction mechanism allows participants (e.g., customer, generator, transmission operator, marketer, etc.) to conduct various transactions with any other party to the extent that regulatory policy permits. Transactive control is regarded as one of the most advanced approaches to realize the full response potential of flexible devices and respect the end user’s privacy, preference, and free will. Finally, some challenges to the development of TESs that arise from the limitations of current equipment level and methodological concepts will be discussed. In summary, TESs provide a more efficient, fair, and transparent environment for participants to promote DERs utilization, improve market efficiency, and increase economic benefits.

Pretreatment of lignocellulosic biomass is a prerequisite to overcome recalcitrance and allow enzyme accessibility to cellulose and maximize product recovery for improved economics of second-generation lignocellulosic bio-refineries. Recently, the three US-DOE funded Bioenergy Research Centers (Joint Bioenergy Institute (JBEI), Great Lakes Bioenergy Research Center (GLBRC), and BioEnergy Science Center (BESC)) compared ionic liquid (IL), dilute sulfuric acid (DA), and ammonia fiber expansion (AFEXTM) pretreatments and published comparative data on mass balance, total sugar yields, substrate accessibility, and microbial fermentation (Biotechnology for Biofuels 7: 71; 72 (2014)). In this study, corn stover solids from IL, DA, and AFEX pretreatments were compared to gain comprehensive, in-depth understanding of induced morphological and chemical changes incorporated to corn stover, and how they overcome the biomass recalcitrance. These studies reveal that biomass recalcitrance is overcome by combination of structural and chemical changes to carbohydrates and lignin after pretreatment. Thermal analysis indicates that AFEX and IL pretreated corn stover showed a lower thermal stability while DA pretreated corn stover showed the opposite. The surface roughness variations measured by SANS were correlated to the removal and redistribution of biomass components and was consistent with compositional analysis, AFM and confocal fluorescence imaging results. With AFM and confocal fluorescent microscopy, lignin was found to be re-deposited on cellulose surface with average cellulose fiber width significantly decreased for DA pretreated corn stover (one third of IL and AFEX). HSQC NMR spectra revealed a ~17.9% reduction of β-aryl ether units after AFEX, ~59.8% reduction after DA and >98% reduction after IL. Both NMR and SEC showed similar patterns of lignin depolymerization with highest degree of depolymerization observed for IL followed with DA and AFEX.

Distributions of pore pressure and water saturation in matrix around fractures after hydraulic fracturing and shut-in period will impact the shale gas well production significantly. However, the influences of hydraulic fracturing and shut-in period on pore pressure and water saturation are not considered in the classical reservoir simulations. In this work, the embedded discrete fracture model (EDFM), which is convenient to be coupled with an existing reservoir simulator with high computational efficiency, was employed to simulate the hydraulic fracture propagation coupled with matrix flow. Then, we developed a model for simulating the integration process of hydraulic fracturing, shut-in period, and well production based on the dual media theory. Distributions of pore pressure and water saturation varying in different periods and the production decline of shale gas well were obtained through the integrated simulation model. The calculation result was validated by the field bottom hole pressure data of a shale gas well in Sichuan Province, China. Simulation results show that the variation of bottom hole pressure is not smooth during the fracture propagation process because the initiations of different fractures are not simultaneous. The fracturing fluid flow-back rate of shale gas well is much lower than that of conventional reservoirs. There is still a large amount of fracturing fluid retained in micro-fracture systems and matrix of shale after production. It is also found that the permeability of the micro-fracture system determines the drop rate of bottom hole pressure and the size of stimulated reservoir volume (SRV) determines the decrease amplitude of bottom hole pressure.

Cosmic-ray muons are a type of natural radiation with high energy and a strong penetration ability. The flux distribution of such particles at sea level is a key problem in many areas, especially in the field of muon imaging and low background experiments. This paper summarizes the existing models to describe sea-level muon flux distributions. According to different means used, four parametric analytical models and one Monte Carlo model, which is referred to as CRY, are selected as typical sea-level muon flux distribution models. Then, the theoretical values of sea-level muon fluxes given by these models are compared with the experimental sea-level muon differential flux data with kinetic energy values in the range of 1–1,000 GeV in the directions of zenith angles 0° and 75°. The goodness of fit of these models to the experimental data was quantitatively calculated by Pearson’s chi-square test. The results of the comparison show that the commonly used Gaisser model overestimates the muon flux in the low-energy region, while the muon flux given by the Monte Carlo model CRY at the large zenith angle of 75° is significantly lower than that of the experimental data. The muon flux distribution given by the other three parametric analytical models is consistent with the experimental data. The results indicate that the original Gaisser model is invalid in the low energy range, and CRY apparently deviates at large zenith angles. These two models can be substituted with the muon flux models given by Gaisser/Tang, Bugaev/Reyna, and Smith and Duller/Chatzidakis according to actual experimental conditions.