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Monotonic and pulsating cyclic compression tests were performed systematically based on high density polyethylene (HDPE). The compressive creep behaviors were further implemented to compare with the ratcheting deformation under the same peak stress level. Monotonic compression experiments reveal that HDPE shows obvious four-stage characteristics which are sensitive to temperature, but independent of the stress rate when the temperature is greater than 80 °C. Interestingly, the strain range during the stage III always starts at 7.4% and ends at 62.6% under various temperatures and stress rates. Moreover, the compressive ratcheting behavior of HDPE significantly depends on temperature T, peak stress σp, stress rate σ˙, stress amplitude Δσ and stress ratio R, especially when T ≥ 80 °C, σp ≥15 MPa, σ˙ ≤0.1 MPa/s and R ≥ 0.8. Additionally, decreasing the stress rate or increasing the temperature will decrease the compressive modulus of HDPE. An approximate linear relationship between the creep strain rate and the ratcheting strain rate under different temperatures and stress ratios was observed. The compressive deformation characteristics of HDPE were compared with that of some other gasket materials, a universal phenomenon is found that the compressive ratcheting evolution with time can be characterized by creep approximately under the same loading peak stress, stress rate and temperature for various gasket materials when the stress ratio is greater than zero, which indicates that the ratcheting deformation for gaskets under cyclic loads may be estimated by the corresponding static creep strain in practical engineering.

Background and Objective: Radiofrequency ablation (RFA) is a safe and less invasive technique that uses an electric current to damage nerve tissue to stop it from sending pain signals. This study was aimed to determine the molecular mechanism of neuropathologic damage induced by RFA at different temperatures.Methods: A total of 36 Sprague Dawley rats were used as model with neuropathological injury. These rats were divided into six groups based on the temperature stimulation at 42°C, 47°C, 52°C, 57°C, 62°C, and 67°C. Conduction time, distance, and velocity were recorded after thermal injury. Hematoxylin and eosin staining was used to observe the histopathological changes of sciatic nerve. Neural ion channel proteins such as sodium voltage-gated channel alpha subunit 9 (SCN9A), sodium channel B3 subunit (SCN3B) and neurofascin (NFASC) expression in sciatic nerve tissue were detected detected by Western Blot.Results: Nerve conduction velocity (NCV) gradually decreased with the increase in temperature and neuronal damage was seen at 67°C. H&E staining showed increased degeneration of neurons with an increase in temperature from 47°C to 67°C. SCN9A and SCN3B expression at 57°C, 62°C, and 67°C was much higher; however, NFASC expression was lower at same temperatures.Conclusion: Neuropathological damage caused by RFA at different temperatures shows positive correlation with NCV. Heat transfer injury affects the expression of SCN9A, SCN3B, and NFASC in sciatic nerve tissue.

Summary: A growing number of governments are pledging to achieve net-zero greenhouse gas emissions by mid-century. Despite such ambitions, realized emissions reductions continue to fall alarmingly short of modeled energy transition pathways for achieving net-zero. This gap is largely a result of the difficulty of realistically modeling all the techno-economic and sociopolitical capabilities that are required to deliver actual emissions reductions. This limitation of models suggests the need for an energy-systems analytical framework that goes well beyond energy-system modeling in order to close the gap between ambition and reality. Toward that end, we propose the Emissions-Sustainability-Governance-Operation (ESGO) framework for structured assessment and transparent communication of national capabilities and realization. We illustrate the critical role of energy modeling in ESGO using recent net-zero modeling studies for the world's two largest emitters, China and the United States. This illustration leads to recommendations for improvements to energy-system modeling to enable more productive ESGO implementation.

Wind power forecasting involves data preprocessing and modeling. In pursuit of better forecasting performance, most previous studies focused on creating various wind power forecasting models, but few studies have been published with an emphasis on new types of data preprocessing methods. Effective data preprocessing techniques and the fusion with the physical nature of the wind have been called upon as potential future research directions in recent reviews in this area. Data enrichment as a method of data preprocessing has been widely applied to forecasting problems in the consumer data universe but has not seen application in the wind power forecasting area. This study proposes data enrichment as a new addition to the existing library of data preprocessing methods to improve wind power forecasting performance. A methodological framework of data enrichment is developed with four executable steps: add error features of weather prediction sources, add features of weather prediction at neighboring nodes, add time series features of weather prediction sources, and add complementary weather prediction sources. The proposed data enrichment method takes full advantage of multiple commercially available weather prediction sources and the physical continuity nature of wind. It can cooperate with any existing forecasting models that have weather prediction data as inputs. The controlled experiments on three actual individual wind farms have verified the effectiveness of the proposed data enrichment method: The normalized root mean square error (NRMSE) of the day-ahead wind power forecast of XGBoost and LSTM with data enrichment is 11% to 27% lower than that of XGBoost and LSTM without data enrichment. In the future, variations on the data enrichment methods can be further explored as a promising direction of enhancing short-term wind power forecasting performance.

Abstract Over the past twenty years, thin film lubrication (TFL) theory has been used to characterize the molecular behaviors in lubrication films thinner than 100 nm, effectively bridging the gap between elastohydrodynamic lubrication and boundary lubrication. Unfortunately, to date, the TFL molecular model proposed in 1996 has not been directly proven by experimental detection. Herein, a method based on surface-enhanced Raman spectroscopy was developed to show both the packing and orienting of liquid molecules in the TFL regime. By trapping liquid crystal molecules between a structured silver surface and a glass surface, molecular ordering states dominated by shear effect and surface effect were successfully distinguished. A nanosandwich structure consisting of an adsorbed layer, an ordered-molecule layer, and a fluid layer was demonstrated. Molecule imaging in TFL was achieved. Our results illustrate the molecular behaviors and lubrication mechanism in nanoconfined films and facilitate the lubrication design of nanoelectromechanical and microelectromechanical systems.

The channels may be formed in the unconsolidated sands reservoir due to formation failure during high-pressure water injection or frac-packing. Based on the continuum mechanics, a mathematical model has been established to simulate the formation process of big channels in unconsolidated sands reservoir during fluid injection. The model considers the effect of reservoir heterogeneity, solid particles erosion, and deposition. The dynamic formation process of channels around the borehole and its influencing factors are analyzed by this model. The results indicate that the seepage erosion plays a very significant role in the formation of the channels during fluid injection for the unconsolidated sands with extremely low strength. The formation of the channels is closely related to the duration of fluid injection, injection pressure, reservoir heterogeneity, formation plugging, and critical fluid velocity. The long channels are more likely to form as injection time increases. Higher injection pressure will lead to higher flow rate, thus eroding the solid particles and forming big channels. The increase of the rock strength will enhance the value of critical fluid velocity, which makes it difficult for the occurrence of erosional channelization. The near-wellbore damage of the formation will decrease the flow rate, and the preferential flow channels are less likely to be induced under the same injection pressure when compared with undamaged formation. In addition, we also found that the reservoir heterogeneity is essential to the formation of preferential flow channels. The channels are especially prone to be formed in the regions with high porosity and permeability at the initial time. The study can provide a theoretical reference for the optimal design of high-pressure water injection or frac-packing operation in the unconsolidated sands reservoir.

A high-quality methane emission estimation in China’s oil and gas sector is the basis of an effective mitigation strategy. Currently, the published emission data and studies of China’s oil and gas sector only provide estimations of total emissions, which is not enough for good analysis of the trend and impact factors for the instruction of emission mitigation activities. The main problem is that published data for oil and gas infrastructure in China is incomplete, which makes it difficult to apply the conventional greenhouse gas inventory compiling method and the uncertainty estimation strategy. Therefore, this paper aims to develop a method to estimate infrastructure data using all available data, including partial data for the infrastructure, national production and consumption of oil and gas, and production and production capacity data of oil and gas enterprises, and then uses a Monte Carlo-based method to generate a source-based inventory and uncertainty analysis of methane emission for China’s oil and gas industry from 1995 to 2018. We found that methane emission increased from 208.3 kt in 1995 to 1428.8 kt in 2018. Methane emission in 2018 has an uncertainty of about ±3%. Compared to former studies, our research found that the production stage of natural gas is the main contributor, which is further driven by the growth of natural gas production. The mitigation potential introduced by technology development on methane emission remains large.

This paper quantifies the exergy losses of coal-based series polygeneration systems and evaluates the potential efficiency improvements that can be realized by applying advanced technologies for gasification, methanol synthesis, and combined cycle power generation. Exergy analysis identified exergy losses and their associated causes from chemical and physical processes. A new indicator was defined to evaluate the potential gain from minimizing exergy losses caused by physical processes—the degree of perfection of the system’s thermodynamic performance. The influences of a variety of advanced technical solutions on exergy improvement were analyzed and compared. It was found that the overall exergy loss of a series polygeneration system can be reduced significantly, from 57.4% to 48.9%, by applying all the advanced technologies selected. For gasification, four advanced technologies were evaluated, and the largest reduction in exergy loss (about 2.5 percentage points) was contributed by hot gas cleaning, followed by ion transport membrane technology (1.5 percentage points), slurry pre-heating (0.91 percentage points), and syngas heat recovery (0.6 percentage points). For methanol synthesis, partial shift technology reduced the overall exergy loss by about 1.4 percentage points. For power generation, using a G-class gas turbine decreased the overall exergy loss by about 1.6 percentage points.

In response to climate change and to achieve global sustainable development, countries should accelerate the transition of their energy systems. In order to clearly understand the underlying mechanism of the transition, it is necessary to investigate the structural changes along energy flow processes and find the driving factors. This paper proposes a quantitative method based on energy allocation Sankey diagrams and index including total amount change, relative growth rate and occupation ratio change (TRO) to evaluate the structural changes of energy flow process and presents a case study of China from 2005 to 2015. Firstly, China’s energy flow process in 2015 was mapped from energy sources, intermediate conversion, end-use devices, passive systems to final services in the form of a Sankey diagram. Secondly, based on TRO index, this diagram was compared with a previous one of 2005 to reveal and evaluate structural changes in the past decade. Finally, the driving factors of these changes were discussed from different perspectives. The main changes from energy sources level are the reduction of coal and the increase of natural gas, from final services level are the reduction of thermal comfort demand and the increase of structural materials (especially that from chemical industry). The key factors driving these changes are the infrastructure construction of natural gas, rapid urbanization, improvement of energy efficiency of buildings and the people’s pursuit of high-quality life.

Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.

To systematically analyze energy-related carbon emissions from the perspective of comprehensive energy flow and allocate emissions responsibility, we introduce energy allocation analysis to carbon flow process based on Sankey diagrams. Then, to quantitatively compare different diagrams and evaluate the structural changes of carbon flow, we define changes from three dimensions including total amount change, relative growth rate and occupation ratio change (TRO), propose TRO index. The method is applied to China’s case study from 2005 to 2015. We map China’s energy-related carbon flow Sankey diagrams with high technical resolution from energy sources, intermediate conversion, end-use devices, passive systems to final services, and conduct TRO index decomposition by stages. The results indicate that in energy sources, the emission share of coal has declined due to energy transition although coal is still the largest contributor to China’s energy-related carbon emissions. In passive systems, the factory passive systems are the largest contributors, among them, emission reduction should focus on the steel, non-ferrous and chemical industries; the building passive systems should pay attention to household appliances; the vehicle passive systems should focus on cars. In final services, the demand for structural materials is the strongest driving force for carbon emissions growth.

Greenhouse gas emissions in China have been increasing in line with its energy consumption and economic growth. Major means for energy-related greenhouse gases mitigation in the foreseeable future are transition to less carbon intensive energy supplies and structural changes in energy consumption. In this paper, a bottom-up model is built to examine typical projected scenarios for energy supply and demand, with which trends of energy-related carbon dioxide emissions by 2050 can be analyzed. Results show that low-carbon technologies remain essential contributors to reducing emissions and altering emissions trends up to 2050. By pushing the limit of current practicality, emissions reduction can reach 20 to 28 percent and the advent of carbon peaking could shift from 2040 to 2030. In addition, the effect of electrification at end-use sectors is studied. Results show that electrifying transport could reduce emissions and bring the advent of carbon peaking forward, but the effect is less significant compared with low-carbon technologies. Moreover, it implies the importance of decarbonizing power supply before electrifying end-use sectors.

Malaysia is a rapidly developing country in Southeast Asia that aims to achieve high-income country status by 2020; its economic growth is highly dependent on its abundant energy resources, especially natural gas and crude oil. In this paper, a complete picture of Malaysia’s energy use from primary source to end use is presented by mapping a Sankey diagram of Malaysia’s energy flows, together with ongoing trends analysis of the main factors influencing the energy flows. The results indicate that Malaysia’s energy use depends heavily on fossil fuels, including oil, gas and coal. In the past 30 years, Malaysia has successfully diversified its energy structure by introducing more natural gas and coal into its power generation. To sustainably feed the rapidly growing energy demand in end-use sectors with the challenge of global climate change, Malaysia must pay more attention to the development of renewable energy, green technology and energy conservation in the future.

Increased glycolysis in tumor cells is associated with increased risk of tumor progression and mortality. Therefore, disruption of glycolysis, one of the main sources of cellular energy supply, can serve as a target for suppressing tumor growth and progression. Of note, hexokinase-2 (HK2) plays vital roles in glucose metabolism. Moreover, the expression of HK2 alters the metabolic phenotype and supports the continuous growth of tumor cells, making it an attractive target for cancer therapy. Quercetin (QUE), a bioactive flavonoid, has a profound anti-tumor effect on hepatocellular carcinoma (HCC), but the precise underlying mechanism of this effect is unclear. In the present study, we reported that QUE inhibited the proliferation of HCC cells that relied on aerobic glycolysis. We further found that QUE could decrease the protein levels of HK2 and suppress the AKT/mTOR pathway in HCC cells. In addition, QUE significantly restrained the growth of HCC xenografts and decreased HK-2 expression in vivo. Taken together, we have revealed that QUE suppresses the progression of HCC by inhibiting HK2-dependentglycolysis, which may have a promising potential to be an effective treatments for HCC, especially for those patients with high HK2 expression.

The energy embodied in construction services consumed by industrial sectors used to increase capacities has led to massive energy-related carbon emissions (ERCE). From the perspective of consumer responsibility, ERCE embodied in construction services is driven by technological changes and the increases in final demand of various sectors, including final consumption, fixed assets investment, and net export. However, little attention has been paid to decomposing sectoral responsibilities from this perspective. To fill this research gap, we propose a dynamic hybrid input–output model combined with structural decomposition analysis (DHI/O-SDA model). We introduce DHI/O modeling into the estimation of ERCE embodied in construction services from the perspective of consumer responsibility and introduce SDA into DHI/O models to improve the resolution of the estimate. Taking China as a case study, we verified the DHI/O-SDA model and present the bilateral relationships among sectoral responsibilities for ERCE embodied in construction services. A major finding is that the “Other Tertiary Industry„ sector is most responsible for ERCE embodied in construction services and strongly influences other sectors. Therefore, controlling the final demand increase of the service industry will be the most effective policy to reduce the ERCE embodied in construction services.

The energy embodied in construction services (EECS) to increase industrial production capacity, contributes to total primary energy consumption (TPEC) in developing countries like China. Forecasting EECS is important for creating energy policies, but has not received enough attention. There are some defects in the main two methods of EECS forecasting: the static hybrid input-output (HI/O) model and the dynamic HI/O model. The former cannot identify the quantity of construction services, whereas the latter is unstable for EECS forecasting. To tackle these problems, we propose a new model, which is a combination of the static and dynamic hybrid input-output model (CSDHI/O model), for EECS forecasting. Taking China as a case study, we forecast the EECS and TPEC of China until 2020 and analyze the sensitivities of four influencing factors. The results show that the EECS of China will reach 1.79 billion tons of coal equivalent in 2020. The improvement of fabrication level is identified as the most important factor for conserving both TPEC and EECS. A sudden drop in gross domestic product (GDP) growth rate and decreasing the investment in the service industry can also restrict EECS growth.

China has been experiencing a rapid urbanization and industrialization progress with continuous increase in primary energy consumption. Meanwhile, China’s changing economic and society structure also introduces huge uncertainty to its future energy demand. Many energy research institutes periodically publish projections of macro energy scenarios of China up to 2030 and 2050, but these projections differ from one another in terms of total amount of energy consumption and energy flows amongst sectors. In this work, we firstly illustrate major differences between existing scenarios based on a literature survey. We then compare and analyze the different projection methods, key policy assumptions, and other boundary conditions adopted in obtaining these scenarios. Then an index decomposition method is introduced with the purpose of decoupling the impacts of economic growth and population growth on the projection to energy consumption and greenhouse gas emissions. Our results illustrate that projections from domestic research institutes tend to be more optimistic regarding clean and sustainable utilization of coal in the future. Also, projections on energy consumption in China are exclusively linearly dependent on projections of economic and population growth in most scenarios, whilst in some other scenarios the impacts of oil price, international trade, and other drivers are also rather significant.

This paper attempts to present a complete picture of the status quo and future trends of the development of rural household energy in China based on a literature review and a systems analysis. First, a comprehensive literature review was conducted from the perspectives of energy consumption, carbon emissions and pollutants, energy resources, energy technologies, and energy policies. The review revealed the complexities and dynamics of the current system of rural household energy in China, and several key issues were identified for further attention. These issues are further explored by a systems analysis based on the “Integrated strategy of Sustainable development objectives, Decision-making systems, Operation systems, and Physical systems” (I-SDOP) concept. Following this method, a complete picture of the market status and policy targets is presented, by mapping an energy Sankey diagram and by reviewing the behavior of the main players. The results indicate that synergy of various energies, technologies, and players, and a combination of flexible engineering schemes and policy designs, with adequate consideration of temporal variation and regional disparity, are key strategies to promote the sustainable development of rural household energy, especially the distributed utilization of renewable energy, in China.

The development of district heating systems of corn straw densified fuel (CSDF-DHS) is an important option to promote the use of bioenergy on a large scale for sustainable development, especially in China. At present, China’s biomass densified solid fuel (BSDF) development lags behind previously planned target, main barriers of which are economic and policy support problems. Accurate case studies are key to analyze these problems. This manuscript takes Nong’an County in Jilin Province of China as an example to establish a techno-economic model to evaluate the economic performance of a CSDF-DHS under two policy scenarios. It calculates the economic performance under a benchmark market scenario (BMS) and the current policy scenario (CPS) and analyzes the influence of various policy instruments, including subsidies, carbon trading, and preferential taxation. The results indicate that: (1) The CSDF-DHS option is not competitive under the BMS or CPS compared to the traditional energy system based mainly on coal and liquefied petroleum gas; (2) Comparatively, the economic performance of corn straw briquette fuel (CSBF) is better than that of corn straw pellet fuel (CSPF); and (3) further policy support can make CSDF-DHSs competitive in the market, especially with subsidies for concentrated heating services and CSDF, carbon trading, and economic compensation to reduce the profit margin of enterprises, which can make both CSPF-DHSs and CSBF-DHSs competitive. The research results could provide scientific basis for relevant policy making and project decision.