The development of tight oil reservoirs has made remarkable progress all over the world currently, but how to quickly and accurately forecast the production decline trend of the single well after fracturing is quite a huge challenge in practical terms. Based on the production characteristics of tight oil reservoirs after fracturing during natural depletion and the fractional flow equation, as well as combined with the material balance equation and the Arps exponential decline model, a novel and practical method for production decline analysis (PDA) of the single well during natural depletion in tight reservoirs after fracturing was proposed. Then, a production well (JX) from the tight oil block X in the Junggar basin of China was selected as the case well for application and the production decline curve of the JX well was calculated and forecasted. Compared with the Logistic model and actual production data from the field, the accuracy of the practical PDA method was verified, the economic recoverable reserves and the corresponding oil recovery factor of the JX well were further predicted. The novel PDA method is of great help for field engineers to evaluate the current production status of oil wells and predict their future production trends quickly and conveniently.
Ammonia (NH3) has been reported as promising hydrogen storage media for clean fuel applications and is widely used as a reductant in selective catalytic reduction (SCR) systems. With such a huge potential in various environmental-friendly applications, however, ammonia is facing several challenges in its storage and delivery feasibility. In this study, we have designed three-dimensional (3D) printed zeolite NaX (faujasite)-magnesium chloride (MgCl2) structured units by the pressure-assisted micro-syringe method. The 3D printed unit consists of a NaX scaffold and MgCl2 blocks located inside, where the NaX scaffold provides the space to accommodate the volume swing during ammonia adsorption-desorption cycles, MgCl2 to Mg(NH3)6Cl2 to MgCl2. The 3D printed unit demonstrates a net-zero structural change and offers structural stability during ammonia adsorption-desorption cycles. Moreover, by combining the zeolite and metal ammine complexes, we demonstrate that physisorption and chemisorption of ammonia occur in structured units and offer high sorption capacity and rapid kinetics in ammonia adsorption and desorption.
Flue gas recirculation (FGR), which can regulate the heat transfer characteristics of double-reheat boilers, has received widely attention. The effect of FGR on heat flux distribution and heat absorption on heating area was investigated by numerical simulation based on a 660 MW tower-type double-reheat boiler. The results showed that when the FGR ratio increases, the heat flux in boiler ash hopper are decreased, and the area with high heat flux (260-330 kW m-2) is reduced. The heat absorption in water-cooled wall zone is decreased, while that of reheater, superheater and economizer zone is increased once the RFG ratio increases.
In this paper, flow and heat transfer characteristics of microalgae slurry in the absorber tube of a solar-driven parabolic trough collector was studied numerically. Several viscosity models were introduced to describe the rheological property which would determine the flow pattern. Meanwhile the proposed model accomplished with the temperature term was optimized by the experimental data. Different thermal conductivities were employed to improve the heat transfer process which was described in the cases of different microalgae concentrations and heat fluxes. The relevant results reveal that the temperature field dominates the viscosity discrepancy in the dilute microalgae slurry while the shear thinning effect will be enhanced with the increasing microalgae condensation. The established model is supposed to represent the non-Newtonian pseudo-plastic fluid flow in the hydrothermal pretreatment system which will introduce a direct method to investigate the heat transfer process. Hence the enhanced heat transfer techniques could be applied to accelerate the recovery techniques of solar energy by microalgae hydrothermal utilization.
The energy visualization technology of smart homes not only brings convenience to users, but also strives to minimize energy consumption and maximize household electricity efficiency. In this paper, we first discuss the different energy visualization technologies, applications and methods under this topic, and analyze the key points of their advantages. Secondly, the paper proposes a simple smart home energy management system. Being convenient for users and energy managers, the system guides users to change their electricity consumption habits through self-motivation and comparison with other, saves energy consciously and improves energy efficiency.
The durability of Proton exchange membrane fuel cell (PEMFC) is one of the technical challenges restricting its commercial application. In order to enhance the reliability and durability of PEMFC, a feature extraction method based on bi-direction long short-term memory (Bi-LSTM) and bi-direction gated recurrent unit (Bi-GRU) is proposed in this paper, which can effectively extract deeper degradation features. Feature extraction model linked with echo state network (ESN), which form a fusion prognostic framework to realize short-term degradation prediction and remaining useful life (RUL) estimation. For short-term prediction, only the first 200 hours of voltage degradation data were used for training can achieve an acceptable and accurate prediction, which the root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) are 0.0235, 0.0195 and 0.9822, respectively. Comparing with traditional machine learning methods, proposed fusion prognostic framework shows the best predictive performance. Besides, a 100-step sliding windows method based on the fusion prognostic framework is used to implement RUL estimation. The results show that the percentage error (𝐸𝑟) is only 1.22% with the first 200 hours training data. The proposed method has great significance for guiding online testing and health management of PEMFC.
Based on the heat demand of users, adjusting the water supply temperature and regulating the heating system can achieve matching the heat dissipation of heat dissipation equipment of heat users with the demand heat load of users and prevent energy wastage caused by high room temperature. This paper proposes a model and method for determining the water supply temperature of heat sources based on load and flow constraints for specific engineering cases, and uses LSTM deep neural network and multiple regression to simulate and analyze the water supply temperature. The results show that the deviation of LSTM is 7.22% compared to the actual value, which is much lower than the 18.20% of multiple regression.
Electric energy conservation is meaningful for the
development of any country. The roads in a city are
equipped with street lights. After midnight, many
pedestrians and vehicles are greatly reduced in these
places, while all street lights still working. Therefore, it is
important to apply more effective and energy-saving
methods to road lighting systems. To solve this problem,
many intelligent street lights have been designed. This
paper summarizes the current status of smart street light
technology and analyzes their advantages and
disadvantages. Thereafter, it proposes a segmented
management system of intelligent street lights based on
wireless communication technologies and sensor
technologies. This design will improve the flexibility and
practicability of the intelligent street light systems.
As one of the important energy systems, heating systems often suffer hydraulic imbalances and high energy consumptions in district heat networks. To further reduce the operational energy consumption of pumps and achieve hydraulic balance, the utilization of nonlinear programming algorithms for hydraulic optimization of district heat networks was proposed. With the actual heating system of a university as a use case, a dynamic hydraulic optimization model was established using the nonlinear programming algorithm to optimize the pump frequency, valve opening and thermal inlet flow rate. The actual data (from 2019 to 2020 and from 2020 to 2021) were selected for the simulation and comparison of the difference between the simulated energy consumption and the actual one by using four different dynamic regulation methods. The results reveal that with the dynamic regulation under day-by-day, day-night, time-by-time, and large temperature difference operation methods, the pump energy consumption could be reduced by 25.0%, 32.7%, 38.2%, and 61.1%, respectively compared with the actual operation. Therefore, the selection of large temperature difference dynamic regulation can further reduce the pump energy consumption of the system, and the work provides a certain reference for the dynamic hydraulic optimization regulation of heat network.
Hydrate based hydrogen storage or solidified hydrogen storage (Solid-HyStore) enabling safe, long-term, and energy-dense storage of hydrogen molecules under moderate temperature and pressure conditions is bound to play a critical role in the foreseeable hydrogen economy. 1,3-Dioxolane (DIOX), a promising alternative to tetrahydrofuran (THF) by its environmentally benign chemical properties and the superior hydrate formation kinetics with hydrogen gas in aqueous solution, has secured its exclusive relevance to the development of Solid-HyStore technology. Amino acids emerging as a kinetic promotor can enhance the formation kinetics of various hydrate systems with the gas molecules being methane or carbon dioxide. Herein, the effects of amino acids (i.e. L-Tryptophan and L-Methionine) on the formation kinetics of mixed H2/DIOX (5.56 mol%) hydrate system was investigated. The visual observation of hydrate appearance during hydrate formation is presented to illustrate the hydrate growth behavior in the presence of amino acids. The results obtained in the current work confirmed the inability of amino acids to enhance the mixed H2/DIOX (5.56 mol%) hydrate formation kinetics and to alter the hydrate growth behavior of the same.