Recent progress on the discrete element method simulations for powder transport systems: A review

Powder transport systems are ubiquitous in various industries, where they can encounter single powder flow, two-phase flow with solids carried by gas or liquid, and gas–solid–liquid three-phase flow. System geometry, operating conditions, and particle properties have significant impacts on the flow behavior, making it difficult to achieve good transportation of granular materials. Compared to experimental trials and theoretical studies, the numerical approach provides unparalleled advantages over the investigation and prediction of detailed flow behavior, of which the discrete element method (DEM) can precisely capture complex particle-scale information and attract a plethora of research interests. This is the first study to review recent progress in the DEM and coupled DEM with computational fluid dynamics for extensive powder transport systems, including single-particle, gas–solid/solid–liquid, and gas–solid–liquid flows. Some important aspects (i.e., powder electrification during pneumatic conveying, pipe bend erosion, non-spherical particle transport) that have not been well summarized previously are given special attention, as is the application in some new-rising fields (ocean mining, hydraulic fracturing, and gas/oil production). Studies involving important large-scale computation methods, such as the coarse grained DEM, graphical processing unit-based technique, and periodic boundary condition, are also introduced to provide insight for industrial application. This review study conducts a comprehensive survey of the DEM studies in powder transport systems.     

Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios

Renewable energy integration into existing or new energy hubs together with Green technologies such as Power to Gas and Green Hydrogen has become essential because of the aim of keeping the average global temperature rise within 2 ^°C with regard to the Paris Agreement. Hence, all energy markets are expected to face substantial transitions worldwide. On the other hand, investigation of renewable energy systems integrated with green chemical conversion, and in particular combination of green hydrogen and synthetic methanation, is still a scarce subject in the literature in terms of optimal and simultaneous design and operation for integrated energy grids under weather intermittency and demand uncertainty. In fact, the integration of such promising new technologies has been studied mainly in the operational phase, without considering design and management simultaneously. Thus, in this work, a multi-period mixed-integer linear programming (MILP) model is formulated to deal with the aforementioned challenges. Under current carbon dioxide limitations dictated by the Paris Agreement, this model computes the best configuration of the renewable and non-renewable-based generators, their optimal rated powers, capacities and scheduling sequences from a large candidate pool containing thirty-nine different equipment simultaneously. Moreover, the effect of the intermittent nature of renewable resources is analyzed comprehensively under three different scenarios for a specific location. Accordingly, a practical scenario generation method is proposed in this work. It is observed that photovoltaic, oil co-generator, reciprocating ICE, micro turbine, and bio-gasifier are the equipment that is commonly chosen under the three different scenarios. Results also show that concepts such as green hydrogen and power-to-gas are currently not preferable for the investigated location. On the other hand, analysis shows that if the emission limits are getting tightened, it is expected that constructing renewable resource-based grids will be economically more feasible.     

Stable power supply of an independent power source for a remote island using a Hybrid Energy Storage System composed of electric and hydrogen energy storage systems

We propose a self-sustaining power supply system consisting of a “Hybrid Energy Storage System (HESS)” and renewable energy sources to ensure a stable supply of high-quality power in remote islands. The configuration of the self-sustaining power supply system that can utilize renewable energy sources effectively on remote islands where the installation area is limited is investigated. It is found that it is important to select renewable energy sources whose output power curve is close to the load curve to improve the efficiency of the system. The operation methods that can increase the cost-effectiveness of the self-sustaining power supply system are also investigated. It is clarified that it is important for increasing the cost effectiveness of the self-sustaining power supply system to operate the HESS with a smaller capacity of its components by setting upper limits on the output power of the renewable energy sources and cutting the infrequent generated power.     

分布式多元随机动态场景生成及快速精准场景降维算法

高比例新能源及多源耦合是电力系统发展的重要特征,这也为系统稳定经济运行提出了新挑战。该文以园区型多能系统为对象,研究了分布式多元随机动态场景分析,从多时空角度有效量化不确定因素给系统造成的影响,可为系统灵活重构、多维度协同运行与决策提供有力模型与场景支撑。首先由预测误差驱动拟合多元功率预测误差概率分布,全面反映随机功率出力信息,提高模型泛化性;以时序相关范围参数为数据驱动关联变量,高效动态控制波动强度;最终场景生成利用逆变换映射思想保证置信度。然后针对典型场景提取,提出一种综合递归聚类思想的多段嵌套削减算法,结合改进Wasserstein距离指标,兼具准确、时效、稳定方面的优势。最后由对比实验论证该方法的前沿有效性。     

Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m³.     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

Direct shear behavior of gravel-rubber mixtures: Discrete element modeling and microscopic investigations

In this paper, a newly developed 3-dimentional discrete element model (DEM) for gravel-rubber mixtures (GRMs), namely DEM4GRM, that is capable of accurately describing the macro-scale shear response (from small to large deformation) of GRMs in a direct shear box apparatus is presented. Rigid gravel grains are modelled as simple multi-shape clumps, while soft rubber particles are modeled by using deformable 35-ball body-centered-cubic clusters. Mixtures are prepared with different volumetric rubber content (VRC) at 0, 10, 25, 40 and 100%, statically compressed under 30, 60 and 100 kPa vertical stress and then sheared, by closely simulating a reference laboratory test procedure. The variation of micro-scale factors such as fabric, normal and tangential force anisotropy is carefully examined throughout the shearing process and described by means of novel micro-mechanical relationships valid for GRMs. Moreover, strong-force chains are scrutinized to identify the transition from rigid to soft granular skeleton and gain insights on the load transfer and deformation mechanisms of GRMs. It is shown that the development of the fabric and force anisotropy during shearing is closely related to the macro-scale shear strength of GRMs, and strongly depends on the VRC. Besides, strong-force chains appear to be primarily formed by gravel-gravel contacts (resulting in a rigid-like mechanical behavior) up to VRC = 30%, and by rubber-rubber contacts (causing a soft-like mechanical response) beyond VRC = 60%. Alternatively, at 30% < VRC < 60%, gravel-rubber contacts are predominant in the strong-force network and an intermediate mechanical behavior is observed. This is consistent with the behavioral trends observed in the macro- and micro-mechanical responses.     

Integrated LaB6/g-C3N4 solar absorber for solving dye accumulation during solar steam generation

Solar steam generation has attracted considerable interest due to its easy accessibility and sustainability. However, dye molecules were gradually concentrated on bulk water or the surface of solar absorbers during the disposal of dye wastewater. Herein, LaB₆/g-C₃N₄ composites were immobilized on porous cotton cloth, served as a solar absorber resistant to dye clogging. The optimal solar absorber possessed solar harvesting of 92.3% and showed great application potential in the field of the treatment of dye wastewater. This study presented a new approach for the treatment of dye wastewater.     

Evidence of fluid evolution of Baoshan Cu−Pb−Zn polymetallic deposit: Constraints from in-situ sulfur isotope and trace element compositions of pyrite

In-situ LA-ICP-MS and S isotopes of pyrite from the Baoshan Cu polymetallic deposit were conducted to investigate the ore-forming process and the enrichment mechanism of elements. Three generations of pyrite (Py I, Py II, and Py III) in the skarn-type ores and pyrite in the carbonate-hosted sulfide ores from central, western, and northern (C_Py, W_Py, and N_Py) mining districts are selected for comparison. Compared with Py I and Py III, the contents of most elements in Py II are apparently higher. The As and Se contents are high within a wide range and are decoupled in the growth band of the C_Py. The highest As, Se, and Pb contents were found in W_Py and N_Py. These results indicate the drastic changes in the temperature and fluid mixing during the mineralization. The occurrence of fluctuation and change in temperature and f(O₂) was triggered by intermittent pulses of magmatic-hydrothermal fluids, mixing with meteoric water, and water−rock interactions. The sulfur isotopes of all species of pyrite indicated the magmatic source. The change in the f(O₂) conditions caused slight differences in the sulfur isotope compositions. Consequently, a metallogenic model was proposed to explain the ore-forming processes.