DEM study on the segregation of a non‐spherical intruder in a vibrated granular bed

The segregation process of a single large intruder in a vibrated bed of small particles has been widely studied, but most previous studies focused on spherical intruders. In this work, the discrete element method was used to study the effects of vibration conditions and intruder shape on the dimensionless ascending velocity (va) of the intruder. The intruder was in a prolate shape with aspect ratio varied but its equivalent diameter fixed. Three equivalent diameters, namely volume‐equivalent diameter, surface‐area‐equivalent diameter, and Sauter diameter, were used. It was found that va increases and then decreases with the rise of the dimensionless vibration amplitude (Ad) and the dimensionless vibration frequency (fd), and va increases with the decrease of the sphe-ricity of the intruder (Φ). Moreover, the porosity variation in the vibrated bed and the granular temperature were analyzed, which can be linked to the change of va. It was further found that va can 0.5 be uniformly correlated to Ad‧f d, while the critical change of the response of va to Ad and fd occurs at Γ = 4.83, where Γ is the vibration intensity. Based on these findings, a piecewise equation was pro-posed to predict va as a function of Ad, fd, and Φ

Progress in developments of dry coal beneficiation

Abstract China’s energy supply heavily relies on coal and China’s coal resource and water resource has a reverse distribution. The problem of water shortages restricts the applications of wet coal beneficiation technologies in drought regions. The present situation highlights the significance and urgency of developing dry beneficiation technologies of coal. Besides, other countries that produce large amounts of coal also encounter serious problem of lack of water for coal beneficiation, such as American, Australia, Canada, South Africa, Turkey and India. Thus, dry coal beneficiation becomes the research hot-points in the field of coal cleaning worldwide in recent years. This paper systematically reviewed the promising research efforts on dry coal beneficiation reported in literature in last 5 years and discussed the progress in developments of dry coal beneficiation worldwide. Finally, we also elaborated the prospects and the challenges of the development of dry coal beneficiation

Multi-scale pressure analysis and fluidization quality characterization of dry dense medium fluidized bed

Coal beneficiation is the source technology of clean processing and utilization of coal. Dry coal beneficiation is an important way for efficient separation and upgrading of easily sliming coal in arid area. Dry dense medium fluidized bed forms a certain density of gas-solid fluidized bed by updraft-driven heavy medium particles fluidization, thus achieving coal separation according to bed density. The uniformity and stability of bed density, namely the bed fluidization quality, is the key to determine the separation accuracy. Due to the disturbance of airflow, bubbles, moving internals, feeding and other factors, the fluidization behavior of the bed is complex and changeable, and the pressure signal shows non-uniformity, non-linearity and multi-scale characteristics. Based on the characteristics of axial differential transmission and lateral equivalent diffusion of pressure signal in dry dense medium fluidized bed, the fluctuation characteristics of axial differential pressure were studied emphatically, and a quantitative characterization method of fluidization quality was proposed. The results show that: Based on time domain analysis, the probability density distribution of total pressure drop in Geldart A type separation fluidized bed is close to normal distribution. When the bed is in the particulate expansion, due to the uneven distribution of contact force between particles, the probability density shows the right deviation and the peak, deviating from the normal distribution. Through frequency domain analysis, it is found that the dominant frequency of bubbles dominates the whole axial interval of fluidized bed at the later stage of bed expansion. After complete fluidization, the dominant frequency of bubbles only controls the central region of the bed. The dominant frequency of bed concentration signal changes obviously along the bed axial distribution. Combined with the results of time-domain and frequency-domain signal analysis, a fluidization quality characterization model was proposed, where the standard deviation of axial fluctuation is weighted and averaged, and the dominant frequency of sub-bed concentration is taken as the weight value. This model can comprehensively evaluate the uniformity and stability of density distribution of dry dense medium fluidized bed, and provide strong support for the steady-state control and accurate separation of dry dense medium fluidized bed

Rapid detection of coal ash based on machine learning and X-ray fluorescence

Real-time testing of coal ash plays a vital role in the chemical, power generation, metallurgical, and coal separation sectors. The rapid online testing of coal ash using radiation measurement as the mainstream technology has problems such as strict coal sample requirements, poor radiation safety, low accuracy, and complicated equipment replacement. In this study, an intelligent detection technique based on feed-forward neural networks and improved particle swarm optimization (IPSO-FNN) is proposed to predict coal quality ash content in a fast, accurate, safe，and convenient manner. The data set was obtained by testing the elemental content of 198 coal samples with X-ray fluorescence (XRF). The types of input elements for machine learning (Si, Al, Fe, K, Ca, Mg, Ti, Zn, Na, P) were determined by combining the X-ray photoelectron spectroscopy (XPS) data with the change in the physical phase of each element in the coal samples during combustion. The mean squared error and coefficient of determination were chosen as the performance measures for the model. The results show that the IPSO algorithm is useful in adjusting the optimal number of nodes in the hidden layer. The IPSO-FNN model has strong prediction ability and good accuracy in coal ash prediction. The effect of the input element content of the IPSO-FNN model on the ash content was investigated, and it was found that the potassium content was the most significant factor affecting the ash content. This study is essential for real-time online, accurate, and fast prediction of coal ash

Combined heat and power generation via hybrid data center cooling-polymer electrolyte membrane fuel cell system

Although there has been a lot of waste heat utilization studies for the air-cooled data center (DC) systems, the waste heat utilization has not been studied for the liquid-cooled DC systems, which have been rapidly gaining importance for the high-performance Information and Communication Technology facilities such as cloud computing and big data storage. Compared to the air-cooled systems, higher heat removal capacity of the liquid-cooled DC systems provides better heat transfer performance; and therefore, the waste heat of the liquid-cooled DC systems can be more efficiently utilized in the low-temperature and low-carbon energy systems such as electricity generation via polymer electrolyte membrane (PEM) fuel cells. For this purpose, the current study proposes a novel hybrid system that consists of the PEM fuel cell and the two-phase liquid-immersion DC cooling system. The two-phase liquid immersion DC cooling system is one of the most recent and advanced DC cooling methods and has not been considered in the DC waste heat utilization studies before. The PEM fuel cell unit is operated with the hydrogen and compressed air flows that are pre-heated in the DC cooling unit. Due to its original design, the hybrid system brings its own original design criteria and limitations, which are taken into account in the energetic and exergetic assessments. The power density of the PEM fuel cell reaches up to 0.99 kW/m2 with the water production rate of 0.0157 kg/s. In the electricity generation case, the highest energetic efficiency is found as 15.8% whereas the efficiency increases up to 96.16% when different multigeneration cases are considered. The hybrid design deduces that the highest exergetic efficiency and sustainability index are 43.3% and 1.76 and they are 9.4% and 6.6% higher than exergetic and sustainability performances of the stand-alone PEM fuel cell operation, respectively.Defence Science and Technology Agency (DSTA)Nanyang Technological UniversityThe authors gratefully thank the funding supports fromthe joint project between Nanyang Technological Univer-sity (NTU) and Defense Science and Technology Agency4770KANBURET AL. (DSTA). We are also grateful to Dr. Wei Tong and SimiaoFan for their help on the study

Multi-criteria thermoeconomic and thermodynamic assessments of the desalination-integrated two-phase liquid-immersion data center cooling system

The waste heat management of the data center cooling systems has a significant share in the energy-efficient operations of the data centers. In this study, a new hybrid desalination-data center cooling system is proposed to reduce the cost drawback of the waste heat in the data center cooling operations. A two-phase liquid-immersion cooling unit is selected as the data center cooling method with the cooling load range of 0.7 to 1.5 kW. It is a promising solution thanks to the high heat flux removal performance but there is still a lack of research about waste heat management. The waste heat of the immersion cooling system is used to heat up the feed side of the desalination module. A direct contact membrane distillation system as preferred as the desalination module with the membrane area range of 5 to 75 cm2. The proposed hybrid system is investigated according to the thermodynamic, economic, and thermoeconomic aspects. The thermoeconomic assessment is done concerning the unique exergy-cost matrix of the original design. The maximum thermal and exergy efficiencies are found as 64.5% and 53.7%, respectively. The daily distilled water rate can reach 6.13 kg at the highest cooling load and membrane area. Compared to the stand-alone data center cooling operation, the hybrid system has higher capital and operation costs. The payback period is found 3.72 years that means the proposed system is economically feasible for real applications. Also, the levelized product cost of the hybrid design is calculated in the range of 2.69 to 5.33 SGD/h. In the multiobjective optimization study, the best trade-off point is decided at the cooling load of 1.1 kW whilst the membrane area varies between 5.12 and 5.19 cm2.Nanyang Technological UniversityFunding information: Nanyang Technological Universit

A Self-Consistent Physical Model of the Bubbles in a Gas Solid Two-Phase Flow

We develop a self-consistent physical model of bubbles in a gas solid two-phase flow. Using the Peng-Robonson state equation and a detailed specific heat ratio equation of bubbles, we obtain the kinetic equations of the bubbles on the basis of the Ergun equation, thermodynamic equations, and kinetic equations. It is found that the specific heat ratio of bubbles in such systems strongly depends on bubble pressures and temperatures, which play an important role in the characteristics of the bubbles. The theoretical studies show that with increasing height in the systems, the gas flow rate shows a downward trend. Moreover, the larger particles in the gas solid flows are, the greater the gas velocity is. The bubble sizes increase with the increasing heights of the gas solid systems, and then decrease. The bubble velocity is affected by the gas velocity and the bubble size, which gradually increase and eventually quasi-stabilize. This shows that gas and solid phases in a gas solid two-phase flow interact with each other and a self-consistent system comes into being. The theoretical results have exhibited important value as a guide for understanding the properties and effects of bubbles in gas solid two-phase flows

System-level experimental investigations of the direct immersion cooling data center units with thermodynamic and thermoeconomic assessments

The study is to perform thermodynamic, economic and thermoeconomic assessments for two different direct immersion cooling data center systems which are the single-phase and the two-phase immersion cooling systems with the operating ranges of 3.2–27.6 kW and 6.8–15.9 kW, respectively. The two-phase cooling system achieves 72–79% better coefficient of performance trends than the single-phase cooling system. According to the present worth method, the replacement and the energy costs are found as the most dominant future cost terms for the two-phase and the single-phase cooling systems, respectively. The annual exergy cost of the two-phase cooling system is found up to 4.91 times the annual energy costs due to the dominant effects of the destruction and loss terms. Moreover, both cooling data center systems are compared to the existing air-cooled data center unit. They are found economically infeasible for the server power rates below 5 kW because of their higher capital investment costs while they become more affordable for higher server power rates with lower future cost terms.Defence Science and Technology Agency (DSTA)Economic Development Board (EDB)Nanyang Technological UniversityThe authors would like to thank the funding supports from the joint project of Nanyang Technological University (NTU) and Defense Science and Technology Agency, and the Economics Development Board Singapore - EcoCampus at NTU project

Analysis and evaluation on pressure fluctuations in air dense medium fluidized bed

Pressure fluctuations contribute to the instability of separation process in air dense medium fluidized bed, which provides a high motivation for further study of underlying mechanisms. Reasons for generation and propagation of pressure fluctuations in the air dense medium fluidized bed have been discussed. Drift rate and collision rate of particles were employed to deduce the correlation between voidage and pressure fluctuations. Simultaneously, a dynamic pressure fluctuation measuring and analysis system was established. Based on frequency domain analysis and wavelet analysis, collected signals were disassembled and analyzed. Results show gradually intensive motion of particles increases magnitudes of signal components with lower frequencies. As a result of violent particle motion, the magnitude of real pressure signal’s frequency experienced an increase as air velocity increased moderately. Wavelet analysis keeps edge features of the real signal and eliminates the noise efficaciously. The frequency of de-noised signal is closed to that of pressure signal identified in frequency domain analysis. Keywords: Air dense medium fluidized bed, Pressure fluctuations, Frequency domain analysis, Wavelet analysis, Particle distribution functio