Total Site Hydrogen Integration with fresh hydrogen of multiple quality and waste hydrogen recovery in refineries

This paper proposes a novel method combining Pinch Methodology and waste hydrogen recovery, aiming to minimise fresh hydrogen consumption and waste hydrogen discharge. The method of multiple-level resource Pinch Analysis is extended to the level of Total Site Hydrogen Integration by considering fresh hydrogen sources with various quality. Waste hydrogen after Total Site Integration is further regenerated. The technical feasibility and economy of the various purification approaches are considered, demonstrated with a case study of a refinery hydrogen network in a petrochemical industrial park. The results showed that fresh hydrogen usage and waste hydrogen discharge could be reduced by 21.3% and 67.6%. The hydrogen recovery ratio is 95.2%. It has significant economic benefits and a short payback period for Total Site Hydrogen Integration with waste hydrogen purification. The proposed method facilitates the reuse of waste hydrogen before the purification process that incurs an additional environmental footprint. In line with the Circular Economy principles, hydrogen resource is retained in the system as long as possible before discharge.     

The effect of particle size distribution on the microstructure and properties of Al2O3 ceramics formed by stereolithography

Stereolithography (SL) shows advantages for preparing alumina-based ceramics with complex structures. The effects of the particle size distribution, which strongly influence the sintering properties in ceramic SL, have not been systematically explored until now. Herein, the influence of the particle size distribution on SL-manufactured alumina ceramics was investigated, including bending strength at room temperature, post-sintering shrinkage, porosity, and microstructural morphology. Seven particle size distributions of alumina ceramics were studied (in μm/μm: 30/5, 20/3, 10/2, 5/2, 5/0.8, 3/0.5, and 2/0.3); a coarse:fine particle ratio of 6:4 was maintained. At the same sintering temperature, the degree of sintering was greater for finer particle sizes. The particle size distribution had a larger influence on flexural strength, porosity and shrinkage than sintering temperature when the particle size distribution difference reached 10-fold but was weaker for 10 μm/2 μm, 5 μm/2 μm and 5 μm/0.8 μm. The sintering shrinkage characteristics of cuboid samples with different particle sizes were studied. The use of coarse particles influenced the accuracy of small-scale samples. When the particle size was comparable to the sample width, such as 30 μm/5 μm and 5 mm, the width shrinkage was consistent with the height shrinkage. When the particle size was much smaller than the sample width, such as 2 μm/0.3 μm and 5 mm, the width shrinkage was consistent with the length shrinkage. The results of this study provide meaningful guidance for future research on applications of SL and precise control of alumina ceramics through particle gradation.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Structural regulation and polishing performance of dendritic mesoporous silica (D-mSiO2) supported with samarium-doped cerium oxide composites

Ceria (CeO₂) particles are prevalent polishing abrasive materials. Trivalent lanthanide ions are the popular category of dopants for enriched surface defects and thus improved physicochemical properties, since they are highly compatible with CeO₂ lattices. Herein, a series of dendritic-like mesoporous silica (D-mSiO₂)-supported samarium (Sm)-doped CeO₂ nanocrystals were synthesized via a facile chemical precipitation method. The relation of the structural characteristics and chemical mechanical polishing (CMP) performances were investigated to explore the effect of Sm-doping amounts on the D-mSiO₂/Sm_xCe_1?xO_2?δ (x = 0–1) composite abrasives. The involved low-modulus D-mSiO₂ cores aimed to eliminate surface scratch and damage, resulting from the optimized contact behavior between abrasives and surfaces. The trivalent cerium (Ce³⁺) and oxygen vacancy (V_O) at CeO₂ surfaces were expected to be reactive sites for the material removal process over SiO₂ films. The optimal oxide-CMP performances in terms of removal efficiency and surface quality were achieved by the 40% Sm-doped composite abrasives. It might be attributed to the high Ce³⁺ and V_O concentrations and the enhancement of tribochemical reactivity between CeO₂SiO₂ interfaces. Furthermore, the relationship between the surface chemistry, polishing performance as well as the actual role in oxide-CMP of the D-mSiO₂/Sm_xCe_1?xO_2?δ abrasives were also discussed.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Influence of high energy ball milling on structural,microstructural and optical properties of TiO2 nanoparticles

The influence of high-energy ball milling on structural, microstructural, and optical properties of TiO₂ by modifying the nanoparticle size was studied. Five samples were extracted at different milling times (0, 2, 4, 8, and 13 h). The average particle sizes estimated by dynamic light scattering (DLS) were 205, 155.8, 116.8, 82.9, and 82.7 nm at 0, 2, 4, 8, and 13 h, respectively. X-ray diffraction analysis confirmed progressive broadening of the peaks as the milling time elapsed. Besides, a correlation was found between d spacing and the average crystal size. The UV–Vis diffuse reflectance spectra of TiO₂ revealed a decrease in reflectance due to particle size reduction. Similarly, an alteration of the bandgap transition energy was presented, whose values gradually decreased from 2.966 eV to 2.861 eV for the sample without and with the maximum duration milling performed (13 h), respectively. Likewise, the SEM analysis showed a distribution in nanoparticle size that became more homogeneous and smaller average grain size as the milling duration was longer.     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

ZrB2-MoSi2 ceramics: A comprehensive overview of microstructure and properties relationships. Part II: Mechanical properties

The mechanical behavior of ZrB₂-MoSi₂ ceramics made of ZrB₂ powder with three different particle sizes and MoSi₂ additions from 5 to 70 vol% was characterized up to 1500 °C. Microhardness (12–17 GPa), Young’s modulus (450–540 GPa) and shear modulus (190–240 GPa) decreased with both increasing MoSi₂ content and with decreasing ZrB₂ grain size. Room temperature fracture toughness was unaffected by grain size or silicide content, whilst at 1500 °C in air it increased with MoSi₂ and ZrB₂ grain size, from 4.1 to 8.7 MPa m^½. Room temperature strength did not trend with MoSi₂ content, but increased with decreasing ZrB₂ grain size from 440 to 590 MPa for the largest starting particle size to 700–800 MPa for the finest due to the decreasing size of surface grain pullout. At 1500 °C, flexure strength for ZrB₂ with MoSi₂ contents above 25 vol% were roughly constant, 400–450 MPa, whilst for lower content strength was controlled by oxidation damages. Strength for compositions made using fine and medium ZrB₂ powders increased with increasing MoSi₂ content, 250–450 MPa. Ceramics made with coarse ZrB₂ displayed the highest strengths, which decreased with increasing MoSi₂ content from 600 to 450 MPa.     

Practical Application of the Probabilistic‐Statistical Model of the Suspension Separation in Hydrocyclones

An effective practical approach that allows not only a significant reduction in the scope of practical experiments in the course of studying suspension separation processes in hydrocyclones, but also makes it possible to assess the intensity of random components of the processes and define the interrelation between such components and hydrodynamics of flows in a hydrocyclone is presented. Within the frames of the developed probabilistic‐statistical model of suspension separation in hydrocyclones on the basis of statistical self‐similarity properties, a relationship was found between determined and random components of the processes. This allowed transitioning from three‐parameter probability density functions for suspension particles in hydrocyclones to two‐parameter functions; thus significantly improving the efficiency of practical application of the developed model.