Analysis of the Flow Field and Impact Force in High-Pressure Water Descaling

This study aims to improve the performances of the high-pressure water descaling technology used in steel hot rolling processes.In particular,a 2050 mm hot rolling line is considered,and the problem is investigated by means of a fluid–structure interaction(FSI)method by which the descaling effect produced by rolling coils with different section sizes is examined.Assuming a flat fan-shaped nozzle at the entrance of the R1R2 roughing mill,the outflow field characteristics and the velocity distribution curve on the strike line(at a target distance of 30–120 mm)are determined.It is found that the velocity in the center region of the water jet with different target distances is higher than that in the boundary region.As the target distance increases,the velocity of the water jet in the central region decreases.Through comparison with experimental results,it is shown that the simulation model can accurately predict the impact position of the high-pressure water on the impact plate,thereby providing a computational scheme that can be used to optimize the nozzle space layout and improve the slabs’descent effect for different rolling specifications.

Analysis and Optimization of Flow-Guided Structure Based on Fluid-Structure Interaction

Gases containing sulfur oxides can cause corrosion and failure of bellows used as furnace blowers in high-temperature environments.In order to mitigate this issue,the behavior of an effective blast furnace blower has been examined in detail.Firstly,the Sereda corrosion model has been introduced to simulate the corrosion rate of the related bellows taking into account the effects of temperature and SO_(2) gas;such results have been compared with effective measurements;then,the average gas velocity in the pipeline and the von Mises stress distribution of the inner draft tube have been analyzed using a Fluid-Structure Interaction model.Finally,the semi-closed internal corrosion environment caused by a 5 mm radial gap between the inner draft tube and the bellows has been considered.The gas flow rate in the residential space has been found to be low(0.5 ms–this value leads to a stable semi-closed internal corrosion environment for exhaust gas exchange);water phase in the exhaust gas is prone to accelerate the corrosion rate.On this basis,a bellows with an optimized inner draft tube has proposed,which includes corrosion-resistant honeycomb buffer rings.

Transferable adversarial slow feature extraction network for few-shot quality prediction in coal-to-ethylene glycol process

In the coal-to-ethylene glycol(CTEG)process,precisely estimating quality variables is crucial for process monitoring,optimization,and control.A significant challenge in this regard is relying on offline laboratory analysis to obtain these variables,which often incurs substantial monetary costs and significant time delays.The resulting few-shot learning scenarios present a hurdle to the efficient development of predictive models.To address this issue,our study introduces the transferable adversarial slow feature extraction network(TASF-Net),an innovative approach designed specifically for few-shot quality prediction in the CTEG process.TASF-Net uniquely integrates the slowness principle with a deep Bayesian framework,effectively capturing the nonlinear and inertial characteristics of the CTEG process.Additionally,the model employs a variable attention mechanism to identify quality-related input variables adaptively at each time step.A key strength of TASF-Net lies in its ability to navigate the complex measurement noise,outliers,and system interference typical in CTEG data.Adversarial learning strategy using a min-max game is adopted to improve its robustness and ability to model irregular industrial data accurately and significantly.Furthermore,an incremental refining transfer learning framework is designed to further improve few-shot prediction performance achieved by transferring knowledge from the pretrained model on the source domain to the target domain.The effectiveness and superiority of TASF-Net have been empirically validated using a real-world CTEG dataset.Compared with some state-of-the-art methods,TASF-Net demonstrates exceptional capability in addressing the intricate challenges for few-shot quality prediction in the CTEG process.

Identifying human body states by using a flexible integrated sensor

Flexible sensors are required to be lightweight,compatible with the skin,sufficiently sensitive,and easily integrated to extract various kinds of body vital signs during continuous healthcare monitoring in daily life.For this,a simple and low-cost flexible temperature and force sensor that uses only two carbon fiber beams as the sensing layer is reported in this work.This simple,flexible sensor can not only monitor skin temperature changes in real time but can also extract most pulse waves,including venous waves,from most parts of the human body.A pulse diagnostic glove containing three such flexible sensors was designed to simulate pulse diagnostic methods used in traditional Chinese medicine.Wearable equipment was also designed in which four flexible sensors were fixed onto different body parts(neck,chest,armpit,and fingertip)to simultaneously monitor body temperature,carotid pulse,fingertip artery pulse,and respiratory rate.Four important physiological indicators—body temperature(BT),blood pressure(BP),heart rate(HR),and respiratory rate(RR)—were extracted by the wearable equipment and analyzed to identify exercise,excited,tired,angry,and frightened body states.