Studying local liquid velocity in liquid–solid packed bed using the newly developed X-ray DIR technique

Combination of X-ray Digital Industrial Radiography (DIR) and Particle Tracking Velocimetry (PTV) techniques for local liquid velocity measurement (V_LL) has been newly developed and successfully applied for trickle bed reactor (TBR). The technique was validated against newly developed fiber optical probe technique. This work attempts to highlight the applicability of this newly developed technique on a liquid–solid packed bed reactor. In this work, liquid was represented by water and solids were represented by EPS beads. The EPS beads were chosen because of its low density property. Three superficial liquid velocities (V_SL) were applied to the system. The experiment was replicated four times. The digital industrial radiography (DIR) consists of a complementary metal oxide semiconductor (CMOS) digital detector and X-ray source. Results of this work suggest that the technique has been successfully applied and comparable with previous work that has been done in the literature. It also suggests that there will be a maximum measurable interstitial liquid velocity when it travel inside the packed bed. The measured V_LL can have a maximum range that is between 4 and 4.7 times that of its V_SL. For V_SL=0.42±±2%, the V_LL-Max is in between 1.7 cm/s and 1.9 cm/s, V_SL=0.84±±2%, the V_LL-Max is in between 3.6 cm/s and 4.0 cm/s, and for V_SL=1.11±±2%, the V_LL-Max is in between 4.3 cm/s and 4.8 cm/s.     

Effect of grinding-induced cyclic heating on the hardened layer generation in the plunge grinding of a cylindrical component

This paper discusses the effects of the grinding-induced cyclic heating on the properties of the hardened layer in a plunge cylindrical grinding process on the high strength steel EN26. It was found that a multi-pass grinding brings about a uniform and continuous hardened layer along the circumference of the cylindrical workpiece. An increase of the number of grinding passes, leads to a thicker layer of hardening, a larger compressive residual stress and a deeper plastic deformation zone. Within the plastic deformation zone, the martensitic grains are refined by the thermo-mechanical loading, giving rise to a hardness of 12.5% higher than that from a conventional martensitic transformation. The coupled effects of heat accumulation and wheel wear in the multi-pass grinding are the main causes for the thickening of the hardened layer. A too small infeed per workpiece revolution would result in insufficient grinding heat, and in turn, bring about an undesirable tempered hardened layer and a reduction of its hardness.     

超超临界锅炉过热器管超温蠕变应力松弛规律研究

超超临界锅炉高温过热器集箱出口区域的过热器管易处于超温运行的环境,产生蠕变应力松弛导致材料失效. 基于Norton蠕变模型,以烟气温度750℃、蒸汽温度600℃、蒸汽压力26 MPa的运行工况,模拟T91过热器管壁在长时间热诱导中产生的应力松弛行为及蠕变分布. 模拟结果显示,过热管应力松弛现象首先发生在管内壁面,随着时间累计沿着径向方向扩散;10000 h后内壁面出现应力松弛且松弛加速;同时管壁面在应力松弛的过程中发生高温蠕变行为,且蠕变行为首先出现在内壁面并沿着径向扩散,内壁面蠕变程度高于外壁面;10000 h后管壁面厚度开始减薄. 研究结果表明:超超临界锅炉过热器管超温运行10000 h是蠕变应力松弛到蠕变损伤的时间拐点.     

Dynamic surface control of a piezoelectric fuel injector during rate shaping

Fuel injection rate shaping is a strategy to improve fuel efficiency and reduce harmful emissions in diesel engines. Due to their fast response, piezoelectric fuel injectors are capable of rate shaping operation. This paper describes a model-based closed-loop controller of injection flow rate for a piezoelectric fuel injector. This within-an-engine-cycle control strategy utilizes a dynamic surface control scheme and shows an injection flow rate tracking capability. Practical issues with LabVIEW FPGA control implementation are also addressed. The performance of the controller is verified with simulation and experimental results at different rail pressures and desired injection rates. The experiments show a maximum error of total fuel per one injection event of 2.5%. A stability analysis is also included.     

Hyperelastic,Robust, Fire-Safe Multifunctional MXene Aerogels with Unprecedented Electromagnetic Interference Shielding Efficiency

MXene aerogels have shown great potential for many important functional applications, in particular electromagnetic interference (EMI) shielding. However, it has been a grand challenge to create mechanically hyperelastic, air-stable, and durable MXene aerogels for enabling effective EMI protection at low concentrations due to the difficulties in achieving tailorable porous structures, excellent mechanical elasticity, and desired antioxidation capabilities of MXene in air. Here, a facile strategy for fabricating MXene composite aerogels by co-assembling MXene and cellulose nanofibers during freeze-drying followed by surface encapsulation with fire-retardant thermoplastic polyurethane (TPU) is reported. Because of the maximum utilization of pore structures of MXene, and conductive loss enhanced by multiple internal reflections, as-prepared aerogel with 3.14 wt% of MXene exhibits an exceptionally high EMI shielding effectiveness of 93.5 dB, and an ultra-high MXene utilization efficiency of 2977.71 dB g g⁻¹, tripling the values in previous works. Owing to the presence of multiple hydrogen bonding and the TPU elastomer, the aerogel exhibits a hyperelastic feature with additional strength, excellent stability, superior durability, and high fire safety. This study provides a facile strategy for creating multifunctional aerogels with great potential for applications in EMI protection, wearable devices, thermal management, pressure sensing, and intelligent fire monitoring.     

A new force-depth model for robotic abrasive belt grinding and confirmation by grinding of the Inconel 718 alloy

Robotic abrasive belt grinding has been successfully applied to the grinding and polishing of aerospace parts. However, due to the flexible characteristics of robotic abrasive belt grinding and the time-varying characteristics of the polishing contact force, as well as the plastic and difficult-to-machine material properties of Inconel 718 alloy, it is very difficult to control the actual removal depth and force of the polished surface, which brings great challenges to robot automatic polishing. Therefore, the relationship between the grinding force and the grinding depth in the robotic abrasive belt grinding is analyzed in detail, the robot machining pose error model considering the deformation of the grinding head is established, and the Inconel 718 alloy machining experiment of the robotic abrasive belt grinding is designed. The mapping relationship between the grinding force and the grinding depth is obtained, and the grinding force ratio in the downgrinding and upgrinding mode is discussed. The experimental and theoretical comparisons results show that with the increase of the grinding depress depth, both the grinding depth and the grinding force show an irregular increasing trend, and the increasing trend of the grinding force (increases by about 344.44%–445.45%) is obviously greater than that of the grinding depth (increases by about 52.94%). When the grinding depress depth is large (greater than 3 mm), the feed direction force and the normal force appear obvious secondary pressure peaks at the beginning and end of grinding, which has not been seen in previous studies. In addition, regardless of whether it is downgrinding or upgrinding, the grinding force ratio decreases with the increase of the depress depth, and the grinding force ratio of downgrinding (average 0.668) is smaller than that of upgrinding (average 0.724). This study provides a reference for robotic abrasive belt grinding, and the surface quality of Inconel 718 alloy of robotic abrasive belt grinding can be further improved through the optimization of force and depth.     

Thermodynamic assessment of RuO4 oxide

RuO₄ oxide appears much less stable than RuO₂(s) in the Ru–O binary system with a melting point close to room temperature and a certain propensity to vaporize or decompose at low temperatures. Ab initio simulations in the framework of density functional theory (DFT) on RuO₄(s) are performed to analyze the cubic and monoclinic structures and to evaluate the heat capacities at low temperatures. Then, a critical evaluation of thermodynamic data from calorimetry and vapor pressure determinations - was carried out coupled with ab-initio calculations to propose new thermodynamic data: the entropy.S° (RuO_4, s, cubic, 298K) = 132.7 J·K⁻¹mol⁻¹ and formation enthalpy.Δ_fH° (RuO₄, s, cubic, 298K) = −252.4 ± 5.5 kJ mol⁻¹.     

高速列车受电弓气动噪声分析与空腔降噪研究

随着高速列车运行速度的不断提高,受电弓气动噪声也愈加严重。针对这一问题,文中采用LES大涡模拟、边界层噪声源模型和FW-H声类比法,通过建立某型号受电弓局部1:1气动噪声分析模型进行数值模拟。文中研究了受电弓各部位的气动噪声贡献量,还探究了针对较大噪声位置空腔采用射流降噪方法的降噪效果。结果表明,当网格总数为4 323万个时,数值模拟精确度满足要求。受电弓空腔上游和空腔中部绝缘子是气动噪声的主要来源。在射流降噪前后,空腔内部气动噪声均为宽频带噪声,主要能量集中在0~4 500 Hz。对250 km·h^-1行驶速度下的空腔进行主动射流降噪,距列车25 m远处的垂向监测点声压级最小值为81.65 dB,比降噪前降低了2.64 dB。     

Improved learning of I2C distance and accelerating the neighborhood search for image classification

Image-to-class (I2C) distance is a novel measure for image classification and has successfully handled datasets with large intra-class variances. However, due to the lack of a training phase, the performance of this distance is easily affected by irrelevant local features that may hurt the classification accuracy. Besides, the success of this I2C distance relies heavily on the large number of local features in the training set, which requires expensive computation cost for classifying test images. On the other hand, if there are small number of local features in the training set, it may result in poor performance.In this paper, we propose a distance learning method to improve the classification accuracy of this I2C distance as well as two strategies for accelerating its NN search. We first propose a large margin optimization framework to learn the I2C distance function, which is modeled as a weighted combination of the distance from every local feature in an image to its nearest-neighbor (NN) in a candidate class. We learn these weights associated with local features in the training set by constraining the optimization such that the I2C distance from image to its belonging class should be less than that to any other class. We evaluate the proposed method on several publicly available image datasets and show that the performance of I2C distance for classification can significantly be improved by learning a weighted I2C distance function. To improve the computation cost, we also propose two methods based on spatial division and hubness score to accelerate the NN search, which is able to largely reduce the on-line testing time while still preserving or even achieving a better classification accuracy.     

A study on type II structures. Part I:: a modified one-dimensional mass–spring model

Most impact energy-absorbing structures can be classified into one of two types in terms of the shape of the overall quasi-static load–displacement curve in the early stages of deformation. Type I has a relatively “flat-topped” curve, while type II has an initial peak load followed by a “steeply falling” curve. The previous work showed that the deformation of type II specimens is much more sensitive to the impact velocity than that of type I specimens. That is, when the total kinetic energy remains the same for all specimens, smaller final deformations result from higher impact velocities; and this phenomenon is much more significant for type II specimens than for type I specimens. In order to explain this characteristic of type II structures, a one-dimensional mass–spring model with variable mass is proposed for a typical type II structure (i.e., a pair of pre-bent plates), and used to examine the effects of the lateral inertia of the structure under impact. Unlike conventional mass–spring models, our system contains an equivalent variable mass, which is a function of the rotational angle at plastic hinges and comes into effect during the second phase of the dynamic response. Predictions of this analytical model agree very well with an ABAQUS FE simulation of the dynamic response of the pre-bent plates to impact; and this verifies the validity of the mass–spring model proposed.