Connecting with the Viewer: Affectivity and Cathexis in Textile Artwork

This article explores how, following bereavement, textile artwork may be able to make a connection with the viewer and allow a progression of their work of mourning. It takes an interdisciplinary approach, drawing from the literature of psychoanalytical theory, affectivity, and textile thinking to understand the importance of cloth as artwork in the grieving process. The article draws on the practice-based textile research of the author which, together with responses to the artworks made, discusses the way viewers can make an emotional investment in textile artwork and considers the concept of exhibitionary affect to increase the emotional connection of the viewer to the work.     

nvPM采样输运系统损失因子计算与改进研究

航空发动机排放的非挥发性颗粒物(nvPM)是大气污染的重要来源之一,对人体健康会造成一定的影响。在采样测量过程中会有一定量的损失,为能够更便捷高效地计算排放损失校正因子,该文结合CFM56-7B26/3型发动机排放数据和美国汽车工程师协会(SAE)排放测量校正因子建议标准改变计算流程,开发出一套计算工具。结果显示,新计算工具计算的数量浓度排放校正因子与发动机推力呈负相关,在推力为100%的额定推力下,数量校正因子最小,在推力为3%(慢车状态)处最大,与原方法结果趋势相同,且最大绝对误差为6.81,最小为0.64;质量校正因子也与发动机推力呈负相关,与原方法结果最大绝对误差为0.14,最小为0.007。新计算工具能够更好地与实际数据和推力相联系,在与原方法差异不大的情况下,能够实现更高效便捷的损失校正因子计算。     

Prediction of the colorimetric parameters and mass loss of heat‐treated bamboo: Comparison of multiple linear regression and artificial neural network method

In this study, the colorimetric parameters (L*, a*, b*) and mass loss of heat‐treated bamboo were investigated, and the obtained results were modeled by using two methods: multiple linear regression (MLR) and artificial neural network (ANN). First, bamboo samples were exposed to heat treatment at different temperatures (110°C, 140°C, 170°C, and 200°C) and durations (15, 30, 45, 60, 75, 90, and 115 minutes) in a laboratory oven. Then, the colorimetric parameters (L*, a*, b*) and mass loss of each sample were measured after each period of heat treatment. All data were modeled by using two methods separately for each parameter and the performances of these proposed methods were compared. It was found that color change and mass loss increased with increasing temperature and duration of heat treatment. Mean absolute percentage error (MAPE) values of all obtained MLR ranged from 0.64% to 10.63%, while the all MAPE values of ANN were found to be lower than 1.5%. Based on these results, it can be said that MLR and ANN could be used to evaluate the changes on the selected properties of heat‐treated bamboo samples. On the other hand, it should be emphasized that the ANN gave more accurate results than the MLR method because of its learning capability.     

Comparative study of the optimal operation of methane reforming process in cylindrical and spherical reactors using multi-objective optimization

We present a multi-objective optimization (MOO) based study of the optimal operation of methane reformer for spherical reactor and compare the results with the ones for the cylindrical reactor. We considered three objective functions for this comparative study, namely maximization of hydrogen production, minimization of carbon dioxide emission, and minimization of power loss due to pressure drop in the reactor. We solve four MOO problems, which include three 2-objective problems with each pair of the aforementioned three objectives. In addition, we also solve a three objective problem considering all the three objectives. The optimization variables considered for the MOO study correspond to the feed conditions. Specifically, the three variables include the inlet temperature and the molar feed ratios of oxygen to methane & steam to methane.     

Performance assessment of gas crossover phenomenon and water transport mechanism in high pressure PEM electrolyzer

To improve proton exchange membrane (PEM) electrolyzes’ performance the voltage loss through them should be avoided. In this work, it is intended to analyze losses including of diffusion loss, ohmic loss due to electrode, bipolar plate (BP), and membrane resistances, and gas crossover associated with the water transferring mechanisms. All of the losses are associated with water transferring mechanisms, which is created due to electro-osmoic drag, pressure differential between the anode and cathode sides, and diffusion. Furthermore, the effect of membrane thickness, cathode pressure, and operating temperature on the hydrogen crossover is examined. In addition, the contribution of ohmic loss due to electrode bipolar plate (BP), and membrane resistances is studied and, the contribution of different losses on the cell performance is discussed. Results show that raising cathode pressure from 1 to 40 bar lead to the increment of anodic hydrogen content from 1.038% to 21% at the specific current density of 10,000 A/m2. Enhancing the thickness of membrane has considerable impact on decrementing anodic hydrogen content, but the mass transfer loss rises from 0.022 to 0.027 V with enhancing membrane thickness from 50 to 300 μm, respectively. Furthermore, the contribution of voltage losses, assigned to each of losses are equal to 85%, 3%, and 12% for activation, diffusion and ohmic losses, respectively. It is found that, from the reported contribution for ohmic loss, the contribution of electrode BP, and membrane resistances are 31% and 69%, respectively.     

Hydraulics of free overfall in steeply sloping rough rectangular channel: A general computational approach

All supercritical free overfalls were almost considered as frictionless flow or pseudo-uniform flow before, the effect of friction had not been paid due attention. Currently, a new mathematical model is proposed to analyze supercritical rectangular free overfall by Boussinesq-type energy equation accounting for frictional effect. A computational approach of loop iteration algorithm is utilized to simultaneously calculate the implicit water surface profile by Runge-Kutta method, end-depth-ratio, and discharge. Subsequently, the dependency of discharge on end depth and Nikuradse equivalent sand roughness for different slope is illustrated. Comparison of computed results with experimental observations reveals satisfactory agreement. Additionally, the present energy approach leads to more accurate results than the momentum method for high roughness. Finally, to aid application for engineers, an explicit solution of discharge for practical application in the commonly using range is also proposed. The most important purpose of this study is to present a general computational approach, which could be used for the rough supercritical free overfalls of any other cross-sections.     

Silica-based ceramics toward electromagnetic microwave absorption

Silica-based ceramics have been explored extensively as a class of versatile materials for various applications in architecture, catalysis, energy, machinery, and biomedical engineering. Nevertheless, comprehensive information on silica-based ceramic and electromagnetic microwave (EMW) absorption is scarce, although excellent progress has been made in this field. Here, recent progress in the investigation of silica-based ceramics toward EMW absorption is reviewed. We first introduced the basis of ceramics (characteristics, classification, synthetic methods, potential applications). Subsequently, the silica-based ceramics, including Si-based oxides and alloys, SiOC/SiC/Si₃N₄/SiCN-based composite, Ti₃SiC₂ and composite for EMW absorption were systematically summarized. Notably, the fabrication strategies, absorption properties, and mechanisms of silica-based ceramics are described in detail, with a focus on structure and component design. Lastly, the prospects and ongoing challenges of this field in the future are presented. This review is expected to learn from the past and achieve progress toward the future of silica-based ceramic for EMW absorption.     

Targeted design of polyaniline-graphene oxide,barium-strontium titanate,hard-soft ferrite,and polyester multi-phase nanocomposite for highly efficient microwave absorption

The current paper focuses on synthesizing a high-efficiency microwave absorber via incorporating the nanofillers of graphene oxide-polyaniline (GO-PANI), barium-strontium titanate (BST), and soft-hard ferrite within the polyester matrix. The nanocomposite magnets of (Ba_0.5Sr_0.5Fe₁₂O₁₉)_1-x hard/(CoFe₂O₄)_x soft (x = 0.2, 0.5, and 0.8) were prepared using sol-gel auto-combustion method. The GO-PANI and BST were successfully synthesized by in situ polymerization and improved polymerization, respectively. The phase structure, chemical structure, morphology, and microwave absorption properties of the synthesized nanocomposites were characterized by X-ray diffractometer (XRD), Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscope (SEM), vector network analyzer (VNA) techniques, respectively. The results showed that the synergistic effects of the combination of dielectric (BST), conductive (GO-PANI), and magnetic materials (hard-soft ferrites) provided the reflection loss values of less than ?20 dB (>99% absorption) in the X-band region. The minimum reflection loss of ?35 dB (>99.99% absorption) was obtained by the optimal formulation including (Ba_0.5Sr_0.5Fe₁₂O₁₉)_0.2 (CoFe₂O₄)_0.8, and the weight ratio of 1: 2 for both BST/soft-hard ferrite and hard-soft ferrite + BST/GO-PANI with the thickness of 1 mm. According to the results, the thickness factor plays a key role in improving the impedance matching. Consequently, the proposed nanocomposite can be employed as a novel kind of microwave absorbers with good impendence matching and high absorption.     

宝钢低铁损取向硅钢在变压器新能效标准下的应用

随着变压器新能效标准GB 20052-2020的正式实施，变压器各能效等级普遍提升，也推动取向硅钢产品等级的提高。本文结合新能效标准，针对宝钢低铁损取向硅钢产品应用实绩，给出选材建议，并针对产品使用过程中存在的问题进行剖析，以期对变压器制造厂家选材和使用起到参考作用。     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.