Life cycle assessment of HFC-134a production by calcium carbide acetylene route in China

HFC-134a is a widely used environment-friendly refrigerant. At present, China is the largest producer of HFC-134a in the world. The production of HFC-134a in China mainly adopts the calcium carbide acetylene route. However, the production route has high resource and energy consumption and large waste emission, and few of the studies addressed on the environmental performance of its production process. This study quantified the environmental performance of HFC-134a production by calcium carbide route via carrying out a life cycle assessment (LCA) using the CML 2001 method. And uncertainty analysis by Monte-Carlo simulation was also carried out. The results showed that electricity had the most impact on the environment, followed by steam, hydrogen fluoride and chlorine, and the impact of direct CO₂ emissions in calcium carbide production stage on the global warming effect also could not be ignored. Therefore, the clean energy (e.g., wind, solar, biomass, and natural gas) was used to replace coal-based electricity and coal-fired steam in this study, showing considerable environmental benefits. At the same time, the use of advanced production technologies could also improve environmental benefits, and the environmental impact of the global warming category could be reduced by 4.1% via using CO₂ capture and purification technology. The Chinese database of HFC-134a production established in this study provides convenience for the relevant study of scholars. For the production of HFC-134a, this study helps to better identify the specific environmental hotspots and proposes useful ways to improve the environmental benefits.     

Fire safe,sustainable loose furnishing

The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production.     

无黏土相盐水储层钻开液体系构建及其抗污染性能评价

采用NaCl/KCl/HCOONa复配欠饱和盐水作为钻开液的基础液相,自研的聚合物VIS-B作为流型调节剂,可酸溶的改性淀粉STA作为体系的降失水剂,Dua及Jqw作为暂堵材料,构建了一套无黏土相钻开液体系。该体系在密度1.10~1.28 g/cm^3间稳定可调,抗温可达130℃,具有较高的低剪切速率黏度和较好的润滑性能,且能有效抵抗各类储层污染物的污染,满足了Missan油田不同储层段的作业需求。     

梯度铝蜂窝夹芯板的力学行为

梯度分层铝合金蜂窝板是一种有效的吸能结构,本工作在梯度铝蜂窝结构的基础上根据梯度率的概念,通过改变蜂窝芯层的胞壁长度,设计了4种质量相同、梯度率不同的铝蜂窝夹芯结构。通过准静态压缩实验,并结合非线性有限元模拟准静态及冲击态下梯度铝蜂窝夹芯结构的变形情况及其力学性能,分析对比了相同质量下梯度铝蜂窝夹芯结构在准静态下的变形模式以及冲击载荷下分层均质蜂窝结构和不同梯度率的分层梯度蜂窝结构的动态响应和能量吸收特性。结果表明:在准静态压缩过程中,铝蜂窝梯度夹芯板的变形具有明显的局部化特征,蜂窝芯的变形为低密度优先变形直至密实,层级之间的密实化应变差随芯层密度的增大而逐渐减小;在高速冲击下,梯度蜂窝板并非严格按照准静态过程中逐级变形直至密实,而是在锤头冲击惯性及芯层密度的相互作用下整体发生的线弹性变形、弹性屈曲、塑性坍塌及密实化;另外,在本工作所设计的梯度率中,当梯度率为γ₁=0.0276时,梯度蜂窝夹芯板的吸能性达到最好,相较于同等质量下的均质蜂窝夹芯板,能量吸收提高了10.63%。     

Repeated low-velocity impact responses of SiC particle reinforced Al metal-matrix composites

This study aimed to investigate experimentally the repeated low-velocity impact behaviors of SiC reinforced aluminum 6061 metal-matrix composites for different volume fractions and energy levels. In addition, the hardness variations were measured by the Vickers hardness tests from the impacted and impact-free cross-sections of the particle reinforced metal-matrix composites. Low-velocity impact tests were applied to composite samples manufactured by powder metallurgy (in 10, 20, and 30% volume fractions) at two total energy levels (15 and 60 J as single) and in repetitions equal to the sum of these energy levels (5 + 5 + 5 and 20 + 20 + 20 J as repeated). As a result, in increasing the impact number for all volume fractions, the total contact time was shortened and the peak contact force increased, whereas both the permanent central deflection and the absorbed energies reduced. Hence, these variations obtained under repeated impacts (5 + 5 + 5 and 20 + 20 + 20 J) revealed that metal-matrix composites showed a tougher behavior with an increase in the impact numbers from 1st to 3rd, particularly because of the strain hardening effect. Furthermore, an increase in volume fraction from 10 to 30% resulted in an increase in the impact strength under all repeated and single impacts despite changing deformation and damage mechanisms due to increasing the strain hardening effect and particle fractures. The hardness was affected by the volume fraction and increased as the volume fraction increased in both the impacted and impact-free zones. The repeated impact increased the impacted zone hardness more than the single impact for all volume fractions. Additionally, the hardness of the impacted zone under 20 + 20 + 20 J repeated impact was measured as the highest value in the 30% volume fraction. Therefore, metal-matrix composites can behave harder with the strain hardening effect under repeated impacts.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

Environmental impact estimation of ceramic lightweight aggregates production starting from residues

Within a circular economy approach, this study investigates the environmental impact of lightweight aggregates (LWAs) produced starting from different mixes of different clays with brewery sludge and cattle bone flour ash (CBA), used as poring and fertilizing agents, respectively. The environmental impact was evaluated by means of release tests, insulation capacity, carbon footprint (CFP), and particulate matter emission during pellet firing. Release tests representative of LWAs realistic application showed very high release of phosphate and satisfactory release of potassium. The thermal insulation of the LWAs was tested by thermal imaging camera and resulted highly variable depending on the composition, with the mix containing CBA performing best. This latter composition leads also to the smallest CO₂ equivalent emission, due to the calorific power of CBA, allowing lower consumption of fossil fuels during the LWA production. Finally, total particulate emissions during the thermal treatment resulted similar in terms of mass for all mixes, while differences in terms of particle morphology and composition occurred. Samples containing residue resulted with a quite good release behavior, CFP, and insulation properties, but higher emission of particles, particularly when glass is added.     

一种改进的特征匹配算法在碎片云测量建模中的应用

为满足超高速撞击典型Whipple防护构型的损伤评估需求,利用图像处理技术对碎片云序列阴影图像进行深入研究。使用超高速序列激光阴影成像仪得到三组不同实验条件下碎片云发展过程的高清阴影图像,分别对每组最具代表性的2帧进行图像处理分析;根据碎片云图像特点以及碎片运动特性,提出了一种改进的碎片二次特征匹配算法,该方法包含碎片粗定位、特征定义及初匹配和精确匹配三步策略;通过运用改进的匹配算法,对选取的相邻两帧图片完成碎片高效匹配,并提取匹配碎片的运动参数,进而分析碎片的速度分布和飞行角度分布,获取二次碎片云相关运动特性;得到三组实验各自的轨迹模拟图。根据得到的轨迹分析结果分别对三组实验的后板损伤进行估计,并通过与防护构型的实际损伤结果进行比较,验证了该方法的有效性。     

氮含量对HPD-1双相不锈钢组织及力学性能的影响

通过显微组织观察与力学性能测试研究了氮含量(0.08%~0.22％,质量分数)对HPD-1双相不锈钢硬度、拉伸性能、低温冲击性能及疲劳性能的影响。结果表明,氮含量变化可显著影响试验钢γ/α相比例,当氮含量由0.08％升高到0.22％,γ相含量由38.1％提高至56.5％。α相的硬度由273 HV10提高到343 HV10,γ相的硬度由238 HV10提高到299 HV10,试验钢强度明显提升。氮元素对两相比例和奥氏体相韧性的双重影响导致试验钢低温冲击性能呈先上升后下降的趋势;更高的氮含量抑制疲劳裂纹萌生与拓展,是影响HPD-1双相不锈钢室温疲劳性能的主要因素。撕裂棱是疲劳断口的显著特征。     

An improved iterative stochastic multi-objective acceptability analysis method for robust alternative selection in new product development

Alternative selection in new product development (NPD) is a multi-criteria decision-making (MCDM) problem. It usually starts with incomplete, imprecise or even partially missing information. Currently, most existing methods in dealing with this problem cannot work well if required information is incomplete or missing. It is acknowledged that stochastic multi-objective acceptability analysis (SMAA) can be applied to address MCDM problem with incomplete preference information and uncertain criteria measurements. In SMAA, alternatives are evaluated based on SMAA measurements (acceptability index, central weight vector and confidence factor). The discriminability of SMAA for the optimum alternative heavily depends on differences of SMAA measurements among different alternatives. Usually, a large number of alternatives and high level of uncertainty are involved in alternative selection in NPD. In this situation, the differences among SMAA measurements are not obvious, and therefore SMAA cannot deal with such problem very well. To this end, this paper proposes an improved SMAA method called Iterative-SMAA (I-SMAA) for alternative selection in NPD. In the I-SMAA, an iterative multi-step decision-making process is suggested to improve differences of SMAA measurements among different alternatives, and thus assist decision makers (DMs) to positively discern from the most preferred alternative. To enhance the decision-making efficiency, sensitive criteria are acquired in each iteration by ranking sensitivity analysis. DMs are guided to provide partial preference information and give more accurate criteria measurements for sensitive criteria rather than all criteria. Eventually, to verify the proposed method, a numerical example of the existing literature is solved with the method, and the results are compared. And then, a practical example of a preparation equipment for coal samples is further employed to verify the practicability of the proposed I-SMAA.