Microscopic details of asphaltenes aggregation onset during waterflooding

We report detailed microscopic studies of asphaltenes aggregation onset during waterflooding of petroleum reservoirs. To achieve this objective, a series of simulations are performed on asphaltenic-oil miscibilized with water at high pressure and temperature through molecular dynamics. Results of this simulation onset are applicable to asphaltenes behavior in real crude oils. Our simulation results illustrate that the aggregation onset in waterflooding generally follows three sequential steps: (i) Asphaltene-water interaction; (ii) Water bridging; (iii) Face-to-face stacking. Then, asphaltene-water and water-water hydrogen-bonding network surround every aggregate boosting the intensity of aggregation onset. We intend to utilize such understanding of these details in our predictive and preventive measures of arterial blockage in oil reservoirs during waterflooding.     

Robustness of asymptotic accelerated life test plans to small‐sample settings

Much of the statistical literature on optimal test planning for accelerated life testing utilize asymptotic methods to derive optimal test plans. While sufficient effort is made to assess the robustness of these test plans to the choice of design parameters and distribution assumptions, there is very little literature on the performance of asymptotic test plans relative to small samples (on the order of 10‐15 samples). An alternative concern is that the asymptotic test plans may not necessarily be the true “optimal” test plan for a given sample size. The purpose of this research is to present exact or “near‐exact” methods for developing test plans and compare the performance of these test plans with corresponding asymptotic test plans in small‐sample settings. The optimal location of design points and sample allocation is determined using each method for lognormal and Weibull lifetime distributions with both complete and Type 1 right‐censored data under two selected acceleration factor models. The investigations reveal that asymptotic test plans tend to corroborate quite well with exact test plans and thus are suitably robust to small‐sample settings in terms of optimal variance.     

Validation of a 3D multiphase-multicomponent CFD model for accidental liquid and gaseous hydrogen releases

As hydrogen-air mixtures are flammable in a wide range of concentrations and the minimum ignition energy is low compared to hydrocarbon fuels, the safe handling of hydrogen is of utmost importance. Additional hazards may arise with the accidental spill of liquid hydrogen. Such a release of LH2 leads to a formation of a cryogenic pool, a dynamic vaporization process, and consequently a dispersion of gaseous hydrogen into the environment. Several LH2 release experiments as well as modeling approaches address this phenomenology. In contrast to existing approaches a new CFD model capable of simulating liquid and gaseous distribution was developed at Forschungszentrum Jülich. It is validated against existing experiments and yields no substantial lacks in the physical model and reveals a qualitatively consistent prediction. Nevertheless, the deviation between experiment and simulation raises questions on the completeness of the database, in particular with regard to the boundary conditions and available measurements.     

Investigating measurements of fine particle (PM2.5) emissions from the cooking of meals and mitigating exposure using a cooker hood

There is growing awareness that indoor exposure to particulate matter with diameter ≤ 2.5 μm (PM_2.5) is associated with an increased risk of adverse health effects. Cooking is a key indoor source of PM_2.5 and an activity conducted daily in most homes. Population scale models can predict occupant exposures to PM_2.5, but these predictions are sensitive to the emission rates used. Reported emission rates are highly variable and are typically for the cooking of single ingredients and not full meals. Accordingly, there is a need to assess PM_2.5 emissions from the cooking of complete meals. Mean PM_2.5 emission rates and source strengths were measured for four complete meals. Temporal PM_2.5 concentrations and particle size distributions were recorded using an optical particle counter (OPC), and gravimetric sampling was used to determine calibration factors. Mean emission rates and source strengths varied between 0.54—3.7 mg/min and 15—68 mg, respectively, with 95% confidence. Using a cooker hood (apparent capture efficiency > 90%) and frying in non‐stick pans were found to significantly reduce emissions. OPC calibration factors varied between 1.5 and 5.0 showing that a single value cannot be used for all meals and that gravimetric sampling is necessary when measuring PM_2.5 concentrations in kitchens.     

基于IMCT理论的CaO-SiO2-MgO-Al2O3-Na2O渣系的脱硫热力学模型

 为了精确表征含Na2O渣系的脱硫能力，改善脱硫效果，基于熔渣离子与分子共存理论（IMCT）建立了CaO-SiO2-MgO-Al2O3-Na2O渣系结构单元的作用浓度计算模型和1 753 K时该渣系的脱硫热力学模型。并对渣系的总硫分配比及各自硫分配比的影响因素进行了讨论分析。理论结果表明，除LS， MgS外，随着Al2O3质量分数的增加，该渣系的脱硫能力明显下降，而MgO和Na2O质量分数的增加，对提高渣系的脱硫能力具有明显的促进作用。此外，少量的Na2O即可表现出很强的脱硫效果，这为含有Na2O的冶金二次资源在铁水脱硫过程中的应用以及铁水脱硫渣系的优化提供了必要的理论依据。     

考虑节点过载的碳排放空间关联系统级联失效模型

为提高突发事件级联失效对现实碳排放关联系统破坏程度的评估可信性，在传统复杂网络的"负载-容量"级联失效模型基础上，考虑个体成员对负载的冗余能力，提出一种过载失效概率，构建了考虑节点过载状态的级联失效模型，并基于节点特性提出了6种过载节点负载分配策略。仿真结果表明：在过载节点负载分配策略中，综合分配策略整体上较优，能够有效控制级联失效的规模，增加网络鲁棒性；在一定范围内提升过载参数有助于降低级联失效的影响，但提升到一定程度时改善效果不明显；在不同负载分配策略下，剩余系数存在一个最优值，容量可调参数存在最优区间，可以使碳排放关联网络保持较好鲁棒性的同时，花费较小的构建成本，其中紧密度分配策略对应的网络构建成本较高。     

基于双树复小波的无参考立体图像质量评价

随着3D技术的不断发展，立体图像的使用领域越来越广泛，同时人们对图像的清晰度要求越来越高，因此，立体图像的质量评价成为关注点，基于此，提出了一种基于双树复小波变换的立体图像质量评价算法。使用双树复小波变换对立体图像的左、右视图进行处理，生成纹理结构图像，且根据最小能量误差的原理，获取左右视图的视差图；对纹理结构图像和视差图提取非对称广义高斯分布模型的参数、梯度幅值、相对梯度方向方差和奇异值曲线与坐标轴的面积等特征；使用AdaBoosting BP神经网络，进行训练和预测立体图像的质量得分。在LIVE立体图像数据库上的实验结果表明，新方法预测得分与主观得分有较好的一致性，获得了比较好的实验结果。     

Experimental study and thermodynamic modeling of the Cu–Sn–Si–O system and sub-systems

Phase equilibria between slag, Cu–Sn alloy and solid oxide phases, SnO₂ (cassiterite) or SiO₂ (tridymite, cristobalite) are important for oxidizing fire refining of black copper produced during the recycling of copper scrap and waste electrical and electronic equipment. Integrated experimental and thermodynamic modeling study is presented for the Cu–Sn–Si–O chemical system and its sub-systems. Experimental technique involved high-temperature equilibration, followed by rapid quenching and direct measurement of Cu, Sn and Si concentrations in the liquid and solid phases using the electron probe X-ray microanalysis. Experimental results and literature data have been used to develop the thermodynamic database for the system. The database works within the environment of FactSage software, as well as ChemApp, ChemSheet and SimuSage. Combined with other assessments, it can be used to optimize and develop recycling processes using the black copper route.     

New insight into subcritical rupture of SiC-based filaments at intermediate temperatures (400–900 °C) under air

The delayed failure of SiC fibrous reinforcement has continuously been investigated to warrant the long term performances of Ceramic Matrix Composite (CMC). Chiefly assessed on multifilament tow samples to alleviate some handling difficulties, subcritical crack growth (SCG) parameters are however ruled by structural artifacts which hinder the identification of intrinsic filament behavior. In this paper, we propose to estimate the true filament parameters for 5 fiber types from bundle behavior using a recently communicated Monte Carlo algorithm integrating flaw and stress distributions through a deterministic fracture mechanics law under Paris’ formulation. So computed tow lifetime are broadly dispersed, encompassing raw data, and show a structure-dependent scale effect, revealed by n_filament>n_tow where n is the stress exponent. The relationship between SCG coefficient and chemical composition of the substrate is discussed and highlights the major effect of doping elements (Ti or Zr), oxygen or hydrogen content.     

Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients

A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First, in order to derive an equation for the discharge coefficient, energy-momentum equations are implemented to define the physical realization of the phenomenon. Afterward, the discharge coefficient is presented in terms of contraction and energy loss coefficients. Subsequently, discharge coefficient, contraction, and energy loss coefficients were determined through an implicit optimization technique on the data. Data analysis illustrated that there is a meaningful power relationship between the contraction and energy loss coefficients. Thereafter, dimensional analysis is performed and an explicit best-fit regression equation is developed for defining the energy loss coefficient. The obtained equations for contraction and energy loss coefficients were then used in the computation of the discharge coefficient and determination of the flow discharge in the vertical sluice gate. The performance of the developed approach is validated against the selected benchmarks existing in the literature.