Novel energy-saving window coating based on F doped TiO2 nanocrystals with enhanced NIR shielding performance

To reduce the energy consumption of cooling in the hot summer days, searching for novel NIR shielding materials for buildings is of great value. In this report, monodispersed F doped TiO₂ nanocrystals with an average size of 8.6 nm were synthesized as novel solar shielding materials for energy-saving windows. All the products adopted an anatase TiO₂ structure. After doping of F ions, the morphology of TiO₂ was transformed from an irregular shape to a pseudospherical shape. The Raman shift and XPS depth analysis confirmed the successful doping of F⁻ ions into the lattice oxygen sites in the TiO₂ structure. The introduction of F⁻ ions generated free electrons and bulk Ti³⁺ in TiO₂ crystals, which activated a localized surface plasmon resonance (LSPR) absorption in the NIR region. Correspondingly, the NIR shielding performance of the TiO₂ films improved with increasing F doping amounts. The NIR shielding value of the films increased from 1.3% to 43.2% when the molar ratio of F to Ti increased from 0 to 0.3. The reason can be attributed to the enhanced NIR absorption induced by the increased electron concentration after doping of fluorine ions. The F–TiO₂ films showed superior visible transmittance (90.1–96.7%). Moreover, the F–TiO₂ films lowered the indoor temperature of the heat box by 5.3 °C in the thermal tests. Overall, the prepared F–TiO₂ nanocrystals show a great potential to be used for energy-saving windows.     

The operation types and operation window for high-purity hydrogen production for the sorption enhanced steam methane reforming in a fixed-bed reactor

The operation types and operation window for high-purity H₂ production for the sorption enhanced steam methane reforming (SE-SMR) with Ni/Al₂O₃ catalyst and CaO sorbent in a fixed-bed reactor are investigated by an experimentally verified 2D numerical method. Four chemical reactions including steam reforming, water gas shift, global steam reforming, and CO₂ sorption are considered. The operation window is defined as the H₂ and CO molar fractions at outlet satisfying both y_H2,out ≥ 90% and y_CO,out ≤ y_CO,allow (= 1%, 2% or 3%) in dry base. Under the conditions of y_H2,out and y_CO,allow, there are six operation types, of which 2 types are within the operation window and 4 types are not within the operation window as the temperature, weight hourly space velocity (WHSV) and steam to methane (S/C) molar ratio vary. For a common case of S/C = 3, the operation windows for y_CO,allow = 3% at WHSV = 8.5 h^?1 and 42.5 h^?1 are located at 570–670 °C and 640–690 °C respectively, based on the parameters in this work. The operation window of temperature is wider with decreasing WHSV, and it becomes wider remarkably as the S/C ratio increases. The lowest temperature inside the operation window is 550 °C. The effects of the temperature, WHSV and S/C ratio on the operating types, y_H2,out and y_CO,out are also presented and discussed in details.     

Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Greatly improved NIR shielding performance of CuS nanocrystals by gallium doping for energy efficient window

In this work, gallium doped copper sulfide (Ga-doped CuS) nanocrystals were prepared using a solvothermal method. The effects of Ga doping on the crystal structures, chemical composition, morphology, optical properties and thermal performance of copper sulfide (CuS) were investigated. The Ga-doped CuS nanocrystals had a hexagonal structure comparable to that of pure CuS. The Cu⁺/Cu²⁺ ratio first decreased and then increased with increasing Ga³⁺ doping. Both CuS and Ga-doped CuS exhibited nanoplate and nanorod morphologies. The visible transmittance of the Ga-doped CuS films was in the range of 61–77.1%. Importantly, the near-infrared (NIR) shielding performance of the films can be tuned by adjusting the concentration of the Ga dopant. The NIR shielding value of the optimal Ga-doped CuS film was 72.4%, which was approximately 1.5 times as high as that of the pure CuS film. This can be ascribed to the enhanced plasmonic NIR absorption that resulted from an increase in the hole concentration after doping with Ga³⁺ ions. In the thermal performance test, the Ga-doped CuS film lowered the interior temperature of the heat box by 9.1 °C. Therefore, the integration of good visible transmittance and high NIR shielding performance make the Ga-doped CuS nanocrystals a promising candidate for energy-efficient window coatings.     

Reduced‐order method for mathematical modeling of multiphase dc‐dc converter

A multiphase dc‐dc converter is effective for miniaturization and achieving high‐power density in a switching power supply. However, its mathematical modeling becomes complex as the phase number of the circuit increases. This study proposes a new modeling method to derive a reduced‐order method in a simple manner. The frequency characteristics of the reduced‐order model are fit to those of the original mathematical model of the multiphase dc‐dc converter. Therefore, the efficacy of the proposed method is validated.     

基于多基表示的滑动窗口椭圆曲线多标量乘算法

标量乘运算从整体上决定了椭圆曲线密码体制的快速实现效率，在一些椭圆曲线公钥密码体制中需要计算多标量乘。多基数链的标量表示长度更短、非零比特数目更少，较好地适用于椭圆曲线标量乘的快速计算。为了提高椭圆曲线密码的效率，在已有的二进制域和素域的标量乘算法的基础上，结合滑动窗口技术、多基算法，提出新的更高效的多标量乘算法。实验结果表明，新算法与传统Shamir算法和交错NAF算法相比，其所需的运算量更少，能有效地提高椭圆曲线多标量乘算法的效率，使多标量乘的运算更高效。相比于其他算法，新算法的计算效率比已有的多标量乘算法提高了约7.9%~20.6%。     

Elliptical distribution-based weight-determining method for ordered weighted averaging operators

The ordered weighted averaging (OWA) operators play a crucial role in aggregating multiple criteria evaluations into an overall assessment supporting the decision makers’ choice. One key point steps is to determine the associated weights. In this paper, we first briefly review some main methods for determining the weights by using distribution functions. Then we propose a new approach for determining OWA weights by using the regular increasing monotone quantifier. Motivated by the idea of normal distribution-based method to determine the OWA weights, we develop a method based on elliptical distributions for determining the OWA weights, and some of its desirable properties have been investigated.     

Multicriteria decision-making using Archimedean aggregation operators in Pythagorean hesitant fuzzy environment

In multicriteria decision-making (MCDM), the existing aggregation operators are mostly based on algebraic t-conorm and t-norm. But, Archimedean t-conorms and t-norms are the generalized forms of t-conorms and t-norms which include algebraic, Einstein, Hamacher, Frank, and other types of t-conorms and t-norms. From that view point, in this paper the concepts of Archimedean t-conorm and t-norm are introduced to aggregate Pythagorean hesitant fuzzy information. Some new operational laws for Pythagorean hesitant fuzzy numbers based on Archimedean t-conorm and t-norm have been proposed. Using those operational laws, Archimedean t-conorm and t-norm-based Pythagorean hesitant fuzzy weighted averaging operator and weighted geometric operator are developed. Some of their desirable properties have also been investigated. Afterwards, these operators are applied to solve MCDM problems in Pythagorean hesitant fuzzy environment. The developed Archimedean aggregation operators are also applicable in Pythagorean fuzzy contexts also. To demonstrate the validity, practicality, and effectiveness of the proposed method, a practical problem is considered, solved, and compared with other existing method.     

Vibration analysis and identification of breathing cracks in beams subjected to single or multiple moving mass using online sequential extreme learning machine

In this paper, a novel approach was presented to vibration analysis and identification of breathing cracks in Timoshenko beam under single or multiple moving mass. Dynamic strain energies (DSEs) and translational accelerations in beam structures under moving mass were used as forward problem and application of an emergent learning algorithm called the online sequential extreme learning machine algorithm as inverse problem to predict crack depths and locations. To demonstrate the potential of the proposed vibration analysis over existing ones, two validation studies have been done. To evaluate the proposed method to identify breathing cracks, two examples, namely, clamped–clamped beam and two span continuous beams have been studied. Also, the effect of the discrepancy in stiffness between the finite-element model and the actual tested dynamic system has been investigated. Another examination has been performed in which moving mass with different speeds are utilized. Also, the effect of multi mass passing through the beam has been studied. The obtained results indicated that the proposed method could identify the breathing cracks existence and severity in the beam under moving mass using DSE and accelerations, which may be noisy or noise free.     

基于时空的弱点状运动目标检测技术

如何在复杂背景下持续有效地检测目标位置,一直是研究者们需要面对的主要挑战。本文在研究红外点状移动目标特征的基础上,根据目标无纹理,无形状的特性,提出一种改进的形态学目标增强算法,并利用目标连续时空不变性检测目标。首先,建立多尺度的图像金字塔,在每层上采用改进的形态学算法快速、粗糙定位小目标。然后进一步的根据目标在时空上的位置相关性,提出基于目标运动特征分析的精确检测方法。得到精确稳定的检测结果。最后实验结果表明与经典的形态学检测算法及其他算法相比,该技术能更有效地检测弱小目标,具有更高的鲁棒性。