Numerical approach to analyze fluid flow in a type C tank for liquefied hydrogen carrier (part 1: Sloshing flow)

The demand for clean energy use has been increasing worldwide, and hydrogen has attracted attention as an alternative energy source. The efficient transport of hydrogen must be established such that hydrogen may be used as an energy source. In this study, we considered the influences of various parameters in the transportation of liquefied hydrogen using type C tanks in shipping vessels. The sloshing and thermal flows were considered in the transportation of liquefied hydrogen, which exists as a cryogenic liquid at ?253 °C. In this study, the sloshing flow was analyzed using a numerical approach. A multiphase sloshing simulation was performed using the volume of fluid method for the observation and analysis of the internal flow. First, a sloshing experiment according to the gas-liquid density ratio performed by other researchers was utilized to verify the simulation technique and investigate the characteristics of liquefied hydrogen. Based on the results of this experiment, a sloshing simulation was then performed for a type C cargo tank for liquefied hydrogen carriers under three different filling level conditions. The sloshing impact pressure inside of the tank was measured via simulation and subjected to statistical analysis. In addition, the influence of sloshing flow on the appendages installed inside of the type C tank (stiffened ring and swash bulkhead) was quantitatively evaluated. In particular, the influence of the sloshing flow inside of the type C tank on the appendages can be utilized as an important indicator at the design stage. Furthermore, if such sloshing impact forces are repeatedly experienced over an extended period of time under cryogenic conditions, the behavior of the tank and appendages must be analyzed in terms of fatigue and brittle failure to ensure the safety of the transportation operation.     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Adaptive GLR-, Rao- and Wald-based CFAR detectors for a subspace signal embedded in structured Gaussian interference

The problem of detecting a subspace signal embedded in subspace Gaussian interference and thermal noise is studied in this paper. In this problem, both the signal-independent and signal-dependent interferences are assumed to be present, therefore the overall interference subspace covers the signal subspace. The approach of this paper extends previous works involving either of those two kinds of interferences. A set of secondary data containing only interference plus noise is employed to estimate the interference covariance matrix and the noise power. Three new detectors are designed via the generalized likelihood ratio (GLR), Rao and Wald tests, respectively. Their probabilities of false alarms (PFAs) and detections are analytically derived. The PFAs show that the new detectors have the constant false alarm rate (CFAR) property against the interference and noise. Numerical results show that the new detectors outperform their counterparts for the studied problem. Furthermore, the new detectors are less sensitive to the secondary data size and to the mismatched subspace signal than some other detectors, such as the GLR detector (GLRD), the adaptive matched filter (AMF), the adaptive subspace detector (ASD), etc.     

Study of metal assisted anisotropic chemical etching of silicon for high aspect ratio in crystalline silicon solar cells

Textured surface is commonly used to enhance the efficiency of silicon solar cells by reducing the overall reflectance and improving the light scattering. In this study, a comparison between isotropic and anisotropic etching methods was investigated. The deep funnel shaped structures with high aspect ratio are proposed for better light trapping with low reflectance in crystalline silicon solar cells. The anisotropic metal assisted chemical etching (MACE) was used to form the funnel shaped structures with various aspect ratios. The funnel shaped structures showed an average reflectance of 14.75% while it was 15.77% for the pillar shaped structures. The average reflectance was further reduced to 9.49% using deep funnel shaped structures with an aspect ratio of 1:1.18. The deep funnel shaped structures with high aspect ratios can be employed for high performance of crystalline silicon solar cells.     

Rational Designs for Lithium-Sulfur Batteries with Low Electrolyte/Sulfur Ratio

Lithium-sulfur batteries (LSBs) are considered a promising next-generation energy storage device owing to their high theoretical energy density. However, their overall performance is limited by several critical issues such as lithium polysulfide (PS) shuttles, low sulfur utilization, and unstable Li metal anodes. Despite recent huge progress, the electrolyte/sulfur ratio (E/S) used is usually very high (≥20 µL mg⁻¹), which greatly reduces the practical energy density of devices. To push forward LSBs from the lab to the industry, considerable attention is devoted to reducing E/S while ensuring the electrochemical performance. To date, however, few reviews have comprehensively elucidated the possible strategies to achieve that purpose. In this review, recent advances in low E/S cathodes and anodes based on the issues resulting from low E/S and the corresponding solutions are summarized. These will be beneficial for a systematic understanding of the rational design ideas and research trends of low E/S LSBs. In particular, three strategies are proposed for cathodes: preventing PS formation/aggregation to avoid inadequate dissolution, designing multifunctional macroporous networks to address incomplete infiltration, and utilizing an imprison strategy to relieve the adsorption dependence on specific surface area. Finally, the challenges and future prospects for low E/S LSBs are discussed.     

Milk from cows fed a diet with a high forage:concentrate ratio improves inflammatory state,oxidative stress,and mitochondrial function in rats

Excessive energy intake may evoke complex biochemical processes characterized by inflammation, oxidative stress, and impairment of mitochondrial function that represent the main factors underlying noncommunicable diseases. Because cow milk is widely used for human nutrition and in food industry processing, the nutritional quality of milk is of special interest with respect to human health. In our study, we analyzed milk produced by dairy cows fed a diet characterized by a high forage:concentrate ratio (high forage milk, HFM). In view of the low n-6:n-3 ratio and high content of conjugated linoleic acid of HFM, we studied the effects of this milk on lipid metabolism, inflammation, mitochondrial function, and oxidative stress in a rat model. To this end, we supplemented for 4 wk the diet of male Wistar rats with HFM and with an isocaloric amount (82 kJ, 22 mL/d) of milk obtained from cows fed a diet with low forage:concentrate ratio, and analyzed the metabolic parameters of the animals. Our results indicate that HFM may positively affect lipid metabolism, leptin:adiponectin ratio, inflammation, mitochondrial function, and oxidative stress, providing the first evidence of the beneficial effects of HFM on rat metabolism.     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Stability and thermophysical properties of fly ash nanofluid for heat transfer applications

Improving the performance of heat transfer fluids is altogether significant. The best approach for improving the thermal conductivity is the addition of nanoparticles to the base fluid. In the present study, specific heat, dynamic viscosity, and thermal conductivity of water-based Indian coal fly ash stable nanofluid for 0.1% to 0.5% volume concentration in the temperature range of 30 to 60°C has been investigated. To evaluate an average particle diameter of 11.5 nm, the fly ash nanoparticles were characterized with scanning electron microscopy and dynamic light scattering. Using zeta potential, the stability of nanofluid in the presence of surfactant Triton X-100 was tested. Thermal conductivity and viscosity of fly ash nanofluid increased, while specific heat decreased as volume concentration increased. The effect of temperature on the fly ash nanofluid was directly proportional to its thermal conductivity and specific heat and inversely proportional to viscosity.     

多带OFDM-UWB系统峰均功率比降低方法研究

针对多带OFDM—UWB信号存在高峰均功率比的问题，提出了利用扩展与交织降低系统信号峰均功率比的方法。该方法通过对传输数据进行正交扩展与交织，使得进入多载波调制的数据趋于高斯分布，减小了传输数据自相关函数的旁瓣峰值，降低了OFDM-UWB信号的峰均功率比。由于采用正交矩阵进行扩展，扩展前后的数据传输速率保持不变。仿真结果表明，扩展与交织可以有效地降低信号峰均功率比2-5dB左右。同时该方法还具有抗窄带干扰的鲁棒性。