Simplification and applicability studies of a hydrogen-air detailed reaction mechanism

The research of hydrogen fuel internal combustion engine (HICE) had great significance facing the challenges of energy and environmental problems. Based on the detailed hydrogen-air reaction mechanism, the pre-mix model of CHEMKIN-Pro software was selected to simplify the detailed mechanism GRI-3.0. The most important elements and reactions was chose to construct framework mechanism firstly based on the sensitivity coefficient for H₂O and NO formation, and additional elements and reactions were added to framework mechanism for complementing the oxidation path of N2 and H₂. A simplified mechanism including 24-step elementary reaction was obtained and the laminar burning velocity calculated by this simplified mechanism matches well with the detailed mechanism in a wide range. This simplified mechanism was also applied in a CFD model which predicted the cylinder instantaneous pressure and NOx emission accurately within a large range of fuel air equivalent ratio. Showing that this mechanism has good applicability.     

Prediction of cooling efficiency of forced-air precooling systems based on optimized differential evolution and improved BP neural network

This paper proposes an approach to predict the efficiency of forced-air cooling of fresh apples that combines the optimized differential evolution (DE) algorithm and the back-propagation (BP) neural network algorithm. First, to balance population diversity and fast convergence, the individual mutation operation of the basic DE algorithm was optimized by dividing the entire population into two equal parts according to the fitness value of individuals, and DE-best-1 and DE-current-to-rand-1 are used as individual mutation operations for the superior- and inferior-part individuals, respectively. Moreover, the selection operation of basic DE was also changed by using a crowding scheme, which helps maintain population diversity and discover more regions containing the global optima. Second, an optimized DE-BP neural network model was established by using the optimized DE to determine the initial weights and thresholds of the BP neural network to avoid being trapped in local minima, following which the effect of input parameters on the network output was subjected to a comprehensive sensitivity analysis based on the trained neural network. The results show that the optimized DE-BP model accurately predicts the efficiency with which apples are cooled. Furthermore, the airflow velocity and total opening area have a significant negative correlation with the average apple temperature and a positive correlation with the cooling rate of the apples. Finally, the most important factor influencing the cooling efficiency of the pre-cooling system is the total opening area of the ventilated packaging.     

A skeletal n-butane mechanism with integrated simplification method

A new skeletal mechanism of n-butane is developed for describing its ignition and combustion characteristics applicable over a wide range of conditions: initial temperature 690–1430 K, pressure 1–30 atm, and equivalence ratio 0.5–2.0. Starting with a detailed chemical reaction kinetic model of 230 species and 1328 reactions (Healy et al., Combust. Flame, 2010), the directed relation graph method is applied as the first step to derive a semi-detailed mechanism with 134 species. Then, the reaction path analysis in conjunction with temperature sensitivity analysis is used to remove the redundant species and reaction paths simultaneously under the condition of low-temperature and moderate-to-high temperatures, respectively. Finally, a skeletal n-butane mechanism consisting of 86 species and 373 reactions can be obtained. Mechanism validation indicates that the new developed skeletal mechanism is in good agreement with the detailed mechanism in predicting the global ignition and combustion characteristics. The new skeletal mechanism is further validated using extensive available literature data including rapid pressure machine ignition delay time, shock-tube ignition delay time, laminar flame speed, and jet-stirred reaction oxidation, covering a large range of temperatures, pressures, and equivalence ratios. The comparison results demonstrate that a satisfactory agreement between predictions and experimental measurements is achieved.     

Simplified anode architecture for PEMFC systems based on alternative fuel feeding: Experimental characterization and optimization for automotive applications

The need to reduce PEMFC systems cost as well as to increase their durability is crucial for their integration in various applications and especially for transport applications. A new simplified architecture of the anode circuit called Alternating Fuel Feeding (AFF) offers to reduce the development costs. Requiring a new stack concept, it combines the simplicity of Dead-End Anode (DEA) with the operation advantages of the hydrogen recirculation. The three architectures (DEA, recirculation and AFF) are compared in terms of performance on a 5-kW test bench in automotive conditions, through a sensitivity analysis. A gain of 17% on the system efficiency is observed when switching from DEA to AFF. Moreover, similar performances are obtained both for AFF and for recirculation after an accurate optimization of the AFF tuning parameters. Based on DoE data, a gain of 25% on the weight of the anodic line has been identified compared to pulsed ejector architecture and 43% with the classic recirculation architecture with blower only (Miraï).     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

A pseudo-likelihood approach for estimating diagnostic accuracy of multiple binary medical tests

Latent class models with crossed subject-specific and test(rater)-specific random effects have been proposed to estimate the diagnostic accuracy (sensitivity and specificity) of a group of binary tests or binary ratings. However, the computation of these models are hindered by their complicated Monte Carlo Expectation–Maximization (MCEM) algorithm. In this article, a class of pseudo-likelihood functions is developed for conducting statistical inference with crossed random-effects latent class models in diagnostic medicine. Theoretically, the maximum pseudo-likelihood estimation is still consistent and has asymptotic normality. Numerically, our results show that not only the pseudo-likelihood approach significantly reduces the computational time, but it has comparable efficiency relative to the MCEM algorithm. In addition, dimension-wise likelihood, one of the proposed pseudo-likelihoods, demonstrates its superior performance in estimating sensitivity and specificity.     

A simplified physically-based breach model for a high concrete-faced rockfill dam: A case study

A simplified physically-based model was developed to simulate the breaching process of the Gouhou concrete-faced rockfill dam (CFRD), which is the only breach case of a high CFRD in the world. Considering the dam height, a hydraulic method was chosen to simulate the initial scour position on the downstream slope, with the steepening of the downstream slope taken into account; a headcut erosion formula was adopted to simulate the backward erosion as well. The moment equilibrium method was utilized to calculate the ultimate length of a concrete slab under its self-weight and water loads. The calculated results of the Gouhou CFRD breach case show that the proposed model provides reasonable peak breach flow, final breach width, and failure time, with relative errors less than 15% as compared with the measured data. Sensitivity studies show that the outputs of the proposed model are more or less sensitive to different parameters. Three typical parametric models were compared with the proposed model, and the comparison demonstrates that the proposed physically-based breach model performs better and provides more detailed results than the parametric models.     

MDCK细胞库的建立、检定及其生物学特性

目的建立MDCK细胞的主细胞库及工作细胞库,并进行检定,同时评价其生物学特性。方法从欧洲细胞保藏中心(European Collection of Authenticated Cell Culture,ECACC)引进1株MDCK细胞,经传代扩大培养后,分别建立主库及工作细胞库。按照《中国药典》三部(2015版)规定的方法对细胞库进行细胞活力、细胞形态、无菌、支原体及细胞内外源病毒因子检查,并对细胞生长状况、传代稳定性、流感病毒敏感性进行检测。结果建立的MDCK细胞主种子库及工作种子库细胞形态呈不规则的上皮样细胞状,生长状态良好,细胞活率分别为96.0%和95.5%,无菌、支原体及细胞内外源病毒因子检查结果均合格。MDCK细胞生长曲线均呈S型,培养48~96 h进入对数生长期,随后进入平台期。连续传10代48 h细胞活率在93.0%~95.5%之间,较稳定。MDCK细胞对流感病毒较敏感,对B型流感病毒的敏感性高于A型流感病毒。结论建立的主细胞库及工作细胞库各项检测结果均符合《中国药典》规定,具有良好的传代稳定性及流感病毒敏感性。     

Sensitivity Analysis as a Tool for Estimating Numerical Modeling Results

Modeling of real physical processes by numerical methods is highly time-consuming and requires significant computational capacity. In some cases, tens or even hundreds of hours of high-power computing are needed to virtually model a real process that lasts one second. Processes that take many hours, such as drying, pose an even greater challenge. This problem can be solved in two ways: by using faster computers (such as computing clusters) or by significantly simplifying the modeled process (its geometry, physical phenomena, or the impact of individual factors). For this reason, all methods which speed up or minimize the number of simulations required to achieve the research objective should be analyzed. This article focuses on the latter approach, and it proposes a simple method for predicting the responses of a numerical model (values of any output parameter) to changes in input values (values of any input parameter). This method requires a base model, such as a numerical model which is qualitatively and quantitatively consistent with experimental observations, and a sensitivity analysis. This article discusses the mathematical and logical premises for the discussed model, and it proposes two methods for predicting numerical simulation results. Those methods are illustrated with examples which analyze the behavior of the Eulerian Multiphase Model and describe phase interactions based on Gidaspow's approach. The discussed example relies on data from a series of articles published by the authors in Drying Technology. This article was inspired by the observations made during a time-consuming process of modeling a spouted bed grain dryer, which was described in the above publications. The objective of this study was to discuss the advantages and possibilities created by sensitivity analyses of numerical models and to encourage their practical application.