传统企业数字化转型能力体系构建研究

企业试图完成数字化转型,这是在竞争中谋求发展的必经之路。文章率先进行数字化转型特征、策略的概念分析,而后总结以此为背景的能力模型、企业管理能力与技术能力,最终以某公司案例完成体系构建与应用的阐述。     

Coastal trapped waves in the southern Caspian Sea

Previous studies reported coastal trapped waves (CTWs) in the Caspian Sea (CS). This study deals with the generation mechanisms, the temporal and spatial variability of CTWs in this area, and their transformations during propagation from the origin to the destination using recent measurements and high-resolution numerical simulations. CTWs are observed at all stations with periods of 2–6 days after northerly storms. The Absheron Peninsula, old Sefidrud delta, and Nur coasts were identified as the CTWs prone regions. The generation of CTWs in these locations was confirmed using numerical experiments. The propagation away from the generating location of CTWs was analyzed using a representative real wind storm. In the west part of the CS, the generation mechanism of CTWs is mainly similar to the barotropic Kelvin waves; in contrast, it is similar to the continental shelf waves in the southern shelves. The results can be used to study the contribution of generated CTWs to the transport of sediment and biological materials in all large lakes.     

柔性夹具技术研究

为适应快速多变的市场需求,制造企业需要设计并应用柔性夹具。介绍了柔性夹具的发展及特点,给出了柔性夹具的设计依据,并从零件结构及工艺、组成元件确定、强度与精度保证等方面分析了柔性夹具的设计方法。     

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (Q_L) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.     

有轨电车车载储能系统研究

有轨电车车载储能系统是当前的业内热点。对有轨电车车载储能系统进行了研究,分析了有轨电车车载储能系统的容量配置、拓扑结构选择,论述了有轨电车车载储能系统的能量管理策略,并介绍了有轨电车车载储能系统的应用情况。     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

Predicting hydrogen adsorption and desorption rates in cylindrical metal hydride beds: Empirical correlations and machine learning

A major limitation in chemisorptive hydrogen storage in metal hydrides is the long time required for the adsorption reaction during charging. This study investigates how the shape and material of the reaction chamber influences the adsorption and desorption rates. Numerical simulations of hydrogen storage in a cylindrical reaction chamber filled with LaNi₅ hydride are conducted for a range of chamber thermal conductivities and aspect ratios. The results show that adsorption and desorption processes are limited by thermal diffusion in the hydride bed and storage chamber. A storage efficiency is proposed based on an ideal isothermal process and used to evaluate the impact of chamber thermal conductivity and aspect ratio on the adsorption and desorption rates. Empirical correlations are proposed for predicting the adsorption and desorption efficiency of cylindrical LaNi₅ hydride beds. Finally, a machine-learning based data model for predicting storage efficiency in metal hydride chambers is presented. Comparison against the empirical correlations highlights that the machine learning-based data model can predict the storage efficiency more accurately.     

Reformate-enriched gasoline-ethanol blends: Volatility criteria and azeotrope formation

Four hydrocarbon-base gasolines (BG) were formulated from the local refinery streams; isomerate, reformate, and light naphtha. The formulations were enriched in reformate. Each of these BG formulations was blended with 10 vol% of anhydrous ethanol. From ASTM-D86 distillation data, eight distillation curves were constructed and the trend line equations of these distillation curves were developed. Also, the area under each distillation curve (AUDC) was calculated through calculus definite integration technique. Subsequently, the area due to azeotrope formation (ADAF) for each BG-ethanol blend was estimated. In this paper, the influence of increasing reformate proportions on the created positive azeotrope, was studied. Also the influence of increasing reformate proportions on vapor pressure, Temperature for the vapor-liquid ratio of 20, T50 and octane number was studied. The results show that the R² values of the distillation curve equations prove the reliability of the fits. Also, increasing reformate proportion in the fuel blend improves the octane number while increasing reformate proportion decreases the volatility of the fuel formulation.     

A personal retrospect on three decades of high temperature fuel cell research; ideas and lessons learned

In1986 the Dutch national fuel cell program started. Fuel cells were developed under the paradigm of replacing conventional technology. Coal-fired power plants were to be replaced by large-scale MCFC power plants fuelled by hydrogen in a full-scale future hydrogen economy. With today's knowledge we will reflect on these and other ideas with respect to high temperature fuel cell development including the choice for the type of high temperature fuel cell. It is explained that based on thermodynamics proton conducting fuel cells would have been a better choice and the direct carbon fuel cell even more so, with electrochemical gasification of carbon as the ultimate step. The specific characteristics of fuel cells and multisource multiproduct systems were not considered, whereas we understand now that these can provide huge driving forces for the implementation of fuel cells compared to just replacing conventional combined heat and power production technology.     

Should emoji replace emotion words in questionnaire-based food-related consumer research?

Emotion word questionnaires remain dominant in food-related emotion research despite acknowledged limitations. Emoji questionnaires can overcome some of these limitations but are not yet regarded as a strong alternative to emotion word questionnaires. We believe they have the potential to earn this right and use this invited opinion piece to explain why. Following a brief introduction about emoji, advantages of emoji questionnaires are summarised: – enhanced ecological validity, familiarity and cross-culturally shared meanings. We then address concerns that hinder uptake of emoji questionnaires, including emoji meanings/interpretations, appropriateness for older consumers and ability to represent emotional arousal (activation to deactivation). Finally, we offer suggestions for how to accelerate the uptake of emoji questionnaires in sensory and consumer science, which include: i) more applied studies using emoji questionnaires, ii) establishing emoji meanings in the context of eating of drinking, iii) adopting open-ended question formats, iv) comparing emoji and emotion word questionnaires, and v) establishing guidelines for emoji questionnaires. An important spill-over benefit of research to develop emoji questionnaires is that it exposes the lack of similar research for emotion word questionnaires. We encourage colleagues in the field to engage in the task of conducting needed methodological research on emoji and emotion words alike.