Advanced Ignition Strategies for Future Internal Combustion Engines with Lean and Diluted Fuel-Air Mixtures

The main objective of this research was to study the mechanisms of the spark ignition process of lean or diluted fuel-air mixtures under enhanced gas flow conditions for applications in future internal combustion engines. Various spark ignition strategies were deployed by controlling the spark discharge process via different spark ignition hardware configurations. Modulated spark discharge parameters, such as enhanced discharge power, prolonged discharge duration, and boosted discharge current were facilitated in the research. The impact of gas flow on the spark discharge process in air was investigated under varying air flow conditions with a range of flow velocities from 0 m/s to 60 m/s. The ignition performance of the spark strategies was investigated with lean or diluted fuel-air mixtures under controlled gas flow conditions in an optical constant volume combustion chamber test platform. The mixture flow velocity across the spark gap ranged from 0 m/s to 35 m/s during the combustion tests.Experiments were carried out with air as the background media. Short circuits and restrikes were observed under air flow conditions. The frequency of these occurrences increased with increased air flow velocity. The length of the spark plasma increased, due to the stretch of the plasma channel by the air flow. The plasma was stretched at a speed similar to the air flow velocity across the spark gap. The maximum length of the spark plasma was affected by the air flow velocity and the spark gap size. The spark discharge duration reduced with increased air flow velocity. To enhance the ignition of a lean or diluted fuel-air mixture under quiescent conditions, high spark discharge power or high spark discharge current were applied. With equivalent spark discharge energy, a larger flame kernel was achieved by the high-power spark whereas the impacts of spark discharge current level and discharge duration during the arc and glow phases were insignificant on the flame kernel growth. A transient high-current spark also generated a larger flame kernel, although with much higher spark energy as compared with that from a conventional spark. Under gas flow conditions, both the spark discharge current magnitude and discharge duration were critical for the flame kernel growth. It is postulated that this kernel growth was the result of a prolonged spark discharge duration effectively increasing the interaction volume between the plasma channel and the combustible gas engulfed by the mixture flow. Consequently, a longer spark discharge duration proved beneficial in establishing a larger flame kernel, probably because the spark discharge current was sufficient to support the flame kernel growth. Indeed, it was observed that boosted spark current was advantageous for the flame kernel growth, especially at higher flow velocities. However, the high-power spark and transient high-current spark proved to be less effective with higher flow velocities, probably because of the short discharge duration

Measuring Immediate Effect and Carry-over Effect of Multi-channel Online Ads

Faced with various online ads, firms are hard to choose the most appropriate advertising channels which have best advertising effects. Online advertising has immediate and carry-over effects. We constructed a comprehensive evaluation model of multi-channel online advertising effects which can evaluate not only immediate effect but also carry-over effect based on lag effect factors. Then, we conducted a restricted grid search and multiple linear regressions to estimate the immediate effect and carry-over effect of paid search ads, mobile phone message ads and e-mail ads based on user behavior data and transaction data of an e-commerce website. The results show that the immediate effect intensity of paid-search ads is the highest, the carry-over effect duration of e-mail ads is the longest, and the cumulative carry-over effect intensity of e-mail ads is the highest. This study puts forward suggestions on how to evaluate the effects of multi-channel online ads more accurately, which can guide this e-commerce website to make better advertising strategy for online marketing

Exhaust Pressure Waves in Diesel Engines and the Impacts on Aftertreatment Sprays

Aftertreatment devices are commonly used in diesel engine systems for emission control. To ensure the proper function of the aftertreatment devices, it is often necessary to inject additional fuel or a reducing agent into the exhaust flow. The conditions in the exhaust flow are affected by the exhaust pressure wave, caused by the reciprocating movement of the piston and valves. Therefore, this research investigates the factors that affect the exhaust pressure wave and the consequent impacts of this wave on a liquid spray. First, the exhaust pressure wave action was studied experimentally on a single cylinder diesel engine at various engine operating conditions such as different load, EGR, and exhaust backpressure levels. Then, the gas flow velocity in the exhaust system was estimated with the simulation tool AVL BOOST. A stand-alone shock tube was used to create a condition comparable to the exhaust flow. The impacts of the pressure wave and the gas flow on the aftertreatment spray distribution and the droplet breakup were studied via optical methods

Density functional theory study on the B doping and B/P codoping of Si nanocrystals embedded in SiO2

Doping silicon nanocrystals (Si NCs) embedded in silicon dioxide (SiO2) with boron (B) and phosphorus (P) is a promising way of tuning the properties of Si NCs. Here we take advantage of density functional theory to investigate the dependence of the structural and electronic properties of Si NCs embedded in SiO2 on the doping of B and P. The locations and energy-level schemes are examined for singularly B-doped or B/P-codoped Si NCs embedded in SiO2 with a perfect or defective Si/SiO2 interface at which a Si dangling bond exists. A dangling bond plays an important role in the doping of Si NCs with B or B/P. The doping behavior of B in Si NCs embedded in SiO2 vastly differs from that of P. The electronic structure of a B/P-codoped Si NC largely depends on the distribution of the dopants in the NC

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning

Forgetting refers to the loss or deterioration of previously acquired information or knowledge. While the existing surveys on forgetting have primarily focused on continual learning, forgetting is a prevalent phenomenon observed in various other research domains within deep learning. Forgetting manifests in research fields such as generative models due to generator shifts, and federated learning due to heterogeneous data distributions across clients. Addressing forgetting encompasses several challenges, including balancing the retention of old task knowledge with fast learning of new tasks, managing task interference with conflicting goals, and preventing privacy leakage, etc. Moreover, most existing surveys on continual learning implicitly assume that forgetting is always harmful. In contrast, our survey argues that forgetting is a double-edged sword and can be beneficial and desirable in certain cases, such as privacy-preserving scenarios. By exploring forgetting in a broader context, we aim to present a more nuanced understanding of this phenomenon and highlight its potential advantages. Through this comprehensive survey, we aspire to uncover potential solutions by drawing upon ideas and approaches from various fields that have dealt with forgetting. By examining forgetting beyond its conventional boundaries, in future work, we hope to encourage the development of novel strategies for mitigating, harnessing, or even embracing forgetting in real applications. A comprehensive list of papers about forgetting in various research fields is available at \url{https://github.com/EnnengYang/Awesome-Forgetting-in-Deep-Learning}

Marine Ecological Disasters and Their Physical Controlling Mechanisms in Jiangsu Coastal Area

The studies in this chapter are focused on marine ecological disasters in Jiangsu coastal area. Three kinds of algal blooms occurred in this region, namely, red tide associated with Dinoflagellate, green tide associated with Ulvaprolifera and golden tide associated with Sargassum. Numerical model results demonstrated that red tides in Haizhou Bay originated locally, because most of Dinoflagellates near Zhoushan Islands would be transported northeastward by the Changjiang diluted water, and even the lucky ones that entered the south of Jiangsu coastal area would die in the Subei Shoal due to high turbidity there. Due to the Changjiang diluted water and the prevailing southerly wind, Ulvaprolifera could not drift southward, either. Seawater with high turbidity in the Subei Shoal limited sunlight penetration into deep water column, and further inhibited the growth of Ulvaprolifera suspending in the water column. In this chapter, we use drift bottles and satellite-tracked Argos drifters to provide solid direct dynamic evidence that Ulvaprolifera could drift from the Subei Shoal to Qingdao coastal area and even further north. The sand ridges limited the traveling path of Ulvaprolifera in the Subei Shoal, and wind-driven currents and other baroclinic processes helped Ulvaprolifera travel farther to the north

Neural Cognition and Affective Computing on Cyber Language

Characterized by its customary symbol system and simple and vivid expression patterns, cyber language acts as not only a tool for convenient communication but also a carrier of abundant emotions and causes high attention in public opinion analysis, internet marketing, service feedback monitoring, and social emergency management. Based on our multidisciplinary research, this paper presents a classification of the emotional symbols in cyber language, analyzes the cognitive characteristics of different symbols, and puts forward a mechanism model to show the dominant neural activities in that process. Through the comparative study of Chinese, English, and Spanish, which are used by the largest population in the world, this paper discusses the expressive patterns of emotions in international cyber languages and proposes an intelligent method for affective computing on cyber language in a unified PAD (Pleasure-Arousal-Dominance) emotional space