Use of La2O3 with 8YSZ as thermal barrier coating and its effect on thermal cycle behavior,microstructure, mechanical properties and performance of diesel engine operated by hydrogen-algae biodiesel blend

In this present work, the effect of lanthanum oxides (La₂O₃) on the thermal cycle behavior of TBC coatings and mechanical properties such as adhesion strength and microhardness of 8% Yttria Stabilized Zirconia (8YSZ) TBCs were investigated. CoNiCrAlY and aluminium alloy (Al–13%Si) were used as bond coat and substrate materials. 8YSZ and different wt % of La₂O₃ (10, 20, and 30%) top coatings were applied using the atmospheric plasma spray (APS) method. The thermal cycling test for TBC coated samples were conducted at 800 °C in the electric furnace. The XRD pattern shows that the La₂O₃ doped 8YSZ material transformed to cubic pyrochloric structured La₂Zr₂O₇ during thermal cycling. Further, the Taguchi-based grey relation analysis (GRA) method was applied to optimize the TBC coating parameters to achieve better mechanical properties such as adhesion strength and microhardness. And the optimized La₂O₃/8YSZ TBC coating was coated on CRDI engine combustion chamber components. The engine was tested with microalgae biodiesel and hydrogen, and the results were promising for the TBC-coated engine. The engine performance increased while using La₂O₃/8YSZ coated components, and the emissions from engine exhaust gas such as CO, HC, and smoke reduced considerably. It was found that there was no separation crack and spallation of the coating layer in the microstructure. Ultimately, the microstructural analysis of the optimized TBC coated piston sample after 50 h of running in the diesel engine confirmed that the developed coating had a superior thermal insulation effect and longer life.     

Effect of utilization of hydrogen-rich reformed biogas on the performance and emission characteristics of common rail diesel engine

The utilization of renewable gaseous fuels in the diesel engine has gained significant interest in recent years due to its clean-burning nature and higher availability. In this study, hydrogen-rich reformed biogas was used as a gaseous fuel in a common rail diesel engine with diesel as pilot fuel. The hydrogen-rich reformed gas was synthesized through dry-oxidative reforming. The experimentations were performed in the load range from 6 to 24 N m with two different flow rates of gaseous fuel (0.5 and 1.5 kg/h) at a constant speed of 1800 RPM. The effects on engine performance parameters (brake thermal efficiency, brake specific energy consumption, and brake specific diesel consumption), combustion parameters (rate of pressure rise and maximum heat release rate) and emission parameters (Unburnt hydrocarbons, nitrogen oxides, carbon monoxide, and carbon dioxide) were assessed. The induction of gaseous fuel led to an increase in brake thermal efficiency by 10.5%, reduction in brake specific energy consumption by 13.6%, and a reduction of 26.4% in brake specific diesel consumption with a flow rate of 0.5 kg/h when compared to diesel-only mode at 24 N m load. The HC, NO_X and CO₂ emissions were reduced by 18.2%, 7.4% and 1.4% with a flow rate of 0.5 kg/h when compared to diesel-only mode at 24 N m load due to lower availability of carbon content in the combustible mixture. The utilization of renewable fuel like hydrogen-rich reformed biogas has great potential for overcoming the issue related to both biogas and hydrogen in diesel engines. Moreover, the higher diesel substitution also demonstrates the potential for cost-saving and fossil fuel conservation.     

定距螺旋桨对船用主机外特性的要求分析

为解决定距螺旋桨与船用主机在船舶运行工况的机桨匹配问题,结合船舶系泊和航行试验的相关标准,分析和归纳船舶运行数据,将实船测试与船机桨匹配理论计算相结合,得出运输船和拖轮在常用工况及特殊工况下定距螺旋桨对主机外特性的定量要求,为配套不同细分市场时船用主机的优化和开发提供参考依据。     

基于Web的机票预订系统的设计与实现

文章主要介绍了实现机票预订系统的管理过程,该设计的完成也切实的体现了系统管理实施的优点。首先让大家了解了该系统开发的背景、研究现状及其发展趋势,让读者清楚设计该系统的目的及意义。然后较为详细地叙述了系统设计的可行性分析、需求分析、概要设计和功能的实现,其中主要以技术可行性和功能需求为主要叙述对象。最后把系统测试的方法和设计该系统出现的问题及修改完善的方法加以说明让大家更好的了解设计的过程。系统的功能主要包括基本的查询系统、订票系统、退票系统;主要的工作处理包括机票预订处理和退票处理;信息资料查询主要是管理员对客户信息查询、用户对航班信息查询、机票预定查询和退票信息查询;这些功能都满足了客户对机票预订系统的使用需求和对信息检索的要求。     

A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

In this article we illustrate a methodology for building cross-language search engine. A synergistic approach between thesaurus-based approach and corpus-based approach is proposed. First, a bilingual ontology thesaurus is designed with respect to two languages: English and Spanish, where a simple bilingual listing of terms, phrases, concepts, and subconcepts is built. Second, term vector translation is used – a statistical multilingual text retrieval techniques that maps statistical information about term use between languages (Ontology co-learning). These techniques map sets of t f id f term weights from one language to another. We also applied a query translation method to retrieve multilingual documents with an expansion technique for phrasal translation. Finally, we present our findings.     

An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries

The Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) is an extension to the classical Vehicle Routing Problem (VRP), where customers may both receive and send goods simultaneously. The Vehicle Routing Problem with Mixed Pickup and Delivery (VRPMPD) differs from the VRPSPD in that the customers may have either pickup or delivery demand. However, the solution approaches proposed for the VRPSPD can be directly applied to the VRPMPD. In this study, an adaptive local search solution approach is developed for both the VRPSPD and the VRPMPD, which hybridizes a Simulated Annealing inspired algorithm with Variable Neighborhood Descent. The algorithm uses an adaptive threshold function that makes the algorithm self-tuning. The proposed approach is tested on well-known VRPSPD and VRPMPD benchmark instances derived from the literature. The computational results indicate that the proposed algorithm is effective in solving the problems in reasonable computation time.     

Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.