150 research outputs found
Thermodynamic Properties of Unburned Reactant Mixtures for Different Kind of Fuels
Accurate estimation of adiabatic flame temperature and combustion product species play a key role in estimating performance and emission characteristics of internal combustion engines. This can be succeeded only with exact knowledge of temperature and thermodynamic properties of the unburned
mixture. In this paper, thermodynamic properties of various fuels and fuel-air mixtures are presented. Differences in gas phase and liquid phase properties are discussed. Effect of equivalence ratio and unburned mixture temperature on enthalpy, specific heat and entropy of unburned fuel-air mixtures as well as effect of phase change on adiabatic flame temperature are shown. In order to serve as a recourse tool for researchers of combustion and internal combustion engines, the required polynomial coefficients used in calculation of thermodynamic properties are tabulated in famous NASA format for various important chemical compounds which are commonly used to represent surrogates of diesel,
gasoline, Jet-A and many other fuels
Comparative effectiveness research of palm tree pruning waste and geotextiles on subgrade stabilization
Ovaj rad predlaže novo i ekološki prihvatljivo rješenje za stabilizaciju posteljice koje ne samo da doprinosi recikliranju otpadnog materijala već i povećava nosivost tla posteljice. Laboratorijska ispitivanja provedena su pod statičkim opterećenjima pločom za prijenos opterećenja kako bi se procijenila potencijalna upotreba otpada od orezivanja palmi (Palm Tree Pruning Waste - PTPW) kao materijala za ojačanje tla umjesto komercijalno proizvedenog geotekstila, kao i za analizu utjecaja dubine ojačanja, broja ojačanih slojeva i relativne gustoće materijala posteljice. Rezultati su otkrili da se s povećanjem broja ojačanja poboljšala nosivost ojačane posteljice. Nadalje, kada se dubina ojačanja smanjila, nosivost se značajno poboljšala. Sve posteljice ojačane PTPW-om imale su bolje rezultate od posteljica ojačanih geotekstilom pod istim uvjetima. Dodatno, poboljšanje nosivosti u ojačanim posteljicama ocijenjeno je na temelju faktora poboljšanja nosivosti (Bearing Capacity Improvement Factor - BCIF). Najviši BCIF postignut je kada je PTPW korišten kao ojačanje s dva sloja pri pješčanoj posteljici relativne gustoće od 80 %.This paper proposes a novel and environmentally friendly solution for subgrade stabilization that not only contributes towards waste material recycling but also enhances the bearing capacity of subgrade soil. Laboratory plate load tests were conducted under static loads to evaluate the potential use of palm tree pruning waste (PTPW) as a soil reinforcement material instead of commercially manufactured geotextiles, as well as to analyse the impact of the reinforcement depth, number of reinforcement layers, and the relative density of the subgrade material. The results revealed that as the number of reinforcements increased, the load-bearing pressure behaviour of the reinforced subgrades improved. Furthermore, when the reinforcement depth decreased, the load-bearing pressure behaviour improved significantly. All PTPW-reinforced subgrades performed better than geotextile-reinforced subgrades under the same conditions. Additionally, the bearing capacity improvement in the reinforced subgrades was evaluated based on the bearing capacity improvement factor (BCIF). The highest BCIF was obtained when the PTPW was used as a reinforcement with two layers at a sand subgrade relative density of 80 %
A hybrid computational approach for seismic energy demand prediction
In this paper, a hybrid genetic programming (GP) with multiple genes is implemented for developing prediction models of spectral energy demands. A multi-objective strategy is used for maximizing the accuracy and minimizing the complexity of the models. Both structural properties and earthquake characteristics are considered in prediction models of four demand parameters. Here, the earthquake records are classified based on soil type assuming that different soil classes have linear relationships in terms of GP genes. Therefore, linear regression analysis is used to connect genes for different soil types, which results in a total of sixteen prediction models. The accuracy and effectiveness of these models were assessed using different performance metrics and their performance was compared with several other models. The results indicate that not only the proposed models are simple, but also they outperform other spectral energy demand models proposed in the literature
CoNLL 2017 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies
The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a real world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.Peer reviewe
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Relatório de estágio em farmácia comunitária
Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr
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