Computational and experimental investigations on tailor-made biofuel blend properties

In regards to sustainability and environmental reasons, biomass based biofuel has emerged as promising candidates amongst other alternative vehicular fuel options. Feedstock selection contributes to diverse biofuel blend components. Through computational product design, potential candidates can be generated and screened from a large pool of fuel blends. Computational approaches minimize the search region and assist focused experimental work as conventional experimental methods are exhaustive and time consuming. Fuel blend properties need to conform with fuel regulation standards in order to be accepted as a vehicular fuel option. This paper compares computationally generated tailor-made biofuel blend properties with experimental methods. Results show notable errors for prediction of kinematic viscosity and distillation temperature of tailor-made biofuel blends associated with property models implemented in model formulation. Nonetheless, predicted and experimentally tested tailor-made biofuel blend properties complied with EN590 fuel regulation standard

Computational approaches for optimal design of tailor made biofuel blends

Diminishing fossil fuel supplies and increasing awareness on environmental issues surged the need for renewable and environmentally friendly alternative fuel options for the transportation sector. Diverse biofuel components can be produced from exploitation of biomass as an energy source. Malaysia having abundant palm biomass waste is prompted to efficiently utilize the available resources for production of second generation biofuel blends. However, complexity arises in designing suitable biofuel blends that comply to fuel regulation standards and generate reduced emissions while having equal performance as conventional diesel fuel. Experimental methods consume immense resources and time, require highly sophisticated equipments, and are difficult to conduct for fluid flow variations. Computational approaches adopt a systematic blend formulation process that assists on focused experimental work. In this study, optimal tailor made biofuel blends were designed and evaluated for engine performances, emissions, and in-cylinder fluid flow analyses through implementation of various computational approaches that follow an integrated framework. Systematic model based approach was applied to design tailor made biofuel blends that comply to EN590 fuel reference standard using B5 diesel, butanol, ethanol, and butyl levulinate as building blocks. Fuel blends were generated through Generalized Algebraic Modelling System and predicted fuel properties validated with experimental tests. In-cylinder fluid flow profiles were simulated through computational fluid dynamics model using ANSYS Fluent software version 13.0. Engine performances such as indicated power and indicated thermal efficiency were predicted through mathematical models where experimental validation was done for indicated power. Semi-empirical emission correlations were applied to predict nitrogen oxide, carbon monoxide, unburnt hydrocarbon, and smoke. Among the five tailor made biofuel blends formulated, Blend 4 was the most promising with enhanced performances and lower emissions in comparison to B5 diesel though nitrogen oxide emissions were higher

doi:10.1093/nar/gkp302 Web services at the European Bioinformatics Institute-2009

The European Bioinformatics Institute (EMBL-EBI) has been providing access to mainstream databases and tools in bioinformatics since 1997. In addition to the traditional web form based interfaces, APIs exist for core data resources such as EMBL-Bank, Ensembl, UniProt, InterPro, PDB and ArrayExpress. These APIs are based on Web Services (SOAP/REST) interfaces that allow users to systematically access databases and analytical tools. From the user’s point of view, these Web Services provide the same functionality as the browser-based forms. However, using the APIs frees the user from web page constraints and are ideal for the analysis of large batches of data, performing text-mining tasks and the casual or systematic evaluation of mathematical models in regulatory networks. Furthermore, these services are widespread and easy to use; require no prior knowledge of the technology and no more than basic experience in programming. In the following we wish to inform of new and updated services as well as briefly describe planned developments to be made available during the course of 2009–2010