Mohammad Isa Irawan

Neural Network-Based Engine Propeller Matching (NN-EPM) for Trimaran Patrol Ship

In recent years efforts on reducing fuel consumption has become the greatest issue related to energy crisis and global warming. The reduction of fuel consumption can be obtained, if the ship propulsion could be operated in its best performance level. Generally this is done by an appropriate analysis of engine propeller matching (EPM). In this study an EPM based on neural-network method, or NN-EPM, is established to predict the best performance of main engines, leading at minimum fuel oil consumption. A trimaran patrol ship is selected as a case study. This patrol ship is equipped with two 2720 kW main engines each connected to a controllable pitch propeller (CPP) through a reduction gear. The input parameters are ship speed V and service margin SM, with the corresponding output parameters comprise of engine speed nE, engine break horse power PB, propeller pitch P/D, and the fuel consumption FC. An NN-EPM 2-20-15-4 configuration has been constructed out of 100 training data and then validated by 30 testing data. The maximum relative error between results from NN-EPM and EPM analysis is 2.1%, that is in term of the fuel consumption. For other parameters the errors are well below 1.0%. These facts indicate that the use of NN-EPM to predict the main enginess performance for trimaran patrol ship is satisfactory.

Reverse Transcription-PCR analysis of geranylgeranyl diphosphate synthase (JcGGPPS) in Jatropha curcas L. and in silico analysis of Casbene Synthase (JcCS) among Euphorbiaceae

Recently, Euphorbiaceae have attracted much attention for their potential uses in biodiesel production. Their seeds have been well known as the principal resource for oil production. The seed-derived oil content ranged from 28 % to 39 % by dry weight for all Euphorbiaceae species. Meanwhile, their seed also possesses relatively high protein content, ranged from 22 % to 35 %, making them a new alternative for livestock animal feed resources. Nevertheless, the development of this new animal feed resource is limited to the toxicity of the seeds. Its toxicity is mainly caused by the presence of anti-nutrient agents and toxins, such as curcin, trypsin inhibitor and phorbol ester (PE). The later is known to be tetracyclic diterpenes, which represents the primary toxic substances in one of the Euphorbiaceae plants, Jatropha curcas L. To date, little is known about the biosynthesis of these toxic substances. This research aims to analyze the expression of JcGGPPS gene encoding the geranylgeranyl diphosphate synth...

Transcription profile data of phorbol esters biosynthetic genes during developmental stages in Jatropha curcas

Jatropha curcas is currently known as an alternative source for biodiesel production. Beside its high free fatty acid content, J. curcas also contains typical diterpenoid-toxic compounds of Euphorbiaceae plant namely phorbol esters. This article present the transcription profile data of genes involved in the biosynthesis of phorbol esters at different developmental stages of leaves, fruit, and seed in Jatropha curcas. Transcriptional profiles were analyzed using reverse transcription-polymerase chain reaction (RT-PCR). We used two genes including GGPPS (Geranylgeranyl diphospate synthase), which is responsible for the formation of common diterpenoid precursor (GGPP) and CS (Casbene Synthase), which functions in the synthesis of casbene. Meanwhile, J. curcas Actin (ACT) was used as internal standard. We demonstrated dynamic of GGPPS and CS expression among different stage of development of leaves, fruit and seed in Jatropha.