Evaluation of soybean/canola/palm biodiesel mixture as an alternative diesel fuel

466-470This study examines fuel properties and performance characteristics of diesel engine fueled with three different biodieselmixtures (soybean, canola and palm oils) and their blends with diesel fuel according to ASTM and EN standards. Viscosity andpour point of soybean-canola-palm (S-C-P) biodiesel blends were found out of standard ranges. Blend with soybean(25%) - canola (25%) - palm (25%) - diesel (25%) reached acceptable fuel properties (kinematic viscosity 4.3 mm2/s, cetanenumber 53, pour point -4°C). It performed 3% power loss with 8% higher specific fuel consumption. While CO and CO2emissions were reduced, NOx emissions were increased with increasing biodiesel contents in blends. As a result, diesel usage wasminimized to 25% by blending it with S-C-P biodiesels together

Islanding Detection in Microgrid Using Deep Learning Based on 1D CNN and CNN-LSTM Networks

Islanding detection is a critical task due to safety hazards and technical issues for the operation of microgrids. Deep learning (DL) has been applied for islanding detection and achieved good results due to the ability of automatic feature learning in recent years. Long short term memory (LSTM) and two dimensional (2D) convolutional neural networks (CNN) based DL techniques are implemented and demonstrated well performance on islanding detection. However, one dimensional (1D) CNN is more suitable for real-time implementations since it has relatively low complexity and cost-effective than 2D CNN. In this paper, for the first time, the 1D CNN and the combination of 1D CNN-LSTM are proposed for islanding detection to better exploit the global information of islanding data samples using the strengths of both networks. The proposed methods utilize only voltage and current harmonic measurements as input at the point of common coupling (PCC). About 4000 cases under the modified CERTS microgrid model are simulated to evaluate the performance of the proposed architectures. The simulation results and the presented analysis show that the proposed networks have achieved the maximum accuracy of 100% on the task of islanding detection; especially the proposed CNN-LSTM model outperforms the other approaches. Furthermore, the robustness of the proposed methods is demonstrated with unseen samples under low none detection zone and the expansion of microgrid topology

Micro hardness and water absorption properties of Cotton/Epoxy Bio-Composite

European Biotechnology Congress -- APR 26-28, 2018 -- Athens, GREECEWOS: 000454825900296

Preface to the special issue section on "International Mediterranean Science and Engineering Congress (IMSEC 2017), 25-27 October 2017, Adana, Turkey"

WOS: 000446144300001

Effect of bioethanol blending with gasoline on emissions characteristics with spark plug alteration for SI engine

European Biotechnology Congress -- APR 26-28, 2018 -- Athens, GREECEWOS: 000454825900293

Cotton/Epoxy Bio-Composite usage as an impact attenuator material for formula student race cars

European Biotechnology Congress -- APR 26-28, 2018 -- Athens, GREECEWOS: 000454825900297

A review on performance and emission characteristics of biodiesel produced from animal fat

European Biotechnology Congress -- MAY 25-27, 2017 -- Dubrovnik, CROATIAWOS: 000413585400366…Cukurova University Scientific Research Project Coordination [FED-2017-8866]The authors would like to express their gratitude to Cukurova University Scientific Research Project Coordination (FED-2017-8866) for financial support

Theoretical determination of maximum biodiesel blend ratios according to kinematic viscosity values

European Biotechnology Conference -- MAY 05-07, 2016 -- LATVIAWOS: 000380240300146

Comparison of transesterification and thermal cracking methods on fuel specifications of castor oil biodiesel

European Biotechnology Congress -- MAY 25-27, 2017 -- Dubrovnik, CROATIAWOS: 000413585400367…Cukurova University Scientific Research Project Coordination [FED-2017-8867]The authors would like to express their gratitude to Cukurova University Scientific Research Project Coordination (FED-2017-8867) for financial support

Thermodynamic analysis of a diesel engine fueled with diesel and sesame oil biodiesel

European Biotechnology Conference -- MAY 05-07, 2016 -- LATVIAWOS: 000380240300142