51 research outputs found
Combustion and emission characteristics of variable compression ignition engine fueled with Jatropha curcas ethyl ester blends at different compression ratio
No full textEngine performance and emission characteristics of unmodified biodiesel fueled diesel engines are highly influenced by their ignition and combustion behavior. In this study, emission and combustion characteristics were studied when the engine operated using the different blends (B10, B20, B30, and B40) and normal diesel fuel (B0) as well as when varying the compression ratio from 16.5 : 1 to 17.5 : 1 to 18.5 : 1. The change of compression ratio from 16.5 : 1 to 18.5 : 1 resulted in 27.1%, 27.29%, 26.38%, 28.48%, and 34.68% increase in cylinder pressure for the blends B0, B10, B20, B30, and B40, respectively, at 75% of rated load conditions. Higher peak heat release rate increased by 23.19%, 14.03%, 26.32%, 21.87%, and 25.53% for the blends B0, B10, B20, B30, and B40, respectively, at 75% of rated load conditions, when compression ratio was increased from16.5 : 1 to 18.5 : 1. The delay period decreased by 21.26%, CO emission reduced by 14.28%, and NO emission increased by 22.84% for B40 blends at 75% of rated load conditions, when compression ratio was increased from 16.5 : 1 to 18.5 : 1. It is concluded that Jatropha oil ester can be used as fuel in diesel engine by blending it with diesel fuel
Nozzle Spacing on Sprayer Boom
No full textAgricultural sprayers are frequently used to spray pesticides on standing crops to avoid pest attack. Nozzles are placed on sprayer boom in such a way that the chemical is spread evenly over the plant canopy. The spacing between the nozzles on the boom of commonly used sprayers is quite speculative and not based on the type of nozzle, the discharge from the nozzle, operating pressure, height of the boom, etc. A computer program was developed to select appropriate spacing between the nozzles based on operating pressure, height, spray pattern, etc. The best-suited nozzle spacing was calculated on the basis of overlap of the spread patterns., Coefficient of Variation was calculated for the different levels of overlap of the spread patterns. Spacing for which the Coefficient of Variation was minimum was taken as the best suitable spacing for nozzles on the sprayer boom. The program was validated by using operational parameters of a Triple Action Nozzle with a hollow cone spread pattern. The nozzle was operated at working pressure of 4.0 kglcm2, at a height of 40 cm moving at the forward speed of2.5 km/h. The best spacing was found to be around 57 cm. The program was also used to find out the number of nozzles required for a given boom length and the total volume of chemical sprayed per hectare
Probing potential Li-ion battery electrolyte through first principles simulation of atomic clusters
No full textRole of Ionic Liquid in Asphaltene Dissolution: A Combined Experimental and Molecular Dynamics Study
No full textThe role of ionic liquid in asphaltene dissolution is studied using experimental characterization techniques, such as optical microscopic imaging analysis, 13C nuclear magnetic resonance (NMR), and Fourier transform infrared (FTIR) spectroscopy, along with molecular insights achieved using classical molecular dynamics (MD) simulations. The dissolution behavior of the asphaltenes in 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6]) ionic liquid along with organic solvents, i.e., toluene and hexane, is investigated using optical images. The behavior of asphaltene aggregates in the solvent plus ionic liquid mixture is probed using FTIR and 13C NMR spectroscopic techniques. The structural and dynamical properties of the asphaltene aggregates mainly end-to-end distance, the diffusion coefficient of the asphaltene molecules, and the trajectory density contour of the asphaltene in the solvent plus ionic liquid mixture are probed using MD simulations. It is concluded from our combined experimental-MD study that the ionic liquid plays a key role in asphaltene separation from organic solvents under study.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Poulumi De
Studies on Selected Mechanized Solutions for Efficient Incorporation of Green Manure Crop
No full textA comparative study on incorporation of green manure crop (Sesbania aculeata) with a newly developed tractor operated biomass incorporator (BI) was conducted in contrast to prevailing technologies. Average depth of soil cut with BI (174.7 mm) was significantly higher than rotavator (71.3 mm), disc harrow (114 mm) and disc harrow plus cultivator (121 mm) at crop growth stage I (36 DAS) and stage II (50 DAS). Size of cut with BI (202 mm and 326.5 mm) was significantly lower than disc harrow, disc harrow pluscultivator and mould board plough at crop growth stage I and II. Field capacity of BI and conventional mould board plough was significantly lower than rotavator and disc harrow because of smaller width of coverage of two-bottom implements. Fuel consumption was significantly higher for rotavator at both stages of crop growth. Pulverization index was lowest with rotavator (6.70 mm and 6.98 mm), followed by BI, disc harrow plus cultivator, disc harrow and mould board plough at both crop stages. Bulk density index was significantly high for BI, followed by rotavator, mould board plough, disc harrow plus cultivator and disc harrow at both crop stages. Mixing index with BI (97.1 %) was significantly higher than all other implements. Biomass incorporator resulted in analogous mixing index at both crop stages. For all other implements, decrease in mixing index was recorded
Studies on Physical Properties of Pelleted Onion (Allium cepa L.) Seeds
No full textOnion (Allium cepa L.) is one of the major vegetable crops grown throughout India. Pelletizing of the onion seed by providing a seed coat helps in changing the physical characteristics of the seed. Experiment was conducted for studying the physical properties of pelleted onion seed and these were compared to un-pelleted seed. The onion seed of variety Punjab Naroya (PN) was used throughout the experiment. The physical properties namely size, shape, thousand grain weight, angle of repose, bulk density and coefficient of static friction are important from engineering view point. The seeds were got pelletized in three categories i.e. the seed to coating material was in the ratio of 1:1, 1:2 and 1:3. The geometric mean diameter was measured for the three categories are 2.45, 2.82, and 3.07 mm. In comparison, the geometric mean diameter for un-pelleted seed was 2.00 mm. The average values of angle of repose for the cultivars under study as observed in the laboratory was 29.50°, 24.78°, and 23.70° respectively for Pelleted 1:1, 1:2 and 1:3 onion seeds. In comparison, the average value of angle of repose for un-pelleted seed was 31.61°. The values of porosity are decreased in gradually un-pelleted to 1:1, 1:2 and 1:3 pelleted seeds whereas the porosity for 1:3 Pelleted seed was 41.84% and is the lowest amongst the other cultivars. The porosity of un-pelleted seed was the highest (53.3%)
Design of Ingenious Electronic Actuated Tractor Operated Liquid Urea Applicator
No full text92-101The paper contains the design, development details, and field performance of an ingenious electronic actuated tractor
operated liquid urea applicator. The fundamentals of farm machinery design were taken into consideration in order to design
and select the various components for the liquid urea applicator. The five-row prototype had a row spacing of 40 cm and
applied liquid urea at a spacing of 30 cm in each line. The cut-off mechanism was controlled electronically with the help of
a limit switch, sensor, solenoid valve, and relay. All the selected components in the designed electronic circuit for cut-off
mechanism were powered by 12V DC, and to function properly, power was taken from the tractor's battery. The applicator
was developed based on design calculations and then evaluated in the laboratory as well as in field conditions. During field
evaluation of the developed prototype, it was found that the application rate was 392 L∙h⁻1, actual field capacity was 0.36
ha∙h⁻1, fuel consumption was 11.3 L∙ha⁻1 with a 2.7 km∙h⁻1 forward speed of the machine. The developed machine is
suitable for applying liquid urea in the mulch field with minimum disturbance of soil, plant and residue. It would help in
curbing paddy straw burning and reduce fertilizer losses due to volatilization
Studies on Engineering Properties of Pelleted Carrot (Daucus carota L.) Seeds
No full text Carrot (Daucus carota L.) commonly known as Gajar. Certain limitations associated with the production, processing and effective utilization of small seeds. Carrot seeds are small in size and difficult to handle for sowing purpose. For the development of a mechanism for carrot seed sowing the study of engineering properties of carrot seeds is of utmost importance. The biometric properties of seeds play an important role in designing seed metering device. Physical and engineering properties of carrot seed both un-pelleted and pelleted were evaluated in the laboratory. Therefore, the physical properties of the carrot seeds such as size, shape, thousand grain weight, and angle of repose, bulk density and coefficient of static friction are important from engineering view point and were studied for cultivars of carrot i.e. deshi red pelleted were compared with un-pelleted carrot seeds. The geometric mean diameter (GMD) was 2.03, 2.19, 2.39 and 2.70 mm for deshi red carrot seeds, respectively. The average values of angle of repose for the cultivars under study as observed in the laboratory was 32.79°, 30.37°, 28.87° and 28.00° respectively for deshi red carrot seeds. The values of porosity are decreased gradually in seeds whereas the porosity for seed having GMD 2.70 mm was 50.84% and is the lowest amongst the other cultivars. The porosity of un-pelleted seed was the highest (64.96%)
LUVLi Pre-trained Model
No full text<p><strong>Introduction</strong></p>
<p>Modern face alignment methods have become quite accurate at predicting the locations of facial landmarks, but they do not typically estimate the uncertainty of their predicted locations nor predict whether landmarks are visible. In this paper, we present a novel framework for jointly predicting landmark locations, associated uncertainties of these predicted locations, and landmark visibilities. We model these as mixed random variables and estimate them using a deep network trained with our proposed Location, Uncertainty, and Visibility Likelihood (LUVLi) loss. In addition, we release an entirely new labeling of a large face alignment dataset with over 19,000 face images in a full range of head poses. Each face is manually labeled with the ground-truth locations of 68 landmarks, with the additional information of whether each landmark is unoccluded, self-occluded (due to extreme head poses), or externally occluded. Not only does our joint estimation yield accurate estimates of the uncertainty of predicted landmark locations, but it also yields state-of-the-art estimates for the landmark locations themselves on multiple standard face alignment datasets. Our method’s estimates of the uncertainty of predicted landmark locations could be used to automatically identify input images on which face alignment fails, which can be critical for downstream tasks.</p>
<p>To foster further research into this topic, we are publicly releasing our pre-trained LUVLi models. Please see our CVPR 2020 paper titled <a href="https://arxiv.org/abs/2004.02980">LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood</a> for details</p>
<p><strong>At a Glance</strong></p>
<p>-The size of the unzipped model is ~700MB.</p>
<p>-The unzipped folder contains: (i) a README.md file and (ii) pre-trained models and logs. The pre-trained models could be loaded in our publicly released LUVLi implementation.</p>
<p><strong>Other Resources</strong></p>
<p><strong>Citation</strong></p>
<p>If you use the LUVLi data in your research, please cite our paper:</p>
<pre><code>@inproceedings{kumar2020luvli,
title={{LUVLi} Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood},
author={Kumar, Abhinav and Marks, Tim K. and Mou, Wenxuan and Wang, Ye and Jones, Michael and Cherian, Anoop and Koike-Akino, Toshiaki and Liu, Xiaoming and Feng, Chen},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}
</code></pre>
<p><strong>License</strong></p>
<p>The LUVLi data is released under <a href="https://creativecommons.org/licenses/by-sa/4.0/">CC-BY-SA-4.0 license</a>.</p>
<p>All data:</p>
<pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2022,2023
SPDX-License-Identifier: CC-BY-SA-4.0
</code></pre>
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