554 research outputs found
Stress Contours in The Connecting-rod under The Dynamic Load and The Oil Film’s Pressure of The Connecting-rod Big End
Under load apply to the connecting-rod and the pressure in the lubricant oil film change the stress in the connecting-rod during the operating cycle. This problem is the one of the characteristics we need to consider when studying the connecting-rod big end bearing. A specific experimental device and the connecting-rod model of photoelastic material are used to determine the load diagram, measure the oil film pressure, and visualize the state of stress. The connecting-rod is subjected to simulation load as in the engine. The lubricated oil film pressure is measured by the pressure sensor and also calculated by numerical modelization method with the same load diagram. The method chosen to visualize the stress state in the dynamically loaded connecting rod is the transmission photoelasticimetry. This method allows the visualization of the isochrones fringes, which are lines of equal difference regarding main stresses in the connecting-rod. The stress contour’s images of the connecting-rod at different angles of the crankshaft are realized by a CCD camera. The measured stress contours are compared to the calculated stress contours by the Algor software. The results show globally a correspondence between the experimental isochrones fields and the calculated isochrones fields
RELATIONSHIPS OF TEMPERATURE AND HUMIDITY TO THE BIODEGRADATION OF PETROLEUM HYDROCARBONS IN SOILS
This work focused on monitoring CO2production, microbial growth and residual hydrocarbon concentration during bioremediation experiments performed on laboratory soil microcosms. A natural soil was artificially contaminated with hexadecane and adjusted with inorganic nutrients to stimulate biodegradation. Microbial growth, CO2production and residual hexadecane were periodically monitored at different soil water contents ranging from 0.15 to 0.25 g water g_1 of dry soil and at different temperatures ranging from 20 to 25oC. Results showed that the humidity has a greater effect on microbial activity and contaminant degradation than the temperature. The study established the experimental regression equation of temperature and humidity to the hexadecane mineralization rate, an important parameter in assessing the ability to convert organic carbon into inorganic carbon. The difference between the results of the hexadecane mineralization rate obtained from the experiment and calculated from the regression equation is not too high, from 2% to 20%
Modelling Flowable Engineered Cementitious Composites and Its Fibre Orientation and Distribution for Tensile Performance Evaluation
University of Technology Sydney. Faculty of Engineering and Information Technology.Engineered Cementitious Composites (ECC) is a unique class of high-performance fibre reinforced cementitious composites (HPFRCC), exhibits high tensile ductility with the tensile strain capacity up to 5% with a moderately low synthetic fibres fraction (typically 2% or less by volume). ECC typically utilises short synthetic fibres, such as polyvinyl alcohol (PVA) or polyethylene (PE) fibres, which are tiny in diameter. These fibres are flexible, i.e. they can be bent or coiled in the matrix of ECC. Notably, the orientation of a bent or coiled fibre varies at different cross-sections of the specimen, leading to the divergence of ECC behaviour. Hitherto, a reliable approach that can provide a full understanding of the orientation and distribution of flexible synthetic fibres in the matrix of ECC and practical information of fibres orientation and distribution for estimating the tensile performance of ECC has not been reported.
In this PhD research, a numerical model was first developed to simulate the flow of fresh ECC, particularly focused on the flow characteristics of self-consolidating or flowable ECC. The numerical results of modelling several standard tests at the fresh state of flowable ECC, including the flow cones, V-funnel and U-box tests, were found to be consistent with experimental data. Through these validations, the developed model has proved its capability of providing insight into the flow behaviour of self-consolidating ECC in terms of filling, passing abilities and the distribution/orientation of flexible synthetic fibres at its fresh state. To take advantage on the understanding of the orientation distribution of flexible synthetic fibres from the developed model above, a novel fibre-bridging model at the hardened state of ECC was then proposed through considering the two-way pullout mechanisms of an arbitrary inclined fibre. The findings of the proposed fibre-bridging model reveal much better agreements with the experimental testing data in comparison with existing models, especially during the pullout stage of fibre. Finally, a novel approach was proposed for estimating the tensile performance of ECC through combining two states of ECC modelling
An Image-Based Rice Weighing Estimation Approach on Clock Type Weighing Scale Using Deep Learning and Geometric Transformations
AI impacts surrounding human life, such as the economy, health, education, and agricultural production; however, the crop prices in the harvest season are still on manual calculation, which causes doubts about accuracy. In this study, an image-based approach is proposed to help farmers calculate rice prices more accurately. YOLOv5 is used to detect and extract the scales in the images taken from the harvesting of rice crops. Then, various image processing techniques, such as brightness balance, background removal, etc., are compiled to determine the needle position and number on the extracted scale. Lastly, geometric transformations are proposed to calculate the weight. A real dataset of 709 images is used for the experiment. The proposed method achieves good results in terms of [email protected] at 0.995, mAP@[0.5:0.95] at 0.830 for scale detection, and MAE at 3.7 for weight calculation
Development of freshwater prawn (Macrobrachium rosenbergii) seed production and culture technology in the Mekong Delta Region of Vietnam: A review of the JIRCAS Project at Cantho University.
The Mekong Delta of Vietnam is a region rich in aquatic resources having high potential for aquaculture development. Inland aquaculture in the Mekong Delta has greatly increased since the last decade. Fish culture carried out in combination with other agricultural activities such as animal husbandry and rice cultivation, and intensive aquaculture in ponds and cages have been the dominant forms of fish production. However, the giant freshwater prawn, Macrobrachium rosenbergii, has recently become a species of economic significance and the target of aquaculture activity in the Mekong Delta. M. rosenbergii is cultured throughout the region in the rice fields, ponds, orchard gardens and in pens along river banks. The major constraints in this industry are seed supply and culture techniques, becoming the major obstacles for the further development of the culture of this species.
In a collaborative research project implemented between the Japan International Research Center for Agricultural Sciences (JIRCAS) and Cantho University (CTU) since 1994, studies have been carried out on various aspects relating to the establishment of M. rosenbergii seed production and culture technology. The project is now in the middle of its second phase and has generated a great deal of scientific and practical information. This paper presents an overview of the achievements of this project
LG-Hand: Advancing 3D Hand Pose Estimation with Locally and Globally Kinematic Knowledge
3D hand pose estimation from RGB images suffers from the difficulty of
obtaining the depth information. Therefore, a great deal of attention has been
spent on estimating 3D hand pose from 2D hand joints. In this paper, we
leverage the advantage of spatial-temporal Graph Convolutional Neural Networks
and propose LG-Hand, a powerful method for 3D hand pose estimation. Our method
incorporates both spatial and temporal dependencies into a single process. We
argue that kinematic information plays an important role, contributing to the
performance of 3D hand pose estimation. We thereby introduce two new objective
functions, Angle and Direction loss, to take the hand structure into account.
While Angle loss covers locally kinematic information, Direction loss handles
globally kinematic one. Our LG-Hand achieves promising results on the
First-Person Hand Action Benchmark (FPHAB) dataset. We also perform an ablation
study to show the efficacy of the two proposed objective functions
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