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Distributed Lagrange Multiplier/Fictitious Domain Finite Element Method for a Transient Stokes Interface Problem with Jump Coefficients
No full textThe distributed Lagrange multiplier/fictitious domain (DLM/FD)-mixed finite element method is developed and analyzed in this paper for a transient Stokes interface problem with jump coefficients. The semi- and fully discrete DLM/FD-mixed finite element scheme are developed for the first time for this problem with a moving interface, where the arbitrary Lagrangian-Eulerian (ALE) technique is employed to deal with the moving and immersed subdomain. Stability and optimal convergence properties are obtained for both schemes. Numerical experiments are carried out for different scenarios of jump coefficients, and all theoretical results are validated
An IB Method for Non-Newtonian-Fluid Flexible-Structure Interactions in Three-Dimensions
No full textProblems involving fluid flexible-structure interactions (FFSI) are ubiquitous in engineering and sciences. Peskin’s immersed boundary (IB) method is the first framework for modeling and simulation of such problems. This paper addresses a three-dimensional extension of the IB framework for non-Newtonian fluids which include power-law fluid, Oldroyd-B fluid, and FENE-P fluid. The motion of the non-Newtonian fluids are modelled by the lattice Boltzmann equations (D3Q19 model). The differential constitutive equations of Oldroyd-B and FENE-P fluids are solved by the D3Q7 model. Numerical results indicate that the new method is first-order accurate and conditionally stable. To show the capability of the new method, it is tested on three FFSI toy problems: a power-law fluid past a flexible sheet fixed at its midline, a flexible sheet being flapped periodically at its midline in an Oldroyd-B fluid, and a flexible sheet being rotated at one edge in a FENE-P fluid
Rheological Studies on Glycerol Plasticized Gelatin and Its Blends with Epoxidized Soybean Oil
No full textBlends of gelatin (Ge) plasticized with varying amounts of glycerol (Gly), buffer solution pH 10 and epoxidized soybean oil (ESO) to enhance hydrophobicity were prepared by mixing and injection-molding. Blends were characterized by rheological tests and microscopy to select optimal conditions for scaling up their processing. The effect of each component on rheological response was analyzed using parallel plate geometry. Coating of gelatin specimens with PDMS during rheological tests led to reliable and reproducible results since water evaporation was prevented. A gradual increment in ESO concentration led to blends with increased degree of phase separation, as evidenced by optical and confocal microscopy. Limited compatibility between ESO and Ge increased viscosity at high ESO levels, but up to 10% Gly could be replaced with ESO without a significant variation of rheological behavior
Mapping of the Brazilian Groups Studying Nanocellulose
No full textThe nanocellulose is a material that has gained much attention in the recent years. So, the relevance of Brazil in this field was evaluated concerning the scientific publications in Web of Science. Next, the Brazilian groups were mapped using a bibliometric procedure on these data. Then, more factors were analyzed from them too. They were the sources to extract the nanocellulose in Brazil, the methods to do it, the characterizations to determine its dimensions and the funding agencies of these researches. The results identified 69 Brazilian groups. Besides, the bacterial cellulose was the most common source. While the acid hydrolysis was the most used method. By its turn, the size characterization was mostly by scanning electron microscopy. At last, the most important agencies were the CNPq, the CAPES and the FAPESP. Giving these points, it was possible to suggest the opportunities to develop the nanocellulose research in Brazil
Shear Strength of Unbound Crop By-Products Using the Direct Shear Box Apparatus
No full textThe return to old building methods by mixing crop by-products with mineral binders is arousing great interest in Europe since about 25 years. The use of these bio-aggregates based materials for the design of building envelopes is a valuable opportunity to deal with increasingly demanding thermal regulations. In addition, the regulatory framework is moving towards reducing the overall car-bon footprint of new buildings. Some traditional and historic buildings are based on timber framing with earth-straw as infill material for instance. Hemp concrete is a bio-based material that can be manually tamped in timber stud walls or more recently in the form of precast blocks. Owing to their low compressive strength, bio-based concretes using a large volume fraction of plant-derived aggregates are only considered as thermal and sound insulation materials. The structural design practice of wood frame walls does not assume any mechanical contribution of hemp concrete whereas it may contribute to the racking strength of the structure. In this context, more research is needed regarding the shear behavior of crop by-products and bio-based concretes. In this case, the objective of the study was to perform direct shear tests under three levels of normal pressure on hemp shiv and rice husk as unbound crop by-products. The results showed that the friction angle of the granular skeleton based on rice husk for a given relative displacement was significantly lower than that measured on hemp shiv. This is in accordance with what had been observed on bio-based concretes cast by mixing aggregates with lime and shear strength parameters measured by means of triaxial compression
Development of CaO From Natural Calcite as a Heterogeneous Base Catalyst in the Formation of Biodiesel: Review
No full textBiodiesel is a fossil fuel that is in demand to be developed because it is bio-renewable, biodegradable and environmentally friendly. Biodiesel produced from the transesterification reaction of vege Tab. oil using a base catalyst. CaO is the most developed catalyst for the reaction of transesterification of oil into biodiesel because it is cheap, the process is easy and has a high level of alkalinity. CaO is a cheap catalyst because it is easily obtained from natural ingredients. The use of CaO catalysts in the reaction formation of biodiesel continues to develop through modification with various porous materials and different oxide materials. In this paper, we discuss the development of CaO, the modification of CaO with a porous material and metal oxide, the mechanism of reaction of CaO and the kinetics of reactions that occur in the reaction transesterification of oil to biodiesel
Biocompatible Blends Based on Poly (Vinyl Alcohol) and Solid Organic Waste
No full textThis work is aimed at the development of new green composite materials through the incorporation of the solid organic waste (SOW) in a thermoplastic matrix. After being ground, the organic waste was exposed to a sterilization process, though an autoclave cycle, in order to obtain a complete removal of the bacterial activity. The SOW was found to have a high amount of water, about 65-70%, which made uneconomical its further treatment to reduce the water amount. Therefore, a water soluble polymer, poly (vinyl alcohol) (PVA) was chosen in order to produce SOW based blends. However, in order to reduce the viscosity of the PVA/SOW slurry, further amount of water was added. The very low viscosity attained by the water suspension allowed to process the PVA/SOW blends by a pressure-free process, for the production of samples, which were afterwards subjected to physical and mechanical characterization. Flexural tests showed the promising properties of the developed blends. In particular, the relevance of porosity was assessed. Increasing the water amount involved a signification increase of porosity, due to a faster water evaporation during processing. On the other hand, compared to neat PVA, addition of SOW allowed to significantly decrease the porosity of the produced samples. Despite this, the mechanical properties of the PVA/ SOW blends were shown to be lower than those of neat PVA processed analogously
Development of Non-Dissipative Direct Time Integration Method for Structural Dynamics Application
Get PDFA direct time integration scheme based on Gauss-Legendre quadrature is proposed to solve problems in linear structural dynamics. The proposed method is a one-parameter non-dissipative scheme. Improved stability, accuracy, and dispersion characteristics are achieved using appropriate values of the parameter. The proposed scheme has second-order accuracy with and without physical damping. Moreover, its stability, accuracy, and dispersion are analyzed. In addition, its performance is demonstrated by the two-dimensional scalar wave problem, the single-degree-of-freedom problem, two degrees-of-freedom spring system, and beam with boundary constraints. The wave propagation problem is solved in the high frequency wave regime to demonstrate the advantage of the proposed scheme. When the proposed scheme is applied to solve the wave problem, more accurate solutions than those of other methods are obtained by using the appropriate value of the parameter. For the single-degree-of-freedom system, two degrees-of-freedom system, and the time responses of beam, the proposed scheme can be used effectively owing to its high accuracy and lower computational cost
A Trajectory Planning-Based Energy-Optimal Method for an EMVT System
Get PDFIn this paper, a trajectory planning-based energy-optimal method is proposed to reduce the energy consumption of novel electromagnetic valve train (EMVT). Firstly, an EMVT optimization model based on state equation was established. Then, the Gauss pseudospectral method (GPM) was used to plan energy-optimal trajectory. And a robust feedforward-feedback tracking controller based on inverse system method is proposed to track the energy-optimal trajectory. In order to verify the effectiveness of the energy-optimal trajectory, a test bench was established. Finally, co-simulations based on MATLAB Simulink and AVL Boost were carried out to illustrate the effect of energy-optimal trajectories on engine performance. Experimental results show that the robust tracking controller can achieve good position tracking performance. And these energy-optimal trajectories can save up to 40% of the energy consumption compared with the conventional camshaft valve trajectories
Estimating the Properties of Ground-Waste-Brick Mortars Using DNN and ANN
Get PDFIn this study, deep-neural-network (DNN)- and artificial-neural-network (ANN)-based models along with regression models have been developed to estimate the pressure, bending and elongation values of ground-brick (GB)-added mortar samples. This study is aimed at utilizing GB as a mineral additive in concrete in the ratios 0.0%, 2.5%, 5.0%, 7.5%, 10.0%, 12.5% and 15.0%. In this study, 756 mortar samples were produced for 84 different series and were cured in tap water (W), 5% sodium sulphate solution (SS5) and 5% ammonium nitrate solution (AN5) for 7 days, 28 days, 90 days and 180 days. The developed DNN models have three inputs and two hidden layers with 20 neurons and one output, whereas the ANN models have three inputs, one output and one hidden layer with 15 neurons. Twenty-five previously obtained experimental sample datasets were used to train these developed models and to generate the regression equation. Fifty-nine non-training-attributed datasets were used to test the models. When these test values were attributed to the trained DNN, ANN and regression models, the brick-dust pressure as well as the bending and elongation values have been observed to be very close to the experimental values. Although only a small fraction (30%) of the experimental data were used for training, both the models performed the estimation process at a level that was in accordance with the opinions of experts. The fact that this success has been achieved using very little training data shows that the models have been appropriately designed. In addition, the DNN models exhibited better performance as compared with that exhibited by the ANN models. The regression model is a model whose performance is worst and unacceptable; further, the prediction error is observed to be considerably high. In conclusion, ANN- and DNN-based models are practical and effective to estimate these values