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Violin studies can be classified into two main types: psychoacoustic studies, which are based on the artistic perception of audibility by violinists and vibro-acoustic studies, which are based on the spectral analysis of the vibrations and sounds produced by the instruments. The paper presents the acoustic analysis of violins by means of specialized software, their main acoustic characteristics being extracted in the form of frequency spectrum, spectrograms, specific modes and number of harmonics. These results were compared with the results of the opinion poll among musicians regarding the acoustic qualities of violins, based on musical auditions. The results highlighted the fact that the acoustic analysis technique cannot detect in totality the psycho-acoustic effects of musical sounds, therefore the establishment of the acoustic quality of the instruments on objective foundations, since the personal touch of an instrumental artist aims at the approach and articulation of the musical discourse, in a complex manner, combined with the interpretation of forms and styles.

The paper presents the interdisciplinary approach of two fields - the artistic (musical) and technical (forestry engineering, wood processing engineering, mechanical and physical engineering) apparently opposite but which can be happily exploited for both parties. Thus, we can speak of a new paradigm of education through which art can combine with the technical sciences for the benefit of all. The aim of the paper is to present experimental methods in mechanical and acoustic evaluation of violins from engineering and artistic perspectives. The presented results are part of a larger study carried out within an experimental demonstration research project.

A fully transient discrete-source 3D Additive Manufacturing (AM) process model was coupled with a 3D stochastic solidification structure model to simulate the grain structure evolution quickly and efficiently in metallic alloys processed through Electron Beam Powder Bed Fusion (EBPBF) and Laser Powder Bed Fusion (LPBF) processes. The stochastic model was adapted to rapid solidification conditions of multicomponent alloys processed via multi-layer multi-track AM processes. The capabilities of the coupled model include studying the effects of process parameters (power input, speed, beam shape) and part geometry on solidification conditions and their impact on the resulting solidification structure and on the formation of inter layer/track voids. The multi-scale model assumes that the complex combination of the crystallographic requirements, isomorphism, epitaxy, changing direction of the melt pool motion and thermal gradient direction will produce the observed texture and grain morphology. Thus, grain size, morphology, and crystallographic orientation can be assessed, and the model can assist in achieving better control of the solidification microstructures and to establish trends in the solidification behavior in AM components. The coupled model was previously validated against single-layer laser remelting IN625 experiments performed and analyzed at National Institute of Standards and Technology (NIST) using LPBF systems. In this study, the model was applied to predict the solidification structure and inter layer/track voids formation in IN718 alloys processed by LPBF processes. This 3D modeling approach can also be used to predict the solidification structure of Ti-based alloys processes by EBPBF.

This paper presents the results of an experimental study performed on seven violins obtained from a top plate made of resonance spruce and a back plate made of curly maple. Each pair of plates had a different modification to its thickness profile. Some were thickened and others were thinned compared to the classical thickness profile. Then, a soloist played a musical sequence on each violin and the acoustic signals were recorded. The sound quality of the signals was evaluated with a psycho-acoustic evaluation based on a blind questionnaire completed by listeners. It turned out that: (1) respondents with more musical experience (especially those with over 26 years of experience) were more demanding in assessing sound clarity and offered the widest range of scores in assessing this quality; (2) the musical experience of the respondents influenced to the highest degree the appreciation of the warm sound quality; (3) the scores for the violins with thinned plates were weaker, especially according to the psycho-acoustic analysis; and (4) the highest score was obtained by the violin with the thickest plates, which can be correlated with the two dominant frequencies extracted from the FFT analysis, whose values coincide with the frequencies of the B1− and B1+ modes.

In this study, three machine learning (ML) models were developed to predict the secondary dendrite arm spacing (SDAS) and then predictions were validated experimentally. First, a three-layer artificial neural network (ANN) was built to predict the SDAS. Then, a linear regression model (LR) with backward selection method is applied to study the relationship of different elemental properties, processing parameters, and SDAS and make a prediction. A principle component analysis (PCA) further explores these relationships. The results show that the ANN model has the best performance compared with the LR and PCA models. Compared with the classical coarsening equation, the current SDAS predictions reveal a deviation from nearly linear relationship with the negative cubic root of cooling rate, which indicates there are other elemental properties that should be accounted for.

A transient 3D multiscale model has been created to simulate the evolution of solidification microstructures rapidly and effectively in Ti6Al4V parts produced through Laser Powder Bed Fusion (LPBF). The microstructure simulation tool has been enhanced to account for rapid solidification conditions in Ti6Al4V alloys during processing of multi-layer multi-track LPBF parts. The simulation tool can evaluate the impact of part geometry, lase power input, laser speed, and laser beam shape on the formation of the microstructure in LPBF-processed Ti6Al4V alloy. The multiscale model considers several factors, including preferential crystallographic growth direction, isomorphism, epitaxy, melt pool motion, and temperature gradients to generate the observed texture and morphology of the microstructure in Ti6Al4V components. The model can evaluate various microstructure characteristics, such as grain size and texture. Consequently, it could aid in controlling the formation of solidification microstructures in Additive Manufacturing (AM) processed parts. The simulation tool has been previously validated by using IN625 laser remelting experiments made by National Institute of Standards and Technology. The 3D simulation tool can also be utilized to predict the microstructure formation in Ti6Al4V components produced by the Electron Beam AM processes.

Background Medical technology is far from reaching its full potential. An area that is currently expanding is that of precision medicine. The aim of this article is to present an application of precision medicine-a deep-learning approach to computer-aided diagnosis in the field of dermatology. Materials and methods The main dataset was proposed in the edition of the ISIC Challenge that took place in 2019 and included 25 331 dermoscopic images from eight different categories of lesions-three of them were malignant and five benign. The behavior of the model was also tested on a dataset collected from the second Department of Dermatology, of the Colentina Clinical Hospital. Results The overall accuracy of the model was 78.11%. Of the total 5031 samples included in the test subset, 3958 were correctly classified. The accuracy of the model on the clinical dataset is lower than that obtained in the first instance. Conclusion The architecture of the model can be considered of general use, being able to be adapted in an optimal way for a wide range of classifications. The model has achieved performance within the expected limits but can be further improved by new methods.

Chemical polymerization of o-phenylenediamine (OPD) in the presence of poly(ethylene oxide), double-wall carbon nanotubes (DWNTs) and ferric chloride is carried out in order to obtain composites based on the poly(o-phenylenediamine)-poly(ethylene oxide) (POPD-PEO) fibres covered and interconnected with DWNTs. Vibrational and photoluminescence properties of these composite materials as well as their morphologies are shown by infrared (IR) spectroscopy, Raman scattering, photoluminescence (PL) and scanning electron microscopy (SEM). An adsorption of DWNTs onto the POPD rods surface in the absence and in the presence of PEO is highlighted by SEM. The vibrational changes reported by Raman scattering and IR spectroscopy prove a covalent functionalization of DWNTs with the macromolecular compound POPD which is doped with FeCl−4 ions. New hydrogen bonds are generated between POPD covalently functionalized DWNTs and hydroxyl groups of PEO according to IR spectroscopic studies. The two macromolecular compounds, POPD and POPD-PEO, show a complex emission band with maxima at 572 and 566 nm, having a shoulder at 667 nm. A significant change in the profile of the PL bands of POPD and POPD-PEO is induced in the DWNTs presence. We show that DWNTs induce (i) a diminution in the POPD PL band intensity peaked between 525–600 nm simultaneous with the increase in the intensity of the PL band situated in the 600–800 nm spectral range and (ii) an enhancement process of the emission band localized in the 475–800 nm spectral range in the case of POPD-PEO.

This research investigated the potential of some European wood species for use in the manufacturing of the back plates of violins as an alternative to the quite rare curly maple wood. An experimental modal analysis was employed for this purpose using the impact hammer method. The modal analysis was performed both on the top and back plates, as individual structures, and then after being integrated into the violin body. The modal analysis envisaged the determination of the eigenfrequencies (natural frequencies), the number of spectral components, and the quality factor, as important indicators of the acoustic performances of a musical instrument. A multi-criteria analysis based on the values obtained for these indicators allowed interesting findings concerning the acoustic properties of the selected wood species (hornbeam, willow, ash, bird-eye maple, walnut, and poplar). Same as curly maple, they all have special aesthetics, but only hornbeam, willow, and ash wood proved to have acoustic potential as well.

The residual strains in three high-pressure die cast A383 engine blocks were measured using neutron diffraction. Residual strains and stresses can be generated during high-pressure die casting process due to high thermal gradients and may cause fatigue failure or dimensional distortion. Neutron diffraction can measure the residual strain distributions deep inside castings with complex geometries, because neutrons can penetrate substantially more material than x-rays. In the present work, the residual strains (in the axial and hoop directions) along the whole cylinder bridge of high-pressure die cast A383 engine blocks in as-cast and heat-treated conditions were measured by neutron diffraction methods. The effect of heat treatment on the distribution and magnitude of residual strains was also investigated. The results indicate that the residual strain in the cylinder bridge is tensile in both the axial and hoop components for both the as-cast and the heat-treated engine blocks. The residual strain in the hoop direction is bigger in magnitude than the residual strain in the axial direction. Heat treatment significantly relaxes the residual strain in the axial direction but only slightly relaxes the residual strain in the hoop direction.

In this study, a chromium carbide layer was fabricated by an in-situ casting technique on ductile iron cast components. The procedure consists of (i) applying a ferrochrome slurry at the surfaces o...

Laboratory scale experimental and modeling results of one-sided upward flame spread over wavy cellulosic paper samples are presented. The sinusoidal shaped samples with varying wavelength and ampli...

In the present study, the fundamental model for interfacial heat transfer coefficient (IHTC) in high-pressure die-casting (HPDC) developed by Hamasaiid et al. is re-examined using numerical simulations and established literature. The role of impact pressure on the peak IHTC is re-evaluated for the Aluminum alloy Al-9Si-3Cu and the magnesium alloy AZ91D. Currently, ANSYS FLUENT does not have a mesh independent model for air gap evolution at the die-casting boundary. To address this, an implementation of the Hamasaiid model is built for ANSYS FLUENT 18.1 and its results are compared to experimental work. All the derivations and code for the simulations are offered as open source under the GNU General Public License v3.0.

In this work, we propose a cost-effective procedure to obtain magnetic single cotton yarns by employing commercially available magnetic powders and adhesives. Two different indirect magnetization methods are used on the yarns coated with several mixtures containing barium hexaferrite (BaFe12O19) as hard magnetic powder. The BH mass percentage is varied between 10% and 50%. Specific textile coating binders such as polyurethane and polyvinyl acetate are used as adhesives. A constant amount of 5% glycerol is employed as plasticizer agent. An in-house developed laboratory equipment is used to produce the magnetic cotton yarns. The equipment allows primary orientation of the magnetic particles along external field lines and subsequent magnetization until saturation. Our studies show that the diameter of the coated yarns is directly dependent on the amount of magnetic powder in the coating solution. Thus, the magnetic yarn diameter increases by 30% when compared to the 356µm diameter of the reference (uncoated) yarn for a barium hexaferrite mass percentage of 50%. Also, our studies reveal that increasing the magnetic properties (residual magnetism and coercive field intensity) of the composite yarns is possible only by increasing the mass percentage of the magnetic powder content. The highest values of the magnetic properties have been measured when neodymium permanent magnets (NdFeB) were used for the magnetization instead of a toroidal coil. The residual magnetization and saturation increase with the amount of barium hexaferrite embedded in the textile yarn. However, the increase in mass percentage is limited by the degradation of the yarn properties which allow them to be used for textile applications. SEM images of the coated yarns reveal a relatively uniform deposition of magnetic layer on the reference cotton yarn. publishedVersion

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We show how our algorithm identifies a number of potentially efficient drugs for breast, ovarian, and pancreatic cancer. We demonstrate our algorithm on several benchmark networks from cancer medicine, social networks, electronic circuits, and several random networks with their edges distributed according to the Erdös-Rényi, the scale-free, and the small world properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches.

Recently, a few computational methodologies and algorithms have been developed to simulate the microstructure evolution in powder bed fusion (PBF) additive manufacturing (AM) processes. However, none of these have attempted to simulate the grain structure evolution in multitrack, multilayer AM components in a fully 3D transient mode and for the entire AM geometry. In this work, a multiscale model, which consists of coupling a transient, discrete-source 3D AM process model with a 3D stochastic solidification structure model, was applied to quickly, efficiently, and accurately predict the grain structure evolution of IN625 alloys during Laser Powder Bed Fusion (LPBF). The capabilities of this model include studying the effects of process parameters and part geometry on solidification conditions and their impact on the grain structure formation within multicomponent alloy parts processed via AM. Validation was accomplished based on single-layer LPBF IN625 benchmark experiments, previously performed and analyzed at the National Institute of Standards and Technology (NIST), USA. This modeling approach can also be used to quantitatively predict the solidification structure of Ti-6Al-4V alloys in electron beam AM processes.

Characterization of unsteady loads is critical for the development of control systems for next-generation air vehicles. Both Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) methods are prohibitively expensive, and existing Reynolds-Averaged Navier-Stokes (RANS) approaches have been shown to be inadequate in predicting both mean and unsteady loads. In recent years, scale-resolving methods, such as Partially Averaged Navier-Stokes (PANS) and Detached Eddy Simulation (DES), have been gaining acceptance and filling the gap between RANS and LES. In this study, we focus on a new variant of the PANS method, namely blended PANS or BPANS, which was shown to perform well in the incompressible regime for both wall-bounded and free shear flows. In this paper, we extend BPANS to compressible supersonic flows by adding a compressibility correction, leading to a new model called BPANS CC. The new model is tested using a well-known supersonic mixing layer case, and the results show good agreement with experimental data. The model is then used on a complex supersonic retropropulsion case and the results are in good agreement with experimental data.

A 3D transient CFD–reaction coupled model is developed to predict the slag–metal reaction and desulphurization kinetics in ladle furnace with both molten slag and air layers considered. The coupled...

The combined effects of heat treatment and strontium (Sr) additions on the microstructure and mechanical properties of high pressure die cast A383 alloy components were investigated. A series of high pressure die cast engine components were produced using combined Sr additions and heat treatments. The resulting micro- and nanostructures were characterized using optical and electron microscopies. The tensile behavior was measured for material taken from the bulkhead sections of the engine bock. The results showed that Sr additions increased the elongation, but not the strength, of as-cast A383 alloys due to the refinement of the Al–Si eutectic. Heat treatment combined with Sr addition improved the strength because of the formation of fine nano-precipitates with a high number density. The results suggest that the formation of these precipitates may be affected by the Sr additions. This same combination also improved the ductility by maintaining the small size and roundness of the Al–Si eutectic particles.

In this work, synthesis and optical properties of a new composite based on poly(o-phenylenediamine) (POPD) fiber like structures, poly(vinylidene fluoride) (PVDF) spheres and double-walled carbon nanotubes (DWNTs) are reported. As increasing the PVDF weight in the mixture of the chemical polymerization reaction of o-phenylenediamine, the presence of the PVDF spheres onto the POPD fibers surface is highlighted by scanning electron microscopy (SEM). The down-shift of the Raman line from 1421 cm−1 to 1415 cm−1 proves the covalent functionalization of DWNTs with the POPD-PVDF blends. The changes in the absorbance of the IR bands peaked around 840, 881, 1240 and 1402 cm−1 indicate hindrance steric effects induced of DWNTs to the POPD fiber like structures and the PVDF spheres, as a consequence of the functionalization process of carbon nanotubes with macromolecular compounds. The presence of the PVDF spheres onto the POPD fiber like structures surface induces a POPD photoluminescence (PL) quenching process. An additional PL quenching process of the POPD-PVDF blends is reported to be induced in the presence of DWNTs. The studies of anisotropic PL highlight a change of the angle of the binding of the PVDF spheres onto the POPD fiber like structures surface from 50.2° to 38° when the carbon nanotubes concentration increases in the POPD-PVDF/DWNTs composites mass up to 2 wt.%.

Background:Diabetic ketoacidosis is an acute major life-threatening complication of diabetes, characterized by hyperglycemia, ketoacidosis and ketonuria, which can be life threatening if it is not promptly recognized and treated. This occurs mainly in patients with type 1 diabetes, but stressors like trauma and infection can increase the risk of ketoacidosis in other forms of diabetes such as type 2 diabetes. Type 2 diabetes mellitus is a complex metabolic disorder of heterogeneous etiology with behavioral, social, and environmental risk factors that unmask the effects of genetic susceptibility. Recent studies indicate an increasing prevalence of type 2 diabetes mellitus in children and adolescents around the world in all ethnicities. C-peptide is a useful and widely used method of assessing pancreatic beta cell function given his structure: part of proinsulin which is cleaved prior to co-secretion with insulin from pancreatic beta cells. This is used as a tool in the differentiation of type 1 diabetes from type 2 but also other types of diabetes. We present a 12-year-old previously healthy male who was hospitalized in our clinic for polydipsia, polyuria, weight loss and emesis, with symptom onset 10 days prior to admission. On the admission day, he presented to the emergency room for progressively increasing somnolence, apathy, decreased muscle tone and urinary incontinence. Physical examination was significant for grade I obesity [height 168 cm and weight 90 kg, yielding a body index mass (BMI) of 31.78 kg/m2, percentile >97%], lethargy, slurred speech, high blood pressure (145/90 mmHg), tachycardia (145 beats per minute) and acanthosis nigricans. Considering his physical examination, laboratory tests and clinical evolution, he was diagnosed with type 2 diabetes mellitus complicated with hyperosmolar hyperglycemic state and diabetic ketoacidosis. Diabetic ketoacidosis should be considered in the differential diagnosis of metabolic decompensation in all types of diabetes. Although type 2 diabetes mellitus seems to be still rare in childhood and adolescence, prevention and treatment of type 2 diabetes mellitus should become public awareness and public health intervention programs. The particularity of this case was the unusual onset of diabetes mellitus type 2 in a male child with metabolic syndrome.

This paper addresses the experimental and numerical dynamic analysis of curved bars used as percussion musical instruments. These structures are known as triangles, being made of various metal materials. The study was based on the experimental analysis of the dynamic response over time and the frequency of three types of triangles, different in material and size. Subsequently, finite element analysis of the same structures modeled with the SimCenter 12 program was performed. The results were compared, highlighting the contribution of material type and geometry in obtaining vibration modes, frequency spectrum, and structural damping coefficient. Between the experimental and the numerical analysis, the obtained errors were below 2.2% in terms of their natural frequencies. The study also highlights the complementarity of the two methods in understanding the vibration modes of triangles.

In the current study, a stochastic mesoscopic model was applied to predict the evolution of the A356 microstructure (e.g., dendritic morphologies and columnar-to-equiaxed transition formation) in a 2-Zone induction melting and solidification furnace. The influence of process and material parameters on microstructure, such as initial melting temperature, ultrasonic stirring and cavitation, fluid flow conditions, cooling rate, temperature gradient, and nucleation and growth kinetics parameters for both equiaxed and columnar phases, is studied. In addition, the initial transient of the macro-segregation of silicon during solidification of A356 in the crucible is also simulated. The results will be helpful for determining the solidification structure, mushy zone evolution in the crucible and assist in developing of comprehensive solidification maps of alloys used in additive manufacturing.

A numerical model was developed to simulate the current density distribution and secondary resistances for the aluminum electrorefining process from the room temperature ionic liquid (RTIL) consisting of 1-butyl-3-methylimidazolium chloride and aluminum chloride with the molar ratio of 2:1 (AlCl3: BMIC). The materials and geometry were created based on the experimental parameters. The current density distribution was calculated via simulation. The effects of applied voltage, temperature, composition of the electrolyte, and the surface roughness of cathode on the secondary resistances were investigated in this research. It was found that the summation of contact and charge transfer resistance decreases with increasing the potential and the temperature as well as decreasing the surface roughness.

We live in an environment where it is debated whether there is a causality between pollution and climate change, which has a negative impact on both human health and nature. Because of this, determining and improving air quality has become a priority in today's society. Combustion of fossil fuels, industrialization or meteorological factors play a significant role in air pollution. Consequently, the society becomes interested in the existence of an application that provides a real-time air quality index of a certain geographical area, as well as a forecast on this air quality index for a few hours or days. Therefore, this paper proposes a practical solution for a faster adaptation of the human user by creating a database with information about polluted areas in the city. As a result, a person will be able to know the air quality both in the area where he finds himself, as well as in another location where he wants to move.

Traditional weather forecasting, using physical methods, requires a lot of computational power and is generally slow. Modern developments in machine learning have led us to experiment with weather prediction using those newly available tools. In this article, we will present the capabilities, advantages and shortcomings of neural networks in the context of weather prediction. The tools consist of open source machine learning libraries, freely available data and two off the shelf computers for all the experiments, in order to show that weather forecasting can be done in a cost-efficient manner.

Human interaction and behavior were proven to be decisive factors for disease spread among the members of a community. Recent events, determined by the COVID-19 outbreak, forced us to develop methods of control, in order to lower the reproductive number and overall, reduce the number of cases. We propose a software simulation method centered on in what manner a virus spreads inside a closed space. This approach required the implementation of a simplified model of human behavior, while considering the factors that influence the rate of transmission between individuals. Agent-based simulation allowed us to identify different control and prevention means, which are efficient in reducing the natural evolution of a pandemic. The results of the analysis offered insight into the rate of spread and human behavior, or habits that led to a significant increase in the total number of infected agents. Recent literature discussed the simulation of disease spread among the inhabitants of larger areas or studied the way that the pathogen can be spread from person to person through droplets containing the virus. Though we strongly consider that previous studies offer important insight, preventing the spread among smaller groups can let us maintain our activity in a safe and supervised manner. The model has been validated by a series of simulations with respect to COVID-19 real data.

This paper deals with the area of structural damage monitoring of steel strands wire ropes embedded into various equipment and mechanical systems. Of the currently available techniques and methods for wire ropes health monitoring, the authors focused on the group of techniques based on operational dynamics investigation of such systems. Beyond the capability and efficiency of both occasionally and continuously monitoring application, the dynamics-based methods are able to provide additional information regarding the structural integrity and functional operability of the entire ensemble embedding the wire ropes. This paper presents the results gained by the authors using a laboratory setup that can simulate the operational condition usually used for regular applications of wire ropes. The investigations were conducted on three directions of acquired signals post-processing. Firstly, the classical fast Fourier transform was used to evaluate the potential changes within the spectral distribution of transitory response. The other two directions involved high-order spectral analyses in terms of bi-spectrum and Wigner&ndash, Ville distribution and multi-scale analysis based methods such as complex wavelet cross-correlation and complex wavelet coherency. The results indicate that each direction of analysis can provide suitable information regarding potential wire rope damage, but the ensemble of post-processing methods offers supplementary precision.

The Lagrange&rsquo, s equation remains the most used method by researchers to determine the finite element motion equations in the case of elasto-dynamic analysis of a multibody system (MBS). However, applying this method requires the calculation of the kinetic energy of an element and then a series of differentiations that involve a great computational effort. The last decade has shown an increased interest of researchers in the study of multibody systems (MBS) using alternative analytical methods, aiming to simplify the description of the model and the solution of the systems of obtained equations. The method of Kane&rsquo, s equations is one possibility to do this and, in the paper, we applied this method in the study of a MBS applying finite element analysis (FEA). The number of operations involved is lower than in the case of Lagrange&rsquo, s equations and Kane&rsquo, s equations are little used previously in conjunction with the finite element method (FEM). Results are obtained regardless of the type of finite element used. The shape functions will determine the final form of the matrix coefficients in the equations. The results are applied in the case of a planar mechanism with two degrees of freedom.

The structure of wind turbine blades (WTBs) is characterized by complex geometry and materials that must resist various loading over a long period. Because of the components’ exposure to highly aggressive environmental conditions, the blade material suffers cracks, delamination, or even ruptures. The prediction of the damage effects on the mechanical behavior of WTBs, using finite element analysis, is very useful for design optimization, manufacturing processes, and for monitoring the health integrity of WTBs. This paper focuses on the sensitivity analysis of the effects of the delamination degree of fiberglass-reinforced polymer composites in the structure of wind turbine blades. Using finite element analysis, the composite was modeled as a laminated structure with five plies (0/45/90/45/0) and investigated regarding the stress states around the damaged areas. Thus, the normal and shear stresses corresponding to each element of delaminated areas were extracted from each ply of the composites. It was observed that the maximum values of normal and shear stresses occurred in relation to the orientation of the composite layer. Tensile stresses were developed along the WTB with maximum values in the upper and lower plies (Ply 1 and Ply 5), while the maximum tensile stresses were reached in the perpendicular direction (on the thickness of the composite), in the median area of the thickness, compared to the outer layers where compression stresses were obtained. Taking into account the delamination cases, there was a sinuous-type fluctuation of the shear stress distribution in relation to the thickness of the composite and the orientation of the layer.

This article examines the influence of an induction coil position and configuration on the fluid flow and heat transfer characteristics in electromagnetic (EM) solidification processes. The mutual inductance technique was used to solve for the EM field, whereas a dual-zone model was used to describe the flow in the two-phase “mushy” region, and accounts for damping of the flow due to grain growth within the suspended particle region. Simulations were performed for a A319 aluminum alloy within a laboratory-scale casting apparatus surrounded by a six turn coil for three configurations and three locations with respect to the melt. It was found that the coil arrangement had only a small effect on the flow structure and velocities in comparison with the coil position. The implications with regard to solidification behavior are discussed.