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This paper concerns the modeling of smart health sensors for data monitoring, where the data are eventually noisy, with correlated noise. In this work, we applied Clifford-based wavelets/multiwavelets for correlated noise in multi-sensors health data monitoring by estimating the set of sensor nodes minimizing an eventual error computed by the signal values at the selected nodes mostly caused by the correlated noise. Instead of directly minimizing the estimation error, we focused on evaluating a multi-level scheme based on multiwavelets for the estimation of the error between the parameter vector and its sub-vector of those nodes. Numerical simulations are provided with a comparison to some recent existing works. This model showed a performance and a fast time execution compared to those existing works. This model exceeds these models by the non-necessity to assume a priory structure of the data. Wavelets are capable to detect, localize, and eliminate the noise, even correlated, efficiently via the independent uncorrelated multiwavelets’ components.

Prevotella copri is a prominent constituent of the human gastrointestinal microbiome, and its fluctuating abundance has been linked with positive and negative influences on diseases such as Parkinson’s disease and rheumatoid arthritis. Prevotella copri demonstrates flexibility against drugs. There is presently no vaccine approved by the FDA against prevotella copri,and treatment options are restricted. Hence, this research work was designed to create an in silico-based vaccine for prevotella copri.The protein sequences of two distinct strains ofprevotella copriwere retrieved from NCBI. The T-cell and B-cell epitopes were obtained and then analyzed for antigenicity, allergenicity, docking and simulation. The peptide comprises linear B-cell and T-cell epitopes from proteins identified as potential novel vaccine candidates. The molecular dynamics (MD) simulations and protein-protein docking results revealed that the vaccine exhibits strong and Sustained interaction with Toll-like receptor 4 (TLR4). The constructed sequence was integrated into the pET-30a (+) biological vehicle (vector) for subsequent analysis expression in E. coli through the SnapGene server. The constructed multi-epitopic vaccine candidate was assessed for its structural, physicochemical and immunological properties. The results demonstrated solubility, stability, antigenicity and nonallergenicity and showed a strong affinity for its target receptors. The in silico study represents a significant step forward in designing a vaccine that could effectively eliminate Prevotella copri globally.

The statistical modeling was used in the analysis of structures containing heterogeneous masses. The statistical probability of a system of coupled oscillators was found taking into account the mass dependence of energy levels. It is essentially a new approach. Both the low as well as high temperature expressions for diffusion coefficient were found. Comparison with experimental data gave satisfactory agreement.

The success of modern electronics is built on the possibility to accurately predict system behavior by using simulation tools. This paradigm can be extended to components such as piezoelectric transducers attached to the electronics. The ability to simulate both piezoelectric transducer and electronics together renders possible effective optimizations at system level, i.e. minimizing size, cost and power consumption. In this paper a computer simulation of a combined electronics and piezoelectric transducer system is explored. The analogy between acoustic wave propagation and wave propagation in an electric transmission line is given. The simulation approach is applied to a pulser-receiver setup for the determination of speed of sound and attenuation in liquids. Experiments and simulations are made for fixed temperature and in the frequency range 1–10 MHz using ethanol, methanol, carbon tetrachloride, acetone, benzene and distilled water as test samples. Comparison shows a good agreement between simulation and experiments. Furthermore, the use of an ultrasonic simulation package allows for the development of the associated electronics to amplify and process the received ultrasonic signals.

The emphasis on structural design of miniaturized machine tool (mMT) used in micro-machining process is different from that of conventional machine tool due to requirement of higher precision and stable performance. In this paper, structural modeling and simulation of 3-axis vertical micro-end-milling system is presented. Based on different components combination, three models of linear multi-degree-of-freedom vertical milling systems are constructed theoretically using high precision stages. The most suitable model is chosen by volumetric error calculation. Finite element method (FEM) is used for simulation of those numerical solid models. Static and dynamic analysis with different joint stiffness and loads is simulated by ANSYS. Prototype model is assembled according to the selected structure. Finally, surface roughness of the bottom of micro slots, which are machined by prototype model, is analyzed to verify the performance of mMT.

This paper is to understand and model the thermomechanical response of the rotary forged WHA, uniaxial compression and tension tests are performed on cylindrical samples, using a material testing machines and the split Hopkinson bar technique. True strains exceeding 40% are achieved in these tests over the range of strain rates from 0.001/s to about 7,000/s, and at initial temperatures from 77K to 1,073K. The results show: 1) the WHA displays a pronounced changing orientation due to mechanical processing, that is, the material is inhomogeneous along the section; 2) the dynamic strain aging occurs at temperatures over 700K and in a strain rate of 10^-3 1/s; 3) failure strains decrease with increasing strain rate under uniaxial tension, it is about 1.2% at a strain rate of 1,000 1/s; and 4) flow stress of WHA strongly depends on temperatures and strain rates. Finally, based on the mechanism of dislocation motion, the parameters of a physically-based model are estimated by the experimental results. A good agreement between the modeling prediction and experiments was obtained.

Silicon nitride bonded silicon carbide (Si₃N₄-SiC) refractories are commonly used as the sidewall of aluminum electrolysis cells. They have to withstand an extremely corrosive molten electrolyte bath for long periods. The sidewall is normally protected with a layer of solidified electrolyte (called frozen ledge), which is sensitive to the thermal conductivity of the sidewall. In this work, through review of the literature on modeling methods for predicting the effective thermal conductivity of dense composites and porous materials, some selected methods were applied to calculate the effective thermal conductivity of Si₃N₄-SiC refractories. The model predictions were compared with the thermal conductivity of a commercial Si₃N₄-SiC refractory measured by using laser flash technique. The present study showed that, due to multi-phase nature and complex microstructure of Si₃N₄-SiC refractories, most of the selected modeling methods individually do not give satisfactory predictions in one step. Recursive applications of one method or combinations of different methods are capable of giving satisfactory predictions.

An analytical model based on Eshelby equivalent inclusion approach and Mori-Tanaka mean field extension was established by introducing numerical matrix and composite secant/tangent moduli to simulate the stress-strain curve of particulate reinforced composite. The same modeling work was also carried out by FEM analysis based on the unit cell model using a commercial ANSYS code. The modeling results by both models on evolution of the load carried by the SiC particles during straining provide strong evidences to back up the strengthening mechanism of the load sharing. The modeling was also carried out to study the influence of different volume fractions and aspect ratios on elastic modulus and yield strength of the composites with different reinforcing particles to get a better understanding of strengthening mechanisms of the materials. A concept of microstructure design for particulate reinforced materials was argued based on new developments in understanding of the relationship between properties and microstructure. The optimal geometry of particulate reinforcement was discussed in respect to the best match up with matrix mechanical behavior.

A hot spot model, involving interaction of pulse laser with nanoparticles where heat diffusion and exothermic chemical reaction are considered and spread out of heat and chemical reaction, is developed to model the thermal reaction dynamic process of Al/NC (nitrocellulose) nanothermites excited by pulse laser for the purpose of verifying the experimental ablation criterion proposed recently and providing a microscopic insight into different physical pathways leading to ablation. In this model, the spatial position and conversion of matters taking place in chemical reactions are regarded as the functions of time, space, and temperature. An exact expression of power density absorbed by nanoparticles in matrix is incorporated to calculate the diameters of chemical reaction region. Calculation results justify experimental ablation criterion, and show that thermal decomposition mechanism predominates the nanosecond pulse-excited process before ablation but it is not suitable for the 100 ps regime which is qualitatively attributed to shock pressure. The effects of pulse duration and nanoparticle size on ablation threshold are examined.

The electrical conductivity of solid oxide fuel cell (SOFC) cathode is one of the most important indices affecting the efficiency of SOFC. In order to improve the performance of fuel cell system, it is advantageous to have accurate model with which one can predict the electrical conductivity. In this paper, a model utilizing support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter optimization was established to modeling and predicting the electrical conductivity of Ba_0.5Sr_0.5Co_0.8Fe_0.2 O_3-δ-xSm_0.5Sr_0.5CoO_3-δ (BSCF–xSSC) composite cathode under two influence factors, including operating temperature (T) and SSC content (x) in BSCF–xSSC composite cathode. The leave-one-out cross validation (LOOCV) test result by SVR strongly supports that the generalization ability of SVR model is high enough. The absolute percentage error (APE) of 27 samples does not exceed 0.05%. The mean absolute percentage error (MAPE) of all 30 samples is only 0.09% and the correlation coefficient (R²) as high as 0.999. This investigation suggests that the hybrid PSO–SVR approach may be not only a promising and practical methodology to simulate the properties of fuel cell system, but also a powerful tool to be used for optimal designing or controlling the operating process of a SOFC system.

The forming process before resistive switching in Cu/ SiO₂/Pt memory devices, corresponding to the formation of conducting path, can be regarded as the dielectric soft breakdown. Based on the analysis of breakdown mechanism, a dynamic model combining the transition of Cu ions with the space-charge effect has been proposed, and demonstrates that the forming voltage depends on the thickness of oxide, the sweep rate of voltage and temperature. The predictions of the model are consistent with the experiment data reported in the literature and it is believed that the transition of Cu ions across the oxide and the accumulation of Cu ions at the SiO₂/Pt interface could be responsible for the conductive path formation in Cu/SiO₂/Pt memory devices.

Following recent rapid development of researches in utilizing Magnetorheological (MR) fluid, a smart material that can be magnetically controlled to change its apparent viscosity instantaneously, a lot of applications have been established to exploit the benefits and advantages of using the MR fluid. One of the most important applications for MR fluid in devices is the MR valve, where it uses the popular flow or valve mode among the available working modes for MR fluid. As such, MR valve is widely applied in a lot of hydraulic actuation and vibration reduction devices, among them are dampers, actuators and shock absorbers. This paper presents a review on MR valve, discusses on several design configurations and the mathematical modeling for the MR valve. Therefore, this review paper classifies the MR valve based on the coil configuration and geometrical arrangement of the valve, and focusing on four different mathematical models for MR valve: Bingham plastic, Herschel–Bulkley, bi-viscous and Herschel–Bulkley with pre-yield viscosity (HBPV) models for calculating yield stress and pressure drop in the MR valve. Design challenges and opportunities for application of MR fluid and MR valve are also highlighted in this review. Hopefully, this review paper can provide basic knowledge on design and modeling of MR valve, complementing other reviews on MR fluid, its applications and technologies.

The coating deformation behavior and stress evolution of the plasma sprayed Cr₃C₂–NiCr coating during nanoindentation process were analyzed by finite element modeling based on its real elastic-plastic properties. The effects of indentation depth and the coating thickness on the mechanical response of the coating were studied. The results show that once the indentation depth exceeded 13% of the coating thickness, the coating material near the indenter was extruded and piled up on the top surface. Meanwhile, high equivalent stress was developed along the coating-substrate interface rather than inside the coating. Even when the indentation depth was smaller than 13% of the coating thickness, the substrate still influences the mechanical behavior of the coating, inducing different reaction force to the indenter.

Nanostructured copper hydroxyl salts have raised researchers’ attention due to its potential application in photocatalysis. In this paper, copper hydroxyl sulfates were synthesized by titrating NaOH solution to CuSO₄ solution with the suggested pH from modeling software Visual MINTEQ. Brochantite nanostructures was produced at the end point pH 5 and 6, meanwhile the mixture of brochantite and posnjakite was obtained at pH 10. These results show the usability of Visual MINTEQ in determining the operating parameter (pH) range for the particular crystal synthetizations. In addition, these crystals show a good visible light absorption, which extends its function to wider applications.

Investigation on (2-dimensional) (2D) materials is growing significantly due to the fundamental electronic properties in the direct inherent bandgap, higher carrier mobility, and easier exfoliation. Phosphorene as a new 2D configuration has presented excellent potential in electronic and optoelectronic applications. In this study, the conductivity of monolayer phosphorene and Einstein’s relations as fundamental parameters in semiconductor manufacturing are analytically modeled. In addition, dependency of conductivity on normalized Fermi energy ($\eta$) is demonstrated. According to the simulation results, conductivity and Einstein’s relation are completely dependent on temperature, therefore, rising up the temperature leads to conductivity and diffusion coefficient (Dn) growth. Indeed, conductivity is saturated when the normalized Fermi energy exceeds than 6. Also, the conductivity and Einstein’s relation dependency to voltage are studied. Results show that carrier conductivity and the electron diffusion coefficient (Dn) increase by amplifying the voltage.

An Eshelby particle-compounded model was employed to investigate the stress distribution in the SiCp/Fe composites during straining in order to predict the stress-strain curves of the composites. Effect of the SiC volume content and aspect ratios on yield strength of the SiCp/Fe composites was studied by the simulation. The modeling results indicate that the stress in the iron matrix is much smaller than that in SiC particles as straining the composites, which means the strengthening mechanisms of the SiCp/Fe composites is determined by the load transfer mechanisms. The aspect ratios of the particles play a significant role in yield strength of the SiCp/Fe composites especially as the particle volume content is large. The stress in SiC particles has a stronger dependence on the aspect ratios of the particles only if the reinforcement volume content is small.

For reinforcement, the photochromic field and the cooperation between the theoretical and experimental branches of physics, the computational, theoretical artificial neural networks (CTANNs) and the resilient back propagation (R${}_{\mathrm{\text{prop}}}$) training algorithm were used to model optical characterizations of casting (Admantan-Fulgide) thin films with different concentrations. The simulated values of ANN are in good agreement with the experimental data. The model was also used to predict values, which were not included in the training. The high precision of the model has been constructed. Moreover, the concentration dependence of both the energy gaps and Urbach’s tail were, also tested. The capability of the technique to simulate the experimental information with best accuracy and the foretelling of some concentrations which is not involved in the experimental data recommends it to dominate the modeling technique in casting (Admantan-Fulgide) thin films.

Predicting the quality of the machined components is the grandiose signification in industrial manufacturing. Calculation of the surface roughness is one of the most important elements to predict the quality of machined parts. In this paper, the surface roughness was modeled in the face-end mill process by using general rhombu insert. In the proposed mathematical model, with the stable milling condition, the surface roughness is formulated by a function of feed rate, and insert geometry such as nose radius and nose angle. An experimental method is proposed based on the stable milling condition to estimate the surface roughness. The developed surface roughness calculation model has been successfully verified by both simulation and experiment with very promising results. The average difference between predicted and experimental results is 7.59%. The proposed model can be applied to predict the surface roughness in face-end mill processes by using general insert at stable cutting condition.

A method has been proposed to reason the choice among the known optimized models for methods for estimating chlorophyll (Chl) concentration in the seawater according to the information-logarithmic criterion, which provides a comparison of theoretical models by the SeaWiFS data. It has been shown that the most appropriate means is to determine the Chl concentration, since the concentration of Chl in seawater is systematically investigated by marine ships or remote sensing. All optimized models of the optical properties of seawater can be verified by checking the simulated and measured Chl concentration data.

Solar cell development has been largely done by investigating how changes in the structural design of new materials will affect the cell’s performance. Although this process has been used for decades, it can sometimes be slow and expensive. Therefore, a new approach to solar cell development must be taken via simulations and modeling to enhance the cell performance. Simulations and modeling before actual fabrication have the added benefit of avoiding wastage of costly materials and time. This paper reviews the various types of solar cells and discusses the latest developments in the photovoltaic field. It also expounds how modeling solar cells before the developmental phase is beneficial with a focus on COMSOL Multiphysics describing how it is particularly advantageous.