Keynote: CMST 2018

Molecular dynamics simulations were performed to study the ion and water distribution around a spherical charged nanoparticle (Fig.1). A soft nanoparticle model was designed using a set of hydrophobic interaction sites distributed in six concentric spherical layers. To simulate the effect of charged functionalized groups on the nanoparticle surface, a set of charged sites were distributed in the outer layer. Four charged nanoparticle models, from a surface charge value of −0.035 C m−2 to −0.28 C m−2 were studied in NaCl and CaCl2 salt solutions at 1 M and 0.1 M concentrations to evaluate the effect of the surface charge, counterion valence, and concentration of added salt. We obtain that Na+ and Ca+2 ions enter inside the soft nanoparticle. Monovalent ions are more accumulated inside the nanoparticle surface, whereas divalent ions are more accumulated just in the plane of the nanoparticle surface sites. The increasing of the salt concentration has little effect on the internalization of counterions, but significantly reduces the number of water molecules that enter inside the nanoparticle. The manner of distributing the surface charge in the nanoparticle (uniformly over all surface sites or discretely over a limited set of randomly selected sites) considerably affects the distribution of counterions in the proximities of the nanoparticle surface.rphological changes.

Accurate Detection and Quantization of Leaf- Diseases through Soft Computing

Diseases in leaves can cause the significant reduction in both quality and quantity of agricultural production. If early and accurate detection of disease/diseases in leaves can be automated, then the proper remedy can be taken timely. A simple and computationally efficient approach is presented in this paper for disease/diseases detection on leaves. Only detecting the disease is not beneficial without knowing the stage of disease thus the paper also determine the stage of disease/diseases by quantizing the affected of the leaves by using digital image processing and machine learning. Though there exists a variety of diseases on leaves, but the bacterial and fungal spots (Early Scorch, Late Scorch, and Leaf Spot) are the most prominent diseases found on leaves. Keeping this in mind the paper deals with the detection of Bacterial Blight and Fungal Spot both at an early stage (Early Scorch) and late stage (Late Scorch) on the variety of leaves. The proposed approach is divided into two phases, in the first phase, it identifies one or more disease/diseases existing on leaves. In the second phase, amount of area affected by the disease/diseases is calculated. The experimental results obtained showed 97% accuracy using the proposed approach.

Application of GIS, Hydraulic and Hydrologic Modelling to Investigate the Changes of Flood Inundation Characteristics due to the Construction of Dams for different scenarios

The novelty of the research project reported in this paper is the coupling of hydrological and hydraulic modeling which are based on the first principal of fluid mechanics for the simulation of flash floods at Wadi Elarish watershed to optimize the a new location of another dam rather than Elrawfa dam which already exist. Results show that, the optimum scenario is obtained by the construction of the west dam. As a direct result of this dam, the downstream inundated area can be reduced up to 15.7 % as function of reservoir available storage behind the dam. Furthermore, calculations showed that the reduction rate of inundated area for 50-year floods is largely more than 100-year floods, implies the high ability of west dam on flood control especially for floods with shorter return period.

Influence of Angle of Inclination of the Crucible on Puddle Formation and Ribbon Thickness during Planar Flow Melt Spinning Process

Planar flow melt spinning process is widely used to manufacture amorphous ribbons for transformer core applications. The position of the crucible above cooling wheel for melt ejection in the realistic production conditions is crucial to producing the higher quality product. The quality of the product depends on the thickness and defect-free state of the ribbon. Puddle formation plays a significant role in the quality of the ribbon. As the experimental investigation is expensive and time consuming a numerical model is used to investigate the effect of clockwise and counter-clockwise inclination of the crucible on puddle formation and ribbon thickness. The thickness increases by 62.8 % and 111.5% with an augment in inclination angle from 0o to 5.4o in counter-clockwise and clockwise directions respectively. Limiting angle of inclination to avoid non-contact zone or cavity in the puddle at the nozzle wall is around 2o to 3o to obtain a higher quality ribbon. This limit can increase up to 3o to 4o for higher wheel speeds. The ideal position of the crucible is perpendicular to the wheel surface. Otherwise, the limiting angle of inclination to produce higher quality ribbon is, counter-clockwise with an optimum inclination of not more than 2 degrees.

Thermomagnetic Properties and Magnetocaloric Effect of R2Fe17C (R=Dy, Nd, Tb, Gd, Pr, Ho, Er) Compounds

We present a mean-field analysis, using the two-sublattice model, for the thermomagnetic and magnetocaloric properties of the R2Fe17C compounds, where R=Dy, Nd, Tb, Gd, Pr, Ho, Er and C is carbon. The dependence of magnetization, magnetic heat capacity, magnetic entropy and isothermal entropy change ∆Sm, are calculated for magnetic fields up to 5T and for temperatures up to 700 K . Direct magnetocaloric effect is present for all compounds with maximum ∆Sm between 6.13-10.95 J/K. mole for an applied field change of 5T. It is found that Pr2Fe17C compound has the highest ∆Sm of 10.95 J/K. mole at ∆H=5T and Tc=375 K. The inverse MCE is found in ferrimagnetic compounds, e.g. Gd2Fe17C, with ∆Sm= J/K mol at critical temperature Tc=623K and ∆Sm= J/K mol at Neel temperature TN=136 K. The calculated Arrott plots confirmed that the magnetic phase transitions in these compounds are of second order. The mean-field model proves its suitability for calculating the properties of the compounds under study.

Energy damping estimation in automotive magneto-rheological elastomers through finite element method

Magneto-rheological elastomers (MRE), which undergo upon the smart materials, are one of the very common products frequently used in modern vehicle production nowadays. For their visco-hyper properties, elastomers find a prevalent use as an energy absorber. Inducing a magnetic field would make their energy absorbing characteristics vary upon the desired ones by adjusting the applied potential field. A precise calculation of the amount of their absorption with respect to the potential field has a key role in the prediction of MREs’ responses. Therefore, in this study, a hyper-visco-magnetic constitutive model is utilized in COMSOL commercial software for the energy damping estimation in magneto-rheological elastomers. A representative volume element has been considered for the calculation of hysteresis loop areas as a characteristic of energy damping behaviour in MREs. Finally, the effects of magnetic flux intensity and mechanical load frequency in the energy damping behaviour of automotive magneto-rheological elastomers are evaluated.

Modelling of Aggregation of Nanoparticles and its effect on their Structural and Biological Functions

Nanoparticles have applications such as drug delivery and cancer treatments, reinforcement of the polymer or metal matrix, consumer products and environment. This work concentrates on how aggregated nanoparticles might realistically effect performance of the intended structural or biological function. As a conceptual basis, primary aggregation is assumed to produce the backbone of micro-structures which then cluster, covering a large portion of the material. This process is assumed to be chaotic and to occur rapidly. Molecular dynamic analysis of this aggregated model is difficult because the problem is not clearly bound and regions not spatially defined. Moreover the modulus of the micron-sized aggregate within the cluster is also difficult to measure directly. Instead an indirect method is developed of the polymer/particle interface in the aggregate which can be verified by bulk modulus experiments on nano-composite samples produced specifically for this work. A computer program equates minimum free-energy of the absorbed polymer molecule to dipolar interaction energies having a Boltzmann’s Distribution. Fractal numbers are used to characterise the molecular/particle interface and configuration of the aggregate backbone. After the principle has been established it is extended to other applications for example how aggregation might effect the probability of release of artificial DNA from silica nano-particles within the body

Modelling of Aggregation of Nanoparticles and its effect on their Structural and Biological Functions

Nanoparticles have applications such as drug delivery and cancer treatments, reinforcement of the polymer or metal matrix, consumer products and environment. This work concentrates on how aggregated nanoparticles might realistically effect performance of the intended structural or biological function. As a conceptual basis, primary aggregation is assumed to produce the backbone of micro-structures which then cluster, covering a large portion of the material. This process is assumed to be chaotic and to occur rapidly. Molecular dynamic analysis of this aggregated model is difficult because the problem is not clearly bound and regions not spatially defined. Moreover the modulus of the micron-sized aggregate within the cluster is also difficult to measure directly. Instead an indirect method is developed of the polymer/particle interface in the aggregate which can be verified by bulk modulus experiments on nano-composite samples produced specifically for this work. A computer program equates minimum free-energy of the absorbed polymer molecule to dipolar interaction energies having a Boltzmann’s Distribution. Fractal numbers are used to characterise the molecular/particle interface and configuration of the aggregate backbone. After the principle has been established it is extended to other applications for example how aggregation might effect the probability of release of artificial DNA from silica nano-particles within the body

A novel cohesive zone model to simulate ductile adhesives in automotive structure metallic joints

In recent years, increasing utilize of the adhesively bonded joints due to its prominent features in distribution of the stress in bonded area and bonding dissimilar material has led to developing its computational aspects to provide more reliable response. In this regard, cohesive zone model (CZM) as an effective method to simulate bondline is introduced. The crucial aspect of this method is the determination of the relation between traction and separation in fracture process zone (FPZ). In fact, the traction-separation law (TSL) is a material model which must be properly obtained and applied to the adhesive bondline. According to the literature, mechanical response of the adhesive joints in most cases (especially in ductile and semi-brittle adhesives) is depended on the TSL curve shape. In this study, a novel CZM is developed to simulate double cantilever beam (DCB) adhesive joint. The main advantageous this new model is considering non-linear behavior of ductile adhesives in elastic region. DCB coupons fabricated by means of Al 6061 adherends and Araldite 2015 adhesive. After direct extraction of the TSL and obtaining cohesive parameters of the new model, numerical simulation of the DCB is conducted. Finally, sensitivity analysis of cohesive parameters and effect of initial crack length on the DCB response is investigated.

Thermomagnetic Properties and Magnetocaloric Effect of R2Fe17C (R=Dy, Nd, Tb, Gd, Pr, Ho, Er) Compounds

We present a mean-field analysis, using the two-sublattice model, for the thermomagnetic and magnetocaloric properties of the R2Fe17C compounds, where R=Dy, Nd, Tb, Gd, Pr, Ho, Er and C is carbon. The dependence of magnetization, magnetic heat capacity, magnetic entropy and isothermal entropy change ∆Sm, are calculated for magnetic fields up to 5T and for temperatures up to 700 K . Direct magnetocaloric effect is present for all compounds with maximum ∆Sm between 6.13-10.95 J/K. mole for an applied field change of 5T. It is found that Pr2Fe17C compound has the highest ∆Sm of 10.95 J/K. mole at ∆H=5T and Tc=375 K. The inverse MCE is found in ferrimagnetic compounds, e.g. Gd2Fe17C, with ∆Sm= J/K mol at critical temperature Tc=623K and ∆Sm= J/K mol at Neel temperature TN=136 K. The calculated Arrott plots confirmed that the magnetic phase transitions in these compounds are of second order. The mean-field model proves its suitability for calculating the properties of the compounds under study.