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The available potential plant waste could be worthy material to strengthen polymers to make sustainable products and structural components. Therefore, modeling the natural fiber polymeric-based composites is currently required to reveal the mechanical performance of such polymeric green composites for various green products. This work numerically investigates the effect of various fiber types, fiber loading, and reinforcement conditions with different polymer matrices towards predicting the mechanical performance of such natural fiber composites. Cantilever beam and compression schemes were considered as two different mechanical loading conditions for structural applications of such composite materials. Finite element analysis was conducted to modeling the natural fiber composite materials. The interaction between the fibers and the matrices was considered as an interfacial friction force and was determined from experimental work by the pull out technique for each polymer and fiber type. Both polypropylene and polyethylene were considered as composite matrices. Olive and lemon leaf fibers were considered as reinforcements. Results have revealed that the deflection resistance of the natural fiber composites in cantilever beam was enhanced for several reinforcement conditions. The fiber reinforcement was capable of enhancing the mechanical performance of the polymers and was the best in case of 20 wt.% polypropylene/lemon composites due to better stress transfer within the composite. However, the 40 wt.% case was the worst in enhancing the mechanical performance in both cantilever beam and compression cases. The 30 wt.% of polyethylene/olive fiber was the best in reducing the deflection of the cantilever beam case. The prediction of mechanical performance of natural fiber composites via proper numerical analysis would enhance the process of selecting the appropriate polymer and fiber types. It can contribute finding the proper reinforcement conditions to enhance the mechanical performance of the natural fiber composites to expand their reliable implementations in more industrial applications.

The calculation of the coefficients of magneto-optical absorption in semiconductors at different temperatures and pressures is carried out. A formula for the temperature dependence of the oscillations of the combined density of states by the Kane dispersion law is obtained. Mathematical modeling has been carried out that determines the magneto-optical absorption coefficient in semiconductors in the presence of external influences. A new method for determining the magneto-optical absorption coefficient in semiconductors in the presence of pressure and temperature is proposed. The correspondence of simulation results with experimental data is shown.

A critical review of the current state of the art of the computing practices adopted by the earthquake engineering community is presented. Advanced computational tools are necessary for estimating the demand on seismically excited structures. Such computational methodologies can provide valuable information on a number of engineering parameters which have been proven essential for earthquake the engineering practice. The discussion extends from the finite element modeling of earthquake-resistant structures and the analysis procedures currently used to future developments considering the calculation of uncertainty and methodologies which rely on sophisticated computational methods. The objective is to provide a common ground of collaboration between the earthquake engineering and computational mechanics communities in an effort to mitigate future earthquake losses.

In this paper we present the first results of beach profile hindcasting with XBeach using recently measured coastal data acquired under storm conditions at eight European sites, including a comparison to model results obtained with off-the-shelf models. The results show consistently that the XBeach has skill in predicting the coastal profile, albeit that in most cases the erosion around the mean water line is overpredicted and the depositions at the lower beach face are overpredicted. The causes for this model effect are under active investigation but not resolved yet. Likely candidates are the modeling of onshore (asymmetry) transports which reduces the offshore transports due to undertow (currents) or the modeling of sediment motion in the swash zone.

Permeability is an important hydraulic parameter for characterizing heat and mass transfer properties of fibrous porous media. However, it is difficult to be quantitatively predicted due to the complex and irregular pore structure of fibrous porous media. Fractal geometry has been verified to be an effective method for determining the permeability of fibrous porous media. In this study, recent works on the permeability of fibrous porous media by means of fractal geometry are reviewed, the advances for each presented fractal model are analyzed and summarized, parameter equations used in available fractal permeability models are also briefly compared and reviewed. Future work for more generalized permeability model of fibrous porous media need to conducted by considering the special characters of fibrous materials, uniform pore structure parameter model and the influence factor of capillary pressure, electrokinetic phenomena, etc.

The field of multimedia software engineering is still in an inmature state. Significant research and development has been dedicated towards multimedia services and systems technology such as networking or database systems. Multimedia document formats have been standardized. But when it comes to multimedia application development, the development process is truncated to an implement-and-test method. Either specialized multimedia authoring systems or multimedia frameworks or libraries complementing programming languages or system software are directly used for implementation. No preceding modeling phases for requirements specification, analysis, or design of the system to build are enforced. The development of sophisticated multimedia process models and established, usable graphical notations tailored to the specification of multimedia systems is still underway.

In order to fill this gap, it is the purpose of this chapter to show current achievements in object-oriented modeling of multimedia applications. Based on an analysis of the state of the art in multimedia application development, we shortly present approaches to object-oriented hypermedia modeling and extensions of the Unified Modeling Language (UML) for hypermedia and interactive systems. The main part of the chapter is dedicated towards a recent approach to the Object-oriented Modeling of MultiMedia Applications (OMMMA).

The force from a tsunami will damage buildings, such as houses, bridges, and many other coastal infrastructures. The impact and drag force of a tsunami depend on the scale and the characteristics of the tsunami as well as the infrastructures' characteristics.

This study was conducted using physical modeling to determine the effect of openings and protection on buildings to reduce the effects of a tsunami attack. The openings were symmetrical about the front and rear walls and were oriented in the direction of the tsunami. Barriers with dimensions that were the same width and three times higher than the building and of various lengths were used to simulate protection against a tsunami.

The results indicated that the force on the buildings depends on but is not linearly correlated to the opening. The barrier upstream of the building significantly reduced the force depending on its distance to the building and the surge Froude number; however, the openings still play an important role in reducing the force on a protected building. Simple equations for practical use are proposed to calculate the tsunami force on a building with openings with or without protection.

Optical problems, related to the particle on the surface, i.e. optical resonance and near-field effects in laser cleaning are discussed. It is shown that the small transparent particle with size by the order of the wavelength may work as a lens in the near-field region. This permits to focus laser radiation into the area with the sizes, smaller than the radiation wavelength. It leads to 3D effects in surface heating and thermal deformation, which influences the mechanisms of the particle removal.

In this work, a new model has been developed for calculating the effect of a quantizing magnetic field on the temperature dependence of the two-dimensional combined density of states in direct-gap heterostructures with quantum wells. The temperature dependence of the oscillations of the two-dimensional combined density of states of the quantum well is explained by the thermal smearing of the Gaussian distribution function in a strong magnetic field. Based on the proposed new models, the Landau levels of charge carriers in a direct-gap quantum well are determined in a wide temperature range. The experimental results were interpreted using the oscillations of the combined density of states of the quantum well in a quantizing magnetic field.

This paper aims to develop a predictive model and optimize the performance of the abrasive water jet machining (AWJM) during machining of carbon fiber-reinforced plastic (CFRP) epoxy laminates composite through a unique approach of artificial neural network (ANN) linked with the nondominated sorting genetic algorithm-II (NSGA-II). Initially, 80 AWJM experimental runs were carried out to generate the data set to train and test the ANN model. During the experimentation, the stand-off distance (SOD), water pressure, traverse speed and abrasive mass flow rate (AMFR) were selected as input AWJM variables and the average surface roughness and kerf width were considered as response variables. The established ANN model predicted the response variable with mean square error of 0.0027. Finally, the ANN coupled NSGA-II algorithm was applied to determine the optimum AWJM input parameters combinations based on multiple objectives.

A model for nanosecond dry laser cleaning that treats the substrate and particle expansion on a unified basis is proposed. Formulas for the time-dependent thermal expansion of the substrate, valid for temperature-dependent parameters, are derived. Van der Waals adhesion, substrate and particle elasticity, and particle inertia are taken into account for an arbitrary temporal profile of the laser pulse. The characteristic time for the particle on the surface system is deduced. This time is related to the size of the particles as well as the adhesion and elastic constants. Cleaning proceeds in different regimes if die duration of the laser pulse is much shorter or longer than this time. Expressions for cleaning thresholds are provided and compared with experiments on the 248 nm KrF excimer-laser cleaning of Si surfaces from spherical SiO₂ particles with radii between 235 and 2585 nm in vacuum. Discrepancies between the experimental data and theoretical results seem to indicate that nanosecond dry laser cleaning cannot be explained purely on the basis of one-dimensional tiiermal expansion mechanism.

Nonlinear dynamics of a real plane and periodically forced triple pendulum is investigated experimentally and numerically. Mathematical modeling includes details, taking into account some characteristic features (for example, real characteristics of joints built by the use of roller bearings) as well as some imperfections (asymmetry of the forcing) of the real system. Parameters of the model are obtained by a combination of the estimation from experimental data and direct measurements of the system's geometric and physical parameters. A few versions of the model of resistance in the joints are tested in the identification process. Good agreement between both numerical simulation results and experimental measurements have been obtained and presented. Some novel features of our real system chaotic dynamics have also been reported, and a novel approach of the rolling bearings friction modeling is proposed, among other.

A study of a DC–DC boost converter fed by a photovoltaic (PV) generator and supplying a constant voltage load is presented. The input port of the converter is controlled using fixed frequency pulse width modulation (PWM) based on the loss-free resistor (LFR) concept whose parameter is selected with the aim to force the PV generator to work at its maximum power point. Under this control strategy, it is shown that the system can exhibit complex nonlinear behaviors for certain ranges of parameter values. First, using the nonlinear models of the converter and the PV source, the dynamics of the system are explored in terms of some of its parameters such as the proportional gain of the controller and the output DC bus voltage. To present a comprehensive approach to the overall system behavior under parameter changes, a series of bifurcation diagrams are computed from the circuit-level switched model and from a simplified model both implemented in PSIM^© software showing a remarkable agreement. These diagrams show that the first instability that takes place in the system period-1 orbit when a primary parameter is varied is a smooth period-doubling bifurcation and that the nonlinearity of the PV generator is irrelevant for predicting this phenomenon. Different bifurcation scenarios can take place for the resulting period-2 subharmonic regime depending on a secondary bifurcation parameter. The boundary between the desired period-1 orbit and subharmonic oscillation resulting from period-doubling in the parameter space is obtained by calculating the eigenvalues of the monodromy matrix of the simplified model. The results from this model have been validated with time-domain numerical simulation using the circuit-level switched model and also experimentally from a laboratory prototype. This study can help in selecting the parameter values of the circuit in order to delimit the region of period-1 operation of the converter which is of practical interest in PV systems.

In the recent decades, the increasing energy demands and its applications have seen the focus shifting to the hybrid nanofluid flows but so much is still left to be investigated. This analysis is executed to explore the hydro-magnetic flow to investigate the incompressible flow and heat transfer towards a stretching surface with velocity and thermal slips. The scaling similarity transformations are created using Lie group analysis and employing these to convert nonlinear partial differential equations to the nonlinear ordinary differential equations. Here, after converting equations from dimensional to non-dimensional, we will use the BVP4C solver (MATLAB) for plotting the graphs to analyze how distinct non-dimensional parameters affect the skin friction and Nusselt number transfer rate, case 1 graphene + CNT + aluminum oxide with base fluid as water and case 2 magnesium oxide + zirconium oxide + copper oxide with water as base fluid, here taking nanoparticles without different shapes. The hybrid nanofluid temperature profile has mixed behavior, and the velocity profile increases when M rises. The hybrid nanofluid temperature profile curvature has composite behavior when $Pr$ rises. The link between several independent or predictor variables and one dependent or criterion variable has been examined using multilinear regression analysis (MLR). When coefficient values for many variables are subject to change, it can forecast a wide range of outcomes.

A Learning Software Organization (LSO) is an organization that learns within the domain of software development, evolution and application. In the context of LSO, knowledge management and learning approaches are complementary views on knowledge handling processes. Learning is based on knowledge and experiences related to the different processes, products, tools, techniques and methods applied to the software development process. The overall objective of an LSO is to improve software processes and products according to the strategic goals of the organization.

Knowledge is considered a crucial resource of each organization and, therefore, needs to be managed carefully. The knowledge management literature usually deals with the mechanisms of knowledge handling, while learning approaches address the process how to gain knowledge. This can be done on an individual, group, or organizational level. Learning extends knowledge and enables decision making for individuals as well as for groups and entire organizations. LSO can only be understood from the interplay between its organizational, content, technology, and methodology dimension.

In this chapter, KM as a prerequisite for organizational learning is described. The basic terminology and core principles of an LSO are characterized in the same way as its enabling techniques: experimentation, modeling, measurement, reuse and collaborative learning.

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.

Translating university technology via the university–industry route faces an array of challenges. Subsequently, understanding the interrelationships of these challenges hopes to provide a better outlook on the complex nature of the university technology transfer (UTT) process. Such an agenda remains a gap in the domain literature. To advance this oversight, this study intends to identify the UTT challenges and determine their complex contextual relationships. The interpretative structural modeling, together with the MICMAC analysis, was sequentially adopted to derive the overarching structure of the challenges of UTT. A case study in a public university in the Philippines was conducted to carry out these objectives. Findings show that time constraints, knowledge being too theoretical, high costs of managing joint research projects, complex organizational structure, institutional bureaucracy, geographic distance, and lack of national benchmark are driving challenges that influence other challenges in impeding UTT in the representative Philippine university. These findings provide policy insights to key decision-makers and stakeholders on the success of technology transfers.

Interval-valued time series (ITS) are interval-valued data that are collected in chronological order. The modeling of ITS is an ongoing issue in domain of time series analysis. This paper presents a new modeling method of ITS based on the synergy of fuzzy set theory and artificial neural networks. The proposed method involves the construction of collection of fuzzy sets describing characteristics of amplitude of ITS, the expression and reconstruction mechanism of ITS and the emergence of model of ITS based on artificial neural network (ANN). The resulting model of ITS not only supports the linguistic output but also the numeric output in interval format. A series of experimental studies is reported for two publicly available financial datasets showing different dynamic characteristics. Experimental results clearly show that the constructed ITS model has the better performance on the linguistic and numeric level.

Sintering of binder jet 3D printed (BJ3DP) parts results in significant nonlinear distortion with typical shrinkage value of 5–20%, which makes design for BJ3DP and post-machining difficult. In this work, a computational modeling framework with calibration and validation procedure is developed to simulate distortion during sintering of BJ3DP parts accurately for the first time. The computational model employs the finite element analysis with a viscoplastic constitutive model that accounts for effects of gravity and friction. A calibration procedure is proposed to obtain values of different model parameters systematically through dilatometric, gravity bending, and grain growth experiments. For model validation, four bridges with different spans and a second part with a circular hole and two free overhangs are designed. The calibration procedure is applied to develop a computational model for sintered 316L stainless steel BJ3DP parts. The displacements at various locations on the sintered parts are simulated using the calibrated model and are found to have errors less than 3.5% compared to those obtained by experiment.

Because sociology is seeking mechanisms for explaining social phenomena, we discuss in this paper whether and how the metaphor of a chemical reaction network can be employed as a formal mechanism to describe social and political systems. A reaction network is a quite general concept that allows one to model a variety of dynamical systems. Furthermore, a set of powerful tools can infer potential dynamical properties from the network structure. Using a toy model of the political system inspired by Luhmann, we demonstrate how chemical organization theory can be applied and can give insight into the structure and dynamics of the resulting model. We show how chemical organization theory allows one to identify an overlapping hierarchy of important subsystems in these networks. Simulations reveal how this hierarchy constrains the potential dynamical behavior of the model.