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Incineration has become increasingly important in many large cities around the world because of fast urbanization and population growth. The benefits of energy production and large reduction in the waste volume to landfills also contribute to its growing adaptation for solid waste management for these cities. At the same time, the environmental impact of the pollutant gases emitted from the incineration process is a common concern for various stakeholders which must be properly addressed. To minimize the pollutant gas emission levels, as well as maximize the energy efficiency, it is critically important to optimize the combustion performance of an incinerator freeboard which would require the development of reliable approaches based on computational fluid dynamics (CFD) modeling. A critical task in the CFD modeling of an incinerator furnace requires the specification of waste characteristics along the moving grate as boundary conditions, which is not available in standard CFD packages at present. This study aims to address this gap by developing a numerical incinerator waste bed model.

A one-dimensional Lagrangian model for the incineration waste bed has been developed, which can be coupled to the furnace CFD model. The changes in bed mass due to drying, pyrolysis, devolatilization and char oxidation are all included in the model. The mass and concentration of gases produced in these processes through reactions are also predicted. The one-dimensional unsteady energy equations of solid and gas phases, which account for the furnace radiation, conduction, convection and heat of reactions, are solved by the control volume method.

The Lagrangian model is validated by comparing its prediction with the experimental data in the literature. The predicted waste bed height reduction, temperature profile and gas concentration are in reasonable agreement with the observations.

The simplicity and efficiency of the model makes it ideally suitable to be used for coupling with the computational furnace model to be developed in future (so as to optimize incinerator designs).

The purpose of this paper is to understand the influence of exposure to motivated offenders who may alter the vulnerability levels to phishing victimization. This is particularly focused on explaining the influences of individuals’ online lifestyles and attitudes toward information sharing online on phishing susceptibility.

This conceptual paper explores the risk of phishing victimization using criminological theories. The authors draw on empirical evidence from existing cybercrime literature and revisit routine activities theory (RAT) and lifestyle RAT (LRAT) to elucidate the risk of phishing victimization. This paper proposes that cyber-RAT, which was developed from RAT and LRAT, could interpret phishing victimization. Grounded on the intervention-based theory against cybercrime phishing, this study suggests that an attitude toward precautionary behavior (information sharing online) is essential to mitigate the phishing victimization risk.

This paper aims to provide a clear insight into the understanding of phishing victimization risk using theoretical and empirical evidence.

The theoretical perspective outlined provides the understanding of the impacts of online routine activities on a phishing attack which in turn will increase the awareness of phishing threats. The important role of the precautionary countermeasure, that is, attitudes toward information sharing online is highlighted to reconcile the phishing victimization risk.

The purpose of this paper is to make a numerical study of natural convection of water‐based nanofluids in a square cavity when a discrete heat source is embedded on the bottom wall, applying a “nanofluid‐oriented” model for the calculation of the effective thermal conductivity (Xu‐Yu‐Zou‐Xu's model) and the effective dynamic viscosity (Jang‐Lee‐Hwang‐Choi's model). Another motivation is the numerical solution of the equations of the flow with a meshless method.

A meshless point collocation method with moving least squares (MLS) approximation is used. A test validation study of the numerical method takes place for pure water flow, as well for water/Al₂O₃ nanofluids. The influence of pertinent parameters such as Rayleigh number (Ra), the non‐uniform nanoparticle size keeping the mean nanoparticle diameter fixed, the volume fraction of nanoparticles and the location of heat source on the cooling performance are studied.

The presence of a discrete heat source, as well as the various thermal boundary conditions affects the characteristics of the nanofluid flow and heat transfer. When the ratio of minimum to maximum nanoparticle diameter is increased, the local Nusselt number is increased and the heat source temperature is decreased. The increase of solid volume fraction of nanoparticles causes the heat source maximum temperature to decrease and the Nusselt Number to increase.

The present study constitutes an original contribution to the nanofluid flow and heat transfer characteristics when a discrete heat source is presence. “Nanofluid‐oriented” models are used for the calculation of the effective thermal conductivity and dynamic viscosity.

Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process.

The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods.

The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods.

The proposed framework can be used effectively for optimizing complex lattice-based structures.

An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.

Some aspects of the distinct element method (DEM) are reviewed. A model for fully grouted reinforcement subjected to axial and/or shear force(s) is proposed. The modelling of some rock mechanics problems, by incorporating the reinforcement model into the DEM is presented. A general discussion on the application of the DEM in rock mechanics, and some of the difficulties that may be encountered, based on the author's experience, are also included.

The present contribution deals with the sensitivity analysis and optimization of structures for path‐dependent structural response. Geometrically as well as materially non‐linear behavior with hardening and softening is taken into account. Prandtl‐Reuss‐plasticity is adopted so that not only the state variables but also their sensitivities are path‐dependent. Because of this the variational direct approach is preferred for the sensitivity analysis. For accuracy reasons the sensitivity analysis has to be consistent with the analysis method evaluating the structural response. The proposed sensitivity analysis as well as its application in structural optimization is demonstrated by several examples.

This paper aims to enhance the reliability of self-validating multifunctional sensors.

An effective fault detection, isolation and data recovery (FDIR) strategy by using kernel principal component analysis (KPCA) coupled with gray bootstrap and fault reconstruction methods.

The proposed FDIR strategy is able to the address fault detection, isolation and data recovery problem of self-validating multifunctional sensors efficiently.

A KPCA-based model which can overcome the limitation of existing linear-based models is used to achieve the fault detection task. By using gray bootstrap method, the position of all faulty sensitive units can be calculated even under the multiple faults situation. A reconstruction-based contribution method is adopted to evaluate the amplitudes of the fault signals, and the fault-free output of the faulty sensitive units can be used to replace the fault output.

The purpose of this study is to investigate the entropy generation in different nanofluids flow over a vertically moving rotating disk. Unlike the classical Karman flow, water-based nanofluids have various suspended nanoparticles, namely, Cu, Ag, Al₂O₃ and TiO₂, and the disk is also moving vertically with time-dependent velocity.

The Keller box technique numerically solves the governing equations after reduction by suitable similarity transformations. The shear stress and heat transport features, along with flow and temperature fields, are numerically computed for different concentrations of the nanoparticles.

This study is done comparatively in between different nanofluids and for the cases of vertical movement of the disk. It is found that heat transfer characteristics rely not only on considered nanofluid but also on disk movement. Moreover, the upward movement of the disk diminishes the heat-transfer characteristics of the fluid for considered nanoparticles. In addition, for the same group of nanoparticles, an entropy generation study is also performed, and an increasing trend is found for all nanoparticles, with alumina nanoparticles dominating the others.

This research is a novel work on a vertically moving rotating surface for the water-conveying nanoparticle fluid flow with entropy generation analysis. The results were found to be in good agreement in the case of pure fluid.

The purpose of this paper is to optimize the performance of an incinerator plant in terms of NO emissions and temperature of particles 2 s after the last air injection, which must be above 850°C as established from the Directive 2000/76/EC of the European Parliament and of the Council – December 4, 2000 on dioxins formation in waste incineration plants.

Investigation is made by coupling proper models developed within three commercial software environments: FLUENT, to reproduce the thermodynamic field inside the combustion chamber of the incinerator plant taken into account, MATLAB, to evaluate the position and temperatures of the particles 2 s after the last air injection, MODEFRONTIER, to change both the secondary air mass flow rate and the equivalent heat transfer coefficient of the refractory walls to fulfill the conflicting objectives of reducing the NO formation and increasing the mean gases temperature as required by the Directive.

The investigations suggest that it is possible to create the conditions allowing the reduction of NO emissions and the fulfilment of the European limits. In particular, the obtained results suggest that increasing the overall mass flow rate of the secondary air and using a different refractory material on the walls, the environmental performance of the incinerator plant can be improved.

Many other parameters could be optimized and, at the same time, more detailed models could be used for the Computational Fluid Dynamics simulations. Moreover, also the energy generated at the plant would need a better investigation in order to understand if optimal conditions can be really achieved.

The work covers new aspects of Waste-to-Energy (WtE) systems, since it deals with an optimization study of plant design and operating parameters. This kind of investigation allows not only to improve already existing technologies for WtE systems, but also to develop new ones.

This paper aims to focus on the mathematical modeling of magnetohydrodynamic natural convective boundary layer flow of nanofluids past a stationary and moving inclined porous plate considering temperature and concentration gradients with suction effects.

The transformed non-dimensional and coupled governing partial differential equations are solved numerically using the finite element method.

The obtained numerical results for physical governing parameters on the velocity, temperature and concentration distributions are exemplified graphically and presented quantitatively. The boundary layer thickness increased with the increasing values of Soret, Dufour and Grashof numbers, while the thickness of boundary layer decreased with increasing values of suction for both stationary and moving plate cases. The primary and secondary velocity profiles are decreasing with an angle of inclination for moving plate and inclination has no significant effect for the stationary plate. An increase of the Soret number and Dufour number tend to increase the heat and mass transfer, while an increase of suction reduces the heat and mass transfer.

The problem is an important contribution to the field of nanofluid science and technology and is relevant to high temperature rotating chemical engineering systems exploiting magnetized nanofluids. This study is relatively original in nanofluids.