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The purpose of this paper is twofold: first, it aims to investigate how salt and sugar reduction in foods due to the pressure from the emerging food regulations will affect the physico-electrical properties (PEPs) of orange juice and tomatoes during a selected PEP-dependent thermal processing. Second, the authors are keen to understand how variations in salt and sugar ingredients will affect the time-temperature processing requirements.

PEPs of the samples (orange juice and tomatoes) were measured using the KD2 thermal analyser and RS conductivity metre. Both samples with varying salt and sugar levels were subjected to ohmic heating processing using a 10 kW ohmic heater. Dehydration rates and processing times for pasteurisation were obtained.

Electrical conductivity increases with added salt in tomato puree but decreases with added sugar in orange juice. Statistical evidence confirmed significant changes in heating rates and processing times of tomatoes and orange juice as their relevant salt and sugar levels change. Reduction in salt content in tomato puree led to increase in time and energy for the thermal processes. While reduction in added sugar in orange juice results led to reduction in processing time and energy requirement for the processing operation.

The study is limited to small change in salt and sugar variations in order to reflect recommended limits. There were therefore no significant changes in thermal conductivity for the range investigated. Also this study is focussed on two food products.

Current pressure on the need to reduce salt and sugar in foods necessitates research to increase food processing industry insight into the process and product impacts of such recipe changes, with particular regard to processing efficiency and product safety and quality.

This study represents an attempt to understand the impact of salt and sugar variations on properties and processing requirements of tomato puree and orange juice.

The thermal behavior at the interfaces (of the deposited strands) during fused filament fabrication (FFF) technique strongly influences bond formation and it is a time- and temperature-dependent process. The processing parameters affect the thermal behavior at the interfaces and the purpose of the paper is to simulate using temperature-dependent (nonlinear) thermal properties rather than constant properties.

Nonlinear temperature-dependent thermal properties are used to simulate the FFF process in a simulation software. The finite-element model is first established by comparing the simulation results with that of analytical and experimental results of acrylonitrile butadiene styrene and polylactic acid. Strand temperature and time duration to reach critical sintering temperature for the bond formation are estimated for one of the deposition sequences.

Temperatures are estimated at an interface and are then compared with the experimental results, which shows a close match. The results of the average time duration (time to reach the critical sintering temperature) of strands with the defined deposition sequences show that the first interface has the highest average time duration. Varying processing parameters show that higher temperatures of the extruder and envelope along with higher extruder diameter and lower convective heat transfer coefficient will have more time available for bonding between the strands.

A novel numerical model is developed using temperature-dependent (nonlinear) thermal properties to simulate FFF processes. The model estimates the temperature evolution at the strand interfaces. It helps to evaluate the time duration to reach critical sintering temperature (temperature above which the bond formation occurs) as it cools from extrusion temperature.

During the thermal processing of thin films in which low intensity line heat sources are used, extended processing times are often required to reach steady state (˜15 sec). In addition, the melting of the film may occur some time after processing has begun, and therefore there is no initial melting condition within the film. In such cases, computer simulations may become very time consuming, and the development of an efficient computational method which incorporates the initial formation of the melt during processing is necessary. A general technique was developed to accurately model two‐dimensional heat conduction in a multilayer film structure with one‐dimensional phase change in one of the thin films. These conditions frequently exist in thin film thermal processing when the thermal gradient through the thickness of the melting film can be considered negligible. The method involves an implicit formulation of the modified enthalpy method. The solid/liquid interface energy‐balance equation is taken into account which allows the exact location of the interface to be tracked within a control volume. A comparison is made between the explicit and implicit modified methods to test efficiency and accuracy. The implicit method is then applied to the zone‐melting recrystallization of a silicon thin film in a multilayer structure.

AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity.

The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity.

The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm³ and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm³. The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains.

The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications.

To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

This study aims to design a novel strategy to avoid thermal defects in three-dimensional (3D) printing processes. A combination of subroutines and utility routines allows for in situ variations of the key process parameters (KPP) in the thermal simulation and produces by post-processing the output an updated machine code for enhanced quality of the printed part in a single iteration.

The input data for the thermal simulation were obtained by characterising an acrylonitrile butadiene styrene filament and calibrating an Ultimaker S5 printer. Abaqus subroutines were used to accurately simulate the continuous deposition of molten material. A utility routine extracted the nodal temperatures during simulation and detected regions that were prone to overheating. We developed a method, enabling the introduction of variable process parameters in the thermal simulation and validated it by printing several test geometries.

The results of the thermal simulation indicate that decreasing the print speed enhances the amount of heat dissipated to the environment. Therefore, it is an efficient way to avoid overheating of the printed geometry. The validation geometries showed improvements when adapting the print speed.

This approach is the first to demonstrate the potential of variable process parameters using implemented routines in the thermal process simulation. Here, the focus is on predicting and avoiding thermal hotspots. However, more potential can be obtained by enabling the prediction and adaptation of KPP to ensure mechanical performance. This would be an alternative way to tackle the cost- and time-inefficient post-processing of 3D-printed parts.

This study aims to numerically examine the influence of various geometric parameters of a novel W-shaped porous cavity undergoing hybrid nanofluid-based magnetohydrodynamic mixed convection. The W-shaped cavity is modified from the classical trapezoidal cavity by constructing a triangular shape at its bottom. This cavity is isothermally active at the bottom, with different numbers and heights of the triangular peak (or undulation). The heated hybrid nanofluid (Cu–Al₂O₃–H₂O) flow is cooled through the translating top wall. Inclined sidewalls are thermally insulated. To compare the impacts of change in geometric parameters, a square cavity under similar boundary conditions is also simulated. This study is carried out systematically addressing the various influences from a range of parameters like side angles (γ), number (m) and height (λ) of the bottom undulation, Reynolds number (Re), Richardson number (Ri), Darcy number (Da), Hartmann number (Ha), hybrid nanoparticles volume fraction (φ) on the overall thermal performance of the cavity.

Applying the finite volume approach, the transport equations involving multiphysical conditions like porous substance, hybrid nanofluid, magnetic field and shearing force are solved numerically by using a written FORTRAN-based code following the SIMPLE algorithm. The algebraic equations are solved over all the control volumes in an iterative process using the alternate direction implicit scheme and the tri-diagonal matrix algorithm. The converged solution of the iterative process is obtained when the relative error levels satisfy the convergence criterion of 10^–8 and 10^–10 for the maximum residuals and the mass defect, respectively.

It is revealed that an increase in the bottom undulation height always improves the thermal energy transfer despite the reduction of fluid volume. Thermal energy transfer significantly depends on the heating and cooling surface lengths, fluid volume in the cavity and the magnitude of the bottom undulation height of the W-shaped cavity. With the increase in bottom undulation height, effective heating length increases by ∼28%, which leads to a ∼15% reduction in the effective volume of the working fluid and a gain in heat transfer by ∼56.48%. In general, the overall thermal energy transport is improved by increasing Re, Ri and Da; whereas it is suppressed by increasing Ha.

There are many opportunities for future research experimentally or numerically, considering different curvature effects, orientations of the geometry, working fluids, boundary conditions, etc. Furthermore, this study could be extended by considering unsteady flow or turbulent flow.

In many modern systems/processes pertaining to materials processing, continuous casting, food processing, chemical reactors, biomedical applications, etc. fine control in the transport process is a major concern. The findings of this analysis can effectively be useful for other applications for getting more control features in terms of achieving the operational objectives. The approach of the system analysis (considering geometrical size parameters to delve into the underlying transport physics) and the obtained simulated results presented in the work can usefully be applicable to similar thermal systems/devices such as materials processing, thermal mixing, chemical reactors, heat exchangers, etc.

From the well-documented and vast pool of literature survey, it is understood that there exists no such investigation on the considered geometry and study. This study contributes a lot to understanding magnetic field moderated thermofluid flow of a hybrid nanofluid in a porous medium filled W-shaped cavity, in consideration of different geometrical shape parameters (undulation peak numbers at bottom wall, peak heights, side angles and heating and cooling length). Findings brought by this study provide great insights into the design and operation under various ranges of multiphysical thermofluid-flow processing phenomena.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This paper aims to investigate the role of shapes of containers (nine different containers) on entropy generation minimization involving identical cross-sectional area (1 sq. unit) in the presence of identical heating (isothermal). The nine containers are categorized into three classes based on their geometric similarities (Class 1: square, tilted square and parallelogram; Class 2: trapezoidal type 1, trapezoidal type 2 and triangular; Class 3: convex, concave and curved triangular).

Galerkin finite element method is used to solve the governing equations for a representative fluid (engine oil: Pr = 155) at Ra = 10³–10⁵. In addition, finite element method is used to solve the streamfunction equation and evaluate the entropy generation terms (S_ψ and S_θ). Average Nusselt number (Nub¯) and average dimensionless spatial temperature (θ^) are also evaluated via the finite element basis sets.

Based on larger Nub¯, larger θ^ and optimal S_total values, containers from each class are preferred as follows: Class 1: parallelogrammic and square, Class 2: trapezoidal type 1 and Class 3: convex (larger θ^, optimum S_total) and concave (larger Nub¯). Containers with curved walls lead to enhance the thermal performance or efficiency of convection processes.

Comparison of entropy generation, intensity of thermal mixing (θ^) and average heat transfer rate give a clear picture for choosing the appropriate containers for processing of fluids at various ranges of Ra. The results based on this study may be useful to select a container (belonging to a specific class or containers with curved or plane walls), which can give optimal thermal performance from the given heat input, thereby leading to energy savings.

This study depicts that entropy generation associated with the convection process can be reduced via altering the shapes of containers to improve the thermal performance or efficiency for processing of identical mass with identical heat input. The comparative study of nine containers elucidates that the values of local maxima of S_ψ (S_ψ,max), S_θ (S_θ,max) and magnitude of S_total vary with change in shapes of the containers (Classes 1–3) at fixed Pr and Ra. Such a comparative study based on entropy generation minimization on optimal heating during convection of fluid is yet to appear in the literature. The outcome of this study depicts that containers with curved walls are instrumental to optimize entropy generation with reasonable thermal processing rates.

The numerical simulation of practical thermal processes is generally complicated because of multiple transport mechanisms and complex phenomena that commonly arise. In addition, the materials encountered are often not easily characterized and typically involve large property changes over the ranges of interest. The boundary conditions may not be properly defined and or may be unknown. However, it is important to obtain accurate and dependable numerical results from the simulation in order to study, design, and optimize most practical thermal processes of current and future interest. The purpose of this paper is to focus on the main challenges that are encountered in obtaining accurate numerical simulation results on practical thermal processes and systems.

A wide range of thermal systems is considered and the challenges faced in the numerical simulation are outlined. The methods that may be used to meet these challenges are presented in terms of grid, solution strategies, multiscale modeling and combined mechanisms. The models employed must be validated and the accuracy of the simulation results established if the simulation is to form the basis for improving existing systems and developing new ones.

Of particular interest are concerns like verification and validation, imposition of appropriate boundary conditions, and modelling of complex, multimode transport phenomena in multiple scales. Additional effects such as viscous dissipation, surface tension, buoyancy and rarefaction that could arise and complicate the modelling are discussed. Uncertainties that arise in material properties and in boundary conditions are also important in design and optimization. Large variations in the geometry and coupled multiple regions are also discussed.

The paper is largely focused on numerical modeling and simulation. Experimental data are considered mainly for validation and for physical insight.

A wide variety of practical systems, ranging from materials processing to energy, cooling, and transportation is considered.

Future needs in this interesting and challenging area are also outlined in the paper.

This paper presents the application of grey modeling for thermal spray processing parameter analysis in less data environment.

Based on processing knowledge, key processing parameters of thermal spray process are analyzed and preselected. Then, linear and non-linear grey modeling models are integrated to mine the relationships between different processing parameters.

Model A reveals the linear correlation between the HVOF process parameters and the characterization of particle in-flight with average relative errors of 9.230 percent and 5.483 percent for velocity and temperature.

The prediction accuracies of coatings properties vary, which means that there exists more complex non-linear relationship between the identified input parameters and coating results, or more unexpected factors (e.g. factors from material side) should be further investigated.

According to the modeling case in this paper, method has potential to deal with other diverse modeling problems in different industrial applications where challenge to collecting large quantity of data sets exists.

It is the first time to apply grey modeling for thermal spray processing where complicated relationships among processing parameters exist. The modeling results show reasonable results to experiment and existing processing knowledge.