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Three-dimensional printing (3DP) is an established process to print structural parts of metals, ceramic and polymers. Further, multi-material 3DP has the potentials to be a milestone in rapid manufacturing (RM), customized design and structural applications. Being compatible as functionally graded materials in a single structural form, multi-material-based 3D printed parts can be applied in structural applications to get the benefit of modified properties.

The fused deposition modelling (FDM) is one of the established low cost 3DP techniques which can be used for printing functional/ non-functional prototypes in civil engineering applications.

The present study is focused on multi-material printing of primary recycled acrylonitrile butadiene styrene (ABS), polylactic acid (PLA) and high impact polystyrene (HIPS) in composite form. Thermal (glass transition temperature and heat capacity) and mechanical properties (break load, break strength, break elongation, percentage elongation at break and Young’s modulus) have been analysed to observe the behaviour of multi-material composites prepared by 3DP. This study also highlights the process parameters optimization of FDM supported with photomicrographs.

The present study is focused on multi-material printing of primary recycled ABS, PLA and HIPS in composite form.

Efficient thermal management of central processing unit (CPU) cooling systems is vital in the context of advancing information technology and the demand for enhanced data processing speeds. This study aims to explore the thermal performance of a CPU cooling setup using a cylindrical porous metal foam heat sink.

Nanofluid flow through the metal foam is simulated using the Darcy–Brinkman–Forschheimer equation, accounting for magnetic field effects. The temperature distribution is modeled through the local thermal equilibrium equation, considering viscous dissipation. The problem’s governing partial differential equations are solved using the similarity method. The CPU’s hot surface serves as a solid wall, with nanofluid entering the heat sink as an impinging jet. Verification of the numerical results involves comparison with existing research, demonstrating strong agreement across numerical, analytical and experimental findings. Ansys Fluent® software is used to assess temperature, velocity and streamlines, yielding satisfactory results from an engineering standpoint.

Investigating critical parameters such as Darcy number (10⁻⁴ ≤ Da_D ≤ 10⁻²), aspect ratio (0.5 ≤ H/D ≤ 1.5), Reynolds number (5 ≤ Re_D,bf ≤ 3500), Eckert number (0 ≤ EC_bf ≤ 0.1) , porosity (0.85 ≤ ε ≤ 0.95), Hartmann number (0 ≤ Ha_D,bf ≤ 300) and the volume fraction of nanofluid (0 ≤ φ ≤ 0.1) reveals their impact on fluid flow and heat sink performance. Notably, Nusselt number will reduce 45%, rise 19.2%, decrease 14.1%, and decrease 0.15% for Reynolds numbers of 600, with rising porosity from 0.85 to 0.95, Darcy numbers from 10⁻⁴ to 10⁻², Eckert numbers from 0 to 0.1, and Hartman numbers from 0 to 300.

Despite notable progress in studying thermal management in CPU cooling systems using porous media and nanofluids, there are still significant gaps in the existing literature. First, few studies have considered the Darcy–Brinkman–Forchheimer equation, which accounts for non-Darcy effects and the flow and geometric interactions between coolant and porous medium. The influence of viscous dissipation on heat transfer in this specific geometry has also been largely overlooked. Additionally, while nanofluids and impinging jets have demonstrated potential in enhancing thermal performance, their utilization within porous media remains underexplored. Furthermore, the unique thermal and structural characteristics of porous media, along with the incorporation of a magnetic field, have not been fully investigated in this particular configuration. Consequently, this study aims to address these literature gaps and introduce novel advancements in analytical modeling, non-Darcy flow, viscous dissipation, nanofluid utilization, impinging jets, porous media characteristics and the impact of a magnetic field. These contributions hold promising prospects for improving CPU cooling system thermal management and have broader implications across various applications in the field.

One of the major challenges in the design of thermal equipment is to minimize the entropy production and enhance the thermal dissipation rate for improving energy efficiency of the devices. In several industrial applications, the structure of thermal device is cylindrical shape. In this regard, this paper aims to explore the impact of isothermal cylindrical solid block on nanofluid (Ag – H₂O) convective flow and entropy generation in a cylindrical annular chamber subjected to different thermal conditions. Furthermore, the present study also addresses the structural impact of cylindrical solid block placed at the center of annular domain.

The alternating direction implicit and successive over relaxation techniques are used in the current investigation to solve the coupled partial differential equations. Furthermore, estimation of average Nusselt number and total entropy generation involves integration and is achieved by Simpson and Trapezoidal’s rules, respectively. Mesh independence checks have been carried out to ensure the accuracy of numerical results.

Computations have been performed to analyze the simultaneous multiple influences, such as different thermal conditions, size and aspect ratio of the hot obstacle, Rayleigh number and nanoparticle shape on buoyancy-driven nanoliquid movement, heat dissipation, irreversibility distribution, cup-mixing temperature and performance evaluation criteria in an annular chamber. The computational results reveal that the nanoparticle shape and obstacle size produce conducive situation for increasing system’s thermal efficiency. Furthermore, utilization of nonspherical shaped nanoparticles enhances the heat transfer rate with minimum entropy generation in the enclosure. Also, greater performance evaluation criteria has been noticed for larger obstacle for both uniform and nonuniform heating.

The current numerical investigation can be extended to further explore the thermal performance with different positions of solid obstacle, inclination angles, by applying Lorentz force, internal heat generation and so on numerically or experimentally.

A pioneering numerical investigation on the structural influence of hot solid block on the convective nanofluid flow, energy transport and entropy production in an annular space has been analyzed. The results in the present study are novel, related to various modern industrial applications. These results could be used as a firsthand information for the design engineers to obtain highly efficient thermal systems.

This paper aims to perform thermal and mechanical characterization for silver-based sintered thermal joints. Layer quality affects thermal and mechanical performance, and it is important to achieve information about how materials and process parameters influence them.

Thermal investigation of the thermal joints analysis method was focused on determination of thermal resistance, where temperature measurements were performed using infrared camera. They were performed in two modes: steady-state analysis and dynamic analysis. Mechanical analysis based on measurements of mechanical shear force. Additional characterizations based on X-ray image analysis (image thresholding), optical microscope of polished cross-section and scanning electron microscope image analysis were proposed.

Sample surface modification affects thermal resistance. Silver metallization exhibits the lowest thermal resistance and the highest mechanical strength compared to the pure Si surface. The type of dynamic analysis affects the results of the thermal resistance.

Investigation of the layer quality influence on mechanical and thermal performance provided information about different joint types.

This study aims to explore the enhancement of mechanical properties in epoxy resin composites through the incorporation of graphene nanoparticles, focusing on their impact and wear resistance. It investigates the role of graphene, both treated and untreated, as a reinforcing agent in composites, highlighting the significance of nanoparticle dispersion and surfactant treatment in optimizing mechanical performance.

Employing a novel dispersion technique using a drawing brush, this research contrasts with traditional methods by examining the effects of graphene nanoparticle concentrations treated with surfactants – Polyvinylpyrrolidone (PVP) and Sulphonated Naphthalene Formaldehyde (SNF) – on the mechanical properties of epoxy resin composites. The methodology includes conducting a series of impact and wear tests to assess the influence of graphene reinforcement on the composites' performance.

The findings reveal a marked enhancement in the composites impact resistance and energy absorption capabilities, which escalate with an increase in graphene content. Additionally, the study demonstrates a significant improvement in wear resistance, attributed to the superior mechanical properties, robust interface adhesion and effective dispersion of graphene. The use of surfactants for graphene treatment is identified as a crucial factor in these advancements, offering profound insights into the development of advanced composite materials for diverse industrial uses.

This study introduces a unique dispersion technique for graphene in epoxy composites, setting it apart from conventional methods. By focusing on the critical role of surfactant treatment in enhancing the mechanical properties of graphene-reinforced composites, it provides a novel insight into the optimization of impact and wear resistance.

The aim was not to perform a systematic review but firstly to search in PubMed, Science Direct, Scopus and Web of Science databases on the papers published in the last five years using tools for reviewing the statement of preferred information item for systematic reviews without focusing on a randomized analysis and secondly to perform a bibliometric analysis on the properties of films and coatings added of tocopherol for food packaging.

On January 24, 2022, information was sought on the properties of films and coatings added of tocopherol for use as food packaging published in PubMed, Science Direct, Scopus and Web of Science databases. Further analysis was performed using bibliometric indicators with the VOSviewer tool.

The searches returned 33 studies concerning the properties of films and coatings added of tocopherol for food packaging, which were analyzed together for a better understanding of the results. Data analysis using the VOSviewer tool allowed a better visualization and exploration of these words and the development of maps that showed the main links between the publications.

In the area of food science and technology, the development of polymers capable of promoting the extension of the shelf life of food products is sought, so the knowledge of the properties is vital for this research area since combining a biodegradable polymeric material with a natural antioxidant active is of great interest for modern society since they associate environmental preservation with food preservation.

In fire resistance tests (FRTs) of building materials, a crucial criterion to pass the test procedure is to avoid the leakage of the hot flue gases caused by gaps and cracks occurring due to the thermal exposure. The present study's aim is to calculate the deformation of a steel door, which is embedded within a wall made of bricks, and qualitatively determine the flue gas leakage.

A computational fluid dynamics/finite element method (CFD/FEM) coupling was introduced representing an intermediate approach between a one-way and a full two-way coupling methodology, leading to a simplified two-way coupling (STWC). In contrast to a full two way-coupling, the heat transfer through the steel door was simulated based on a one-way approach. Subsequently, the predicted temperatures at the door from the one-way simulation were used in the following CFD/FEM simulation, where the fluid flow inside and outside the furnace as well as the deformation of the door were calculated simultaneously.

The simulation showed large gaps and flue gas leakage above the door lock and at the upper edge of the door, which was in close accordance to the experiment. Furthermore, it was found that STWC predicted similar deformations compared to the one-way coupling.

Since two-way coupling approaches for fluid/structure interaction in fire research are computationally demanding, the number of studies is low. Only a few are dealing with the flue gas exit from rooms due to destruction of solid components. Thus, the present study is the first two-way approach dealing with flue gas leakage due to gap formation.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.