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The purpose of this study is to analyze the question “In what order of magnitude does the comfort and performance improvement lie with the use of a cooling vest for construction workers?”.

The use of personal cooling systems, in the form of cooling vests, is not only intended to reduce the heat load, in order to prevent disruption of the thermoregulation system of the body, but also to improve work performance. A calculation study was carried out on the basis of four validated mathematical models, namely a cooling vest model, a thermophysiological human model, a dynamic thermal sensation model and a performance loss model for construction workers.

The use of a cooling vest has a significant beneficial effect on the thermal sensation and the loss of performance, depending on the thermal load on the body.

Each cooling vest can be characterized on the basis of the maximum cooling power (Pmax; in W/m²), the cooling capacity (Auc; in Wh/m2) and the time (tc; in minutes) after which the cooling power is negligible. In order to objectively compare cooling vests, a (preferably International and/or European) standard/guideline must be compiled to determine the cooling power and the cooling capacity of cooling vests.

It is recommended to implement the use of cooling vests in the construction process so that employees can use them if necessary or desired.

Climate change, resulting in global warming, is one of the biggest problems of present times. Rising outdoor temperatures will continue in the 21st century, with a greater frequency and duration of heat waves. Some regions of the world are more affected than others. Europe is one of the regions of the world where rising global temperatures will adversely affect public health, especially that of the labor force, resulting in a decline in labor productivity. It will be clear that in many situations air conditioning is not an option because it does not provide sufficient cooling or it is a very expensive investment; for example, in the situation of construction work. In such a situation, personal cooling systems, such as cooling vests, can be an efficient and financially attractive solution to the problem of discomfort and heat stress.

The value of the study lies in the link between four validated mathematical models, namely a cooling vest model, a thermophysiological human model, a dynamic thermal sensation model and a performance loss model for construction workers.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

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.

The purpose of this paper is to analyze how far technology and information enable, facilitate or support the planning and implementation decisions in humanitarian vaccine cold chains for vaccination campaigns. The authors specifically focus on three emerging technologies that have the potential to create more flexible conditions in the field, and identify the need to further explore the link between uncertainty, information and irreversibility.

The authors present a basic structure for the analysis of cold chain disruptions in terms of three distinct yet connected layers of deficient infrastructure and capacity, information gaps and failures in decision making. The authors then review three humanitarian technologies and their impact on vaccine campaigns along these layers. From there, a research agenda is developed to address research gaps this review brought forward.

Three critical research gaps in the areas of technology innovation for humanitarian vaccine cold chain management are presented. The authors argue that technology to improve capacity, information and decisions need to be aligned, and that the areas of uncertainty, information and irreversibility require further investigation to achieve this alignment. In this way, the paper contributes to setting the research agenda on vaccine cold chains and connects humanitarian logistics to technology, information management and decision making.

This paper presents the humanitarian vaccine cold chain problem from an original angle by illuminating the implications of technology and information on the decisions made during the planning and implementation phases of a vaccine campaign. The authors develop an agenda to provide researchers and humanitarians with a perspective to improve cold chain planning and implementation at the intersection of technology, information and decisions.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

The adverse impacts of climate change coupled with rapid informal urbanization in the Southern African region are increasing the vulnerability of already sensitive population groups. Consequently, these urban regions are highly vulnerable to urban heat island effects and heatwaves due to exogenous and endogenous factors. While the dynamic interplay between the built environment, climate and response strategies is known, this paper highlights the lived experience of informal settlement residents. It presents work from a project undertaken in Melusi, an informal settlement in Tshwane, South Africa, as a multi-disciplinary project focusing on improving the local resilience to climate change associated heat stress.

Following a mixed method approach, a semi-structured observational analysis of the spatial layout and material articulation of selected dwellings along with the continuous monitoring and recording of their indoor environments were undertaken.

The paper presents the research results in terms of the dwelling characteristics, as spatial and material-use strategies and documented heat stress exposure in these structures. The findings highlight that informal dwellings perform poorly in all cases due to endogenous factors and that inhabitants experience extreme heat stress conditions for between 6 and 10 h daily during the peak summer period.

Currently, there are little empirical data on the heat stress residents living in informal settlements in Southern Africa are experiencing. This article provides insight into the indoor environments of informal dwellings and hopes to contribute future guidelines or heat health policies.