Thermo, Volume 4, Issue 1 (March 2024) – 9 articles

The phase behavior of lipids extracted from Astrocaryum vulgare (AV) and Astrocaryum aculeatum (AA) pulp and kernels and their microstructural, thermal and flow properties were studied. The lipid profiles, crystal structures, microstructures, thermal stabilities and flow behaviors of these lipids provided important structure–function information that are useful to assess potential applications in the food, cosmetic and pharmaceutical industries. AV and AA fruits were sourced from the lowlands and rainforests, respectively, of Guyana. AV and AA pulp oils (AVP and AAP) were distinguished from each other in composition and unsaturation, with AVP oils being predominated by a di-unsaturated TAG (2-(palmitoyloxy)propane-1,3-diyl dioleate (POO)) and AAP oils predominated by propane-1,2,3-triyl trioleate (OOO); there were unsaturation levels of 65% and 80%, respectively. The main fatty acids in AVP oils were oleic, palmitic and stearic; for AAP, these were oleic, linoleic, palmitic and stearic. The kernel fats of AV and AA were similar in composition and had saturation levels of 80%, being mainly comprised of tri-saturated TAGs propane-1,2,3-triyl tridodecanoate (LLL) and 3-(tetradecanoyloxy)propane-1,2-diyl didodecanoate (LML). The onset of mass loss $\left(T_{5\%}^{on}\right)$ of AV and AA pulp oils were similar at 328 ± 6 °C, which were 31 °C ± 9 higher compared to that of the kernel fats, which demonstrated similar $T_{5\%}^{on}$ = 293 ± 7 °C. AA and AV pulp oils were liquid at room temperature, with melting points of −5 ± 1 °C and 3 ± 1 °C, respectively; both kernel fats were solid at room temperature, packing in β′ (90% of crystals) and β (10% of crystals) polymorphic forms and melting almost identically at 30 ± 1 °C. Pulp oils demonstrated sporadic nucleation at the onset of crystallization with slow growth into rod-shaped crystallites, leading to an approximately 50% degree of crystallization at undercooling of approximately 40K. Nucleation for kernel fats was instantaneous at undercooling of approximately 23K, demonstrating a spherulitic growth pattern incorporating crystalline lamella and a 90% degree of crystallization. Kernel fats and pulp oils demonstrated Newtonian flow behavior and similar dynamic viscosity in the melt, approximately 28.5 mPa·s at 40 °C. The lipid profiles of AVP and AAP oils were dominated by unsaturated TAGs, suggesting potential nutrition and health benefits, particularly compared to other tropical oils with higher saturation levels, such as palm oil. AAP oil in particular is as unsaturated as olive oil, contains high levels of beta carotene and provides a unique flavor profile. The AAK and AVK lipid profiles and phase transformation indicate potential for applications where a high solid fat content and medium-chain fatty acids are required. Their high lauric and myristic acid content makes them similar to industrially important tropical oils (coconut and palm kernel), suggesting their use in similar formulations. The melting point and plasticity of the kernel fats are similar to that of cocoa and shea butters, suggesting use as replacements in cosmetics, foods and confections. There is, however, the need to better understand their nutritional status and effects on health. Full article

Given the climate change in recent decades and the ever-increasing energy consumption in the building sector, research is widely focused on the green revolution and ecological transition of buildings. In this regard, artificial intelligence can be a precious tool to simulate and optimize building energy performance, as shown by a plethora of recent studies. Accordingly, this paper provides a review of more than 70 articles from recent years, i.e., mostly from 2018 to 2023, about the applications of machine/deep learning (ML/DL) in forecasting the energy performance of buildings and their simulation/control/optimization. This review was conducted using the SCOPUS database with the keywords “buildings”, “energy”, “machine learning” and “deep learning” and by selecting recent papers addressing the following applications: energy design/retrofit optimization, prediction, control/management of heating/cooling systems and of renewable source systems, and/or fault detection. Notably, this paper discusses the main differences between ML and DL techniques, showing examples of their use in building energy simulation/control/optimization. The main aim is to group the most frequent ML/DL techniques used in the field of building energy performance, highlighting the potentiality and limitations of each one, both fundamental aspects for future studies. The ML approaches considered are decision trees/random forest, naive Bayes, support vector machines, the Kriging method and artificial neural networks. The DL techniques investigated are convolutional and recursive neural networks, long short-term memory and gated recurrent units. Firstly, various ML/DL techniques are explained and divided based on their methodology. Secondly, grouping by the aforementioned applications occurs. It emerges that ML is mostly used in energy efficiency issues while DL in the management of renewable source systems. Full article

To ascertain the significance of temperature and residence time of hydrothermal carbonization (HTC) in controlling hydrochar production, multiple regression was employed based on central composite design (CCD) to model the responses of mass yield (MY) and higher heating value (HHV). The hydrothermal reaction was explored at temperatures and times ranging from 150 to 250 °C and 0.5 to 3.5 h. Sorghum bagasse (SB) and microalgae (MA) were used to complex the reaction due to their differences in organic constituents. Simultaneously, the operating parameters were optimized by maximizing the response values under domain constraints in the HHV models. The results show that at least temperature and time in the linear system played a significant role in determining the solids recovery and the energy generation of hydrochars (p-values = 0.00), regardless of the biomass type. Moreover, the optimum conditions of SB and MA hydrochars can be achieved by increasing the temperature to the limit of 250 °C and prolonging the time to 3.5 and 3.25 h, respectively. Both respective conditions resulted in maximum HHVs of 27.54 and 35.83 MJ kg⁻¹. Full article

This paper addresses the often overlooked, yet critical, aspect of designing and optimizing the surface pipeline network for the transportation of geothermal fluids from the wellheads to the delivery point, such as greenhouses, food drying plants, or fish farming units. While research on the geothermal industry predominately focuses on the reservoir and well engineering aspects of exploitation, insufficient attention has been given to the design of the pipeline network, leading to improper design and significant, yet avoidable, energy losses. Thus, this paper presents a comprehensive methodology for modeling and simulating geothermal fluid flow within the pipeline network by fully considering all hydraulic (friction, viscous flow, and gravity effects) and thermal (open air and underground pipeline heat loss) phenomena. These two aspects are handled simultaneously by setting up and solving the coupled set of the governing (differential) equations. We also demonstrate the difficulties that arise when attempting the solution of the mathematical problem, such as potential instability or lack of convergence. Finally, a fully detailed study of the real-world geothermal production system is presented utilizing the developed methodology to optimize the design and operation conditions of the system. By integrating debottlenecking strategies into the analysis, this approach not only maximizes power output, but also identifies and mitigates constraints within the system, ensuring efficient operation and performance increase. Full article

Preheating is important to improve the mechanical properties of nickel-based superalloys processed by additive manufacturing. The microstructure of IN718 was found to be influenced by the preheating temperature. Different preheating temperatures affect mechanical properties by changing microstructures. This work aims to clarify the thermal behavior for two preheated base plate temperatures (200 °C and 600 °C) on the IN718 superalloy built by the selective laser melting (SLM) process using the finite element method and experiments. The simulation findings indicate that the preheated 600 °C model has a deeper melt pool, a slower transformation of liquid to solid, and a slower cooling rate compared to the 200 °C model. As a result, the interdendritic Niobium (Nb) segregation of IN718 is reduced, thus improving the mechanical properties of additive-manufactured IN718 using the laser. The solidification map derived from the simulation indicates a columnar microstructure for the IN718 superalloy. Preheating increased the size of the dendrite structure and reduced elemental segregation, but it did not affect the morphology or size of crystal grains. We focused on comparing the temperature gradient and cooling rate for the two preheated base plate temperatures using the solidification map of IN718. The simulation confirmed that preheating does not affect the grain structure. Full article

Polymer thermal conductivities play an important role for their potential use in industrial applications. Therefore, great efforts have been made to investigate fundamental structure–property relationships to understand and predict thermal conductivities for polymers and their composites. The review summarizes selected well-proven microscopic theoretical approaches to calculate thermal conductivities such as EMD, NEMD, EMT, and BTE, and cites examples to focus on different qualitative aspects of recent polymer theoretical research. Examples other than polymer materials are given as supplemental information to support the general discussion of heat transport phenomena in solid materials. Full article

Multiwalled carbon nanotubes (MWCNTs) exhibit outstanding physical properties, including high thermal conductivity, excellent mechanical strength, and low electrical resistivity, which make them suitable candidates for a variety of applications. The work presented in this paper focuses on the pool boiling performance of refrigerant R-134a on microporous Cu-MWCNT composite surface layers. A two-stage electrodeposition technique was used to fabricate Cu-MWCNT composite coatings. In order to achieve variation in the surface properties of the Cu-MWCNT composite surface layer, electrodeposition was carried out at various bath temperatures (25 °C, 30 °C, 35 °C, and 40 °C). All surfaces coated with the Cu-MWCNT composite demonstrated superior boiling performance compared to the uncoated surface. Heat transfer coefficient (HTC) values for Cu-MWCNT composite surface layers, prepared at bath temperatures of 25 °C, 30 °C, 35 °C, and 40 °C, exhibited improvements of up to 1.75, 1.88, 2.06, and 2.22, respectively, in comparison to the plain Cu surface. Full article

In this work, different CFD models to compute flows inside a steam ejector were investigated. The results were compared to the analytical models as well as the experimental results from the literature. All the simulations gave realistic results from the hydrodynamic perspective with a relative error of the entrainment ratio between 25% and 40% compared to reference experimental data. However, an analysis of the temperature profiles showed that only realistic results from the thermodynamic perspective were given by multiphase calculations. The first multiphase model tested was the so-called Wet-Steam model from ANSYS Fluent. This model gave inconsistent results for the steam ejector CFD simulation due to the physical boundaries of this model. The second model tested was the Eulerian mixture model, which gave the most realistic results in terms of the physical conditions of the liquid and vapor phases inside the ejector. It also showed that the phase change could have a significant impact on the value of the critical output pressure as a way to improve the performance of the ejector. Full article