Apichit Maneengam's research while affiliated with King Mongkut's University of Technology North Bangkok and other places

... Moreover, few other studies suggest that renewable energy does not contribute to a reduction in emissions (Apergis et al., 2010). While technological innovation can effectively reduce carbon emissions by improving energy utilization efficiency (Avagyan, 2018;Du et al., 2019;Zhao and Tian, 2022;Lin and Ma, 2022;Ramzan et al., 2023;Temesgen Hordofa et al., 2023), it can also stimulate an increase in output, increasing energy use and indirectly contributing to increased carbon emissions (Avagyan, 2018;Avagyan and Singh, 2019;Chen and Lee, 2020;Petrovic & Lobanov, 2020). However, despite the strong commitment and contribution of scholars to pursue the rapid transition to renewable energy, the current technologies used in its production are still underdeveloped, and the research on renewable energy's impact on carbon emissions remains controversial and equivocal (Razzaq et al., 2023;Jain, 2023;Wang et al., 2022;Qing et al., 2023). ...

... In this study, we investigated the trading risk spillover effect among China's rare earth market assets, including catalysts and oxides in the Baotou Rare Earth Products Exchange (BREPE), and we analyzed the formation mechanism using the impulse response. Previous research has mostly focused on a single rare earth asset such as yttrium's general characteristics or on rare earth stocks based on geological and geochemical data to investigate the trading risk [7]; however this has not occurred at the level of the entire rare earth trading market [8]. Furthermore, there is much research on cross-markets such as China and the USA as well as the linkage to traditional financial system or economic policy uncertainty [2,8,9]. ...

... Thermophysical properties of the NEPCMs and the base liquid[30][31][32]. ...

... The reducing effect of low thermal conductivity of PCMs could be mitigated by introducing heat transfer enhancing methods on both PCM and HTF sides [37]. The heat transfer improvement method includes employing turbulence inducer structures [38,39], thermal conductivity enhancement or viscosity reduction using nanoparticles (NP)s [40,41] and using extended surfaces or fins [42,43]. Several studies were conducted to reveal the enhancing effect of fin geometry, their numbers and their orientation in the LTEE system [44,45]. ...

... The first one is related to the shape of the elements of the system [6][7][8][9][10][11]. The second aspect of the research is based on the quality of the fluid and the effects of its thermal properties on the thermal activity [12][13][14][15][16]. The improvement of thermal properties of fluids is presented as follows: The first type of fluid is called complex fluid [17][18][19][20][21][22]. ...

... Fossil fuels such as coal, natural gas, and petroleum have been extensively used as raw materials for synthesizing several fuels and chemicals. However, these non-renewable materials have caused a variety of damaging effects to the environment, such as global warming from greenhouse gas (GHG) emissions, land contamination, and air/water pollution [1]. In the last few decades, renewable materials have gained much attention worldwide as promising substitutes for petroleum-based materials, given their environmental benefits and sustainable properties [1,2]. ...

... In a Multivariate Bayesian framework, apply sign limitations to separate oil price supply from inflationary pressures to discover the fundamental price fluctuations shocks and responses. This is similar to the vector Autoregression model proposed by (Yating et al., 2022), in which the real price of crude oil is broken down into three components: shocks to consumer spending for commodities and services as a whole, as well as shocks to crude oil supply, with the latter accounting for the bulk of the higher preventative measure demand for an uncertain future supply. ...

... This class of fluids is characterized by its viscosity, which is related to the shear stress of the fluid. That is, the reduction of the viscosity of the fluid allows an increase in the flow of thermal energy from the solid to the fluid, which increases the thermal activity; the second class of fluids is called nanofluids [23][24][25][26][27][28][29][30]. This type of fluid is characterized by its high ability to transfer thermal energy between a solid and a liquid. ...

... One challenge left is how to pack the PCMs in the equipment, which has to be investigated in a laborious experimental manner. Computational fluid dynamics (CFD) models help to reduce the experimental effort [22][23][24][25][26][27]; whereas, it has to distinguished if the phase behaviour of the PCM itself will be modelled or the application of the PCM in large-scale. For the simulation of the PCM, the surface between the solid and the liquid phase has to be traced and a two-phase system has to be modelled. ...

... Hence, the robustness of a logistics network can be measured by the space dimension and time dimension. In the space dimension, graph theory has been widely used to describe the interactions and interdependencies between topology nodes and edges, which can directly evaluate the importance of nodes or edges and is useful to measure the logistics network's robustness [1][2][3][4][5][6][7][8][9][10][11]. ...