Jayapura City, Indonesia, presents significant potential for solar energy utilisation, driven by its high solar radiation levels. However, the presence of urban obstacles, such as buildings, trees, and varied topography, can obstruct the direct transmission of solar radiation to the ground, thereby reducing its efficiency for solar energy systems. This study aims to develop a methodology for predicting and assessing the shade projection of solar radiation intensity across Jayapura City. A quantitative descriptive approach was employed, involving the measurement of elevation and azimuth angles using Global Positioning System (GPS) technology. Data were analysed using RETScreen and Sun Locator Pro (SLP) software. The analysis of the collected data facilitated the generation of a detailed shade projection map, which can be utilised to optimise the placement of solar panels and enhance the performance of the city's Solar Power Generation System (SPGS). The findings indicated that the highest elevation angle occurred at 12:00 pm in March. In September, the sun's position was nearly directly above the equator, leading to a minimal shadow ratio (SR = 0.08), with the projection closely aligned with the object. The azimuth angle, measured at noon, exhibited an extreme angular shift, reflecting the standard reference towards the north (180° at noon). This study demonstrates the potential of this methodology to inform the strategic placement of solar infrastructure, improving the efficiency and efficacy of solar power systems in urban environments characterised by complex topographies.

In the realm of heat transfer, the phenomenon of boiling heat transfer is paramount, especially given its efficiency in harnessing the latent heat of vaporization for significant thermal energy removal with minimal temperature alterations. This mechanism is integral to various industrial applications, including but not limited to the cooling systems of nuclear reactors, macro- and micro-electronic devices, evaporators in refrigeration systems, and boiler tubes within power plants, where the nucleate pool boiling regime and two-phase flow are prevalent. The imperative to optimize heat exchange systems by mitigating excessive heat dissipation, whilst simultaneously achieving downsizing, has consistently been a critical consideration. This research uses computational, based on Fluent software, to analyze thermal characteristics and cooling mechanisms of different concentrations of nanofluids, in conjunction with surfaces adorned with diverse fin geometries. Specifically, the study scrutinizes the thermal performance of water-based nanofluids, incorporating Copper (II) Oxide (CuO) nanoparticles at concentrations ranging from 0% to 1.4% by volume, under boiling conditions. The analyses extend to the efficacy of different fin shapes—including circular, triangular, and square configurations-within a two-dimensional geometry, under the conditions of forced convection heat transfer in both steady and transient, viscous, incompressible flows. The findings are poised to contribute to the design of more efficient heat exchange systems, facilitating enhanced heat dissipation through the strategic use of nanofluids and meticulously designed surface geometries.

C4 olefin is an important chemical raw material, but traditional production methods use limited and polluting fossil energy as raw materials. Ethanol stands out from many alternative energy sources because of its wide sources, easy conversion, and low pollution. The preparation of C4 olefins from ethanol has become an effective alternative route for olefin production, which has great environmental and economic value. Metal oxides are the main catalysts for the preparation of C4 olefins from ethanol. In this paper, a $\mathrm{SiO}_2$-$\mathrm{HAP}$ catalyst with both acid and base active sites was designed, and Co metal with dehydrogenation activity was supported on its surface. To improve the catalytic activity and improve the conversion of ethanol and the selectivity of C4 olefin, experiments were carried out by changing the process parameters such as $\mathrm{Co}$ loading (weight ratio of $\mathrm{Co}$ to $\mathrm{SiO}_2$), HAP (hydroxyapatite) mass, ethanol concentration, and reaction temperature. The improved gray relational degree algorithm was used to analyze the relational degree of process parameters with ethanol conversion and C4 olefin selectivity. Experimental results show that the detection accuracy of this algorithm for C4 olefin selectivity is better than that of the traditional algorithm without considering the difference in change rate between data, the detection accuracy is improved by 50%, and the detection accuracy of ethanol conversion is improved by 2%.

Solar energy, a ubiquitous and environmentally friendly source, plays a pivotal role in mitigating carbon emissions and reducing air pollution. This study evaluates the performance of a 50-watt monocrystalline solar panel over a thirty-day period in October 2022, within Merauke Regency, South Papua Province, Indonesia. Adopting an experimental research methodology and comprehensive data collection, measurements of solar intensity, temperature, voltage, and current were systematically gathered using temperature sensors, ammeters, and voltmeters. These measurements were obtained by positioning the solar panel at a perpendicular angle to direct sunlight, with data recorded between 9:00 and 16:00 Eastern Indonesia Time. The analysis of the collected data was conducted to ascertain the panel's efficacy, revealing an average output of 20.68 volts, 1.95 amperes, 40.37 watts, and a 9% efficiency. Notably, peak performance was observed on the tenth day, characterized by 21.30 volts, 2.24 amperes, 47.71 watts, and an efficiency of 11.01%. The findings of this investigation are anticipated to inform the installation and utilization strategies of similar solar panel types within Merauke Regency and potentially broader applications. This study underscores the critical influence of solar irradiance on the operational performance of monocrystalline silicon solar panels, contributing valuable insights to the field of renewable energy research.