Advances in Science and Technology Vol. 126

Abstract: Ordinary Portland Cement (OPC) used in building structures has a negative impact. The presence of CO2 emissions produced becomes very dangerous. To reduce this impact, materials that are more environmentally friendly are used. Silica Fume and liquid carbon dioxide (CO2) are among them. In this study, silica fume and liquid carbon dioxide were used as a substitute for cement. The effect of the stiffness of the two materials and the earthquake lateral load was tested by looking at the response of the high-rise building. Through numerical simulations, we compare the mode shape, displacement of the structure, and the sheer force experienced by the structure.

Abstract: . The use of Ordinary Portland Cement (OPC) for building structures should be reduced because it can produce harmful CO₂ emissions. The use of environmentally friendly materials could be the solution. Liquid carbon dioxide (CO₂) is one of these material innovations. In this study, the liquid carbon dioxide was used as a substitute for OPC. The use of this material will affect the rigidity of the multi-story building structure. The effect of the stiffness variable value is tested by looking at the response of multy storey buildings during an earthquake. By using the finite difference method, the response of the multi-story building structure is analyzed through mode shape, structural displacement, and shear force.

Abstract: In order to obtain license renewal for RSG-GAS operation expired in 2020, an evaluation on periodic safety review (PSR) should be performed as required by BAPETEN regulation. This PSR had been done from 2005 to 2015. The objectives of the qualification review is to ensure that the critical structure, system, and component (SSC) for safety fulfils the requirements. SSC, which is important to safety, is reviewed in term of its environment, service frequency, aging mechanism, aging mitigation, and aging degradation detection. The results of this detection are evaluated to achieve sustainable and safe operation and to identify SSC replacement and repair before a failure occurs. From the evaluation results, it can be concluded that SSC qualification during the period of 2005 – 2015 still fulfils the requirements so that safe and sustainable operation of RSG-GAS is assured.

Abstract: The current work investigates the impact of MOX fuel introduction on AP1000 neutronic characteristics. The MCNP code with new silicon carbide cladding and the AP1000 core with three 235U enrichment zones (2.35%, 3.40%, and 4.45%) were used to perform the neutronic computations. The outcomes demonstrated that the simulated model for the AP1000 core complies with the optimization requirements as a Westing-house reference. The results which included: effective multiplication factor, k_eff, and excess reactivity were calculated and compared with the available published results. The k_eff in the cold zero power was found to be AP1000 Zircaloy, SiC, FeCrAl, and SS-310 cladding are (1.20685+/-0.00028), (1.21170+/-0.00028), (1.14435+/-0.00027), and (1.12432+/-0.00028). The excess reactivity is 17.11%, 17.47% 12,61%, and 11.06% with the MOX fuels, respectively. These numbers line up with the k_eff value of 1.205 given in the AP1000 Design Control Document for the UO2 fuel core. However, the results are positive and support the AP1000 reactor core's design and efficient modeling as being safe operation.

Abstract: This study aimed to design a condenser for a special application of condensing the vapor of pyrolysis process of hydrocarbon-based material such as plastic and biomass into liquid form or pyrolytic oil. Numerous condensers have been available in the market. However, a condenser cannot be selected and utilized directly for pyrolysis vapor condensation purposes. Before doing selection, the condenser must be designed first to meet the heat transfer requirements. In this work, the condenser was designed based on thermal analysis and validated with numerous published experimental data and the pyrolytic characteristics from related industry. A theoretical model is formulated for describing condensation of the pyrolysis vapor in the condenser to determine heat transfer requirement and the rate of condensation obtained. The effect of operating parameters such as cooling water rate in liters per minute (LPM) and temperature on the condensation rate was examined through an iterative procedure which rely to the heat transfer rate and the allowed pressure drop in the condenser. In this study, it was obtained that the highest cooling load is obtained when the flow rate of cooling water is 1.95 LPM. It was also obtained that the condenser effectiveness decreased of about 29.3 % with the ranges of cooling flow rate from 1.3 to 2.6 LPM

Abstract: Thermoelectric-based on Thermoelectric Generator (TEG) is a method of converting heat energy into electrical energy directly if there is a temperature difference (∆T) between the hot side temperature (Th) and the cold side temperature (Tc) of the TEG. Compared to conventional energy conversions such as steam turbines, this thermoelectric technology has no moving parts, is compact, quiet, highly reliable, environmentally friendly, and operated for long periods with minimal maintenance. This study aims to develop TEG technology as a means of converting heat energy from geothermal sources, especially those with medium and low temperatures (< 180 °C). The method used in this research is to conduct experiments to obtain the ideal TEG characteristics for use in medium and low temperature geothermal conditions. To achieve this goal, a characteristic test was conducted for five types of TEG with criteria including a maximum operating temperature of 200 °C. The parameters that measured in this experiment are temperature T, voltage V, current I and electric power P. Based on data, the results is TEG1-241-1.4-1.2 is the most optimal power that produce output power 6.5 Watt at 150 °C.

Abstract: Mukherjee and friends had written that the fermentation process of tempeh can increase the nutritional value, organoleptic properties, and digestibility of the product, as well as increase the bioavailability of proteins, carbohydrates, and lipids, in easily digestible sizes. Therefore, fermentation process needs more attention to produce best quality tempeh. In order to automate the industry process on making tempeh, the incubator for fermentation is designed to meet market needs so that it can be implemented by tempeh industry. The time required for the conventional tempeh fermentation process ranges from 24 hours to 40 hours and can be exacerbated by the transition season (uncertain temperature). The study aims to reduce human dependence on controlling temperature and humidity as well as shorten the time in the fermentation process and reduce failures in making tempeh by designing a tempeh incubator and applying the concept of the internet of things (IoT) using MCU32 Node and firebase as a real time database. To apply the IoT-based tempeh incubator, there are several discussions in this paper, namely control systems, temperature sensors, humidity sensors, android, Arduino Mega 2560 and IoT architecture. temperature and humidity sensors as leading devices that are in direct contact with real conditions using a DHT22 sensor which has 2 functions at once to read temperature and humidity then sent to Arduino Mega 2560 with C++ language as reference data to turn on/off (6 Fan 12 V Dc and 2 Spiral Heaters). This control process is configured fully automatically by the system. After going through the testing stages that the temperature and humidity control will work when the room temperature is below 31°C and above 33°C. From the results of testing the tempeh incubator, the average temperature is 31°C and humidity is 84.33% and the time required for tempeh fermentation is 20 hours, which is 4 hours faster than conventional process.

Abstract: Hydroponics is an agricultural cultivation system without using soil media. Hydroponics is an agricultural activity carried out using water as a medium to replace soil. Hydroponics emphasizes meeting the nutritional needs of plants through the flow of water. If nutrients are given through fertilizer in soil media, then in hydroponics, the nutrients are dissolved and flow through water. The concentration of nutrients that dissolve in water will affect the high and low pH of the water. The pH level in the water will affect the development and growth of plants. In addition, air humidity can also affect plant growth, especially for plants grown in a greenhouse. Therefore, special attention is needed to maintain the pH level in the water. The particular concern is when is the right time to replace the water or add nutrients to the water. However, the large land area and the limited number of workers owned by the partners make it difficult for them to monitor the development and growth of existing plants. Therefore, a sensor will be installed in the hydroponic system to monitor the plant's development and growth. Based on the results of the tests and evaluations, the three hydroponic monitoring sensors, which include the pH sensor, nutrient solution concentration sensor, and air humidity sensor, may be properly programmed on the Arduino. The measurements between sensors and manual measurements showed an error value of 0.36% for pH measurements, 0.56% for EC measurements, and 0.42% for humidity measurements.

Abstract: Beef and lamb each have a distinctive aroma. Classification of beef and lamb based on the aroma of the meat using an electronic nose. This electronic nose uses a series of sensors consisting of 6 (six) pieces and uses a Conducting Polymer. This polymer has a high resistance so it is widely used as an insulator. However, this resistance has a certain limit where the polymer surface will turn into carbon and conduct electric current if exposed to excessive electric charge. This research was conducted by taking samples of beef and lamb as test samples where these meats were placed in a closed container at room temperature. Data is taken alternately every day to find out the odor of each meat where on the first day data is taken from the odor of beef and on the second day data is taken from the odor of lamb. A two-layer neural network consisting of six input nodes and three output neurons is trained using the Kohonen algorithm with the training process completed in 31 iterations. The test was carried out 20 times for each exposure to steam from the odor of beef and lamb which was carried out alternately. The percentage of success of the system is reaching 90%.