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"Any events presumed to risk the safety of a nuclear reactor should be analyzed. In a research reactor, the applicability of best estimate thermal-hydraulic codes has been assessed for safety analysis purposes. In this paper, the applicability of the RELAP/SCDAPSIM/MOD3.4 thermal-hydraulic code to one Indonesian research reactor, which is named TRIGA-2000, is performed. The aim is to validate the model and use the model to analyze the thermal-hydraulic characteristics of TRIGA-2000 for main transient events considered in the Safety Analysis Report. The validation was done by comparing the calculation results with experimental data mainly in steady state conditions. The comparison of calculation results with the measurement data showed good agreement with little discrepancies. Based on these results, simulations for thermal-hydraulic analyses were performed for loss of coolant transients. The calculation results also properly depicted the physic of the thermal-hydraulic phenomena following the loss of coolant transients. These results showed the adequacy of the model. It could be shown that the engineered safety features of TRIGA-2000 play an important role in keeping the reactor safe from the risk of postulated loss of a coolant accident."

"Penelitian ini bertujuan untuk menganalisis hubungan perilaku berkendara dengan efektivitas radiator pada kendaraan dan mengembangkan aplikasi pemantau berbasis Android yang terintegrasi dengan Internet of Things (IoT). Dengan menggunakan ESP32 dan OBD-II untuk mendapatkan data suhu coolant dan posisi pedal akselerasi. Kemudian data tersebut dikirim dan disimpan di Firebase Cloud Server. Data tersebut kemudian ditampilkan pada aplikasi berbasis Android yang dibuat menggunakan Android Studio dan Flutter. Perhitungan Steinhart-Hart digunakan untuk mendapatkan nilai suhu dari thermistor yang digunakan untuk mendapatkan nilai efektivitas radiator. Pelepasan panas juga diperhitungkan untuk mengetahui kemampuan coolant dalam menyerap panas mesin. Pengujian menunjukkan bahwa perilaku berkendara sangat berpengaruh terhadap efektivitas radiator. Pada mode berkendara Eco, rata-rata efektivitas pendinginan mencapai 25,48%, dengan efektivitas terbaik sebesar 33,76% dan efektivitas terendah sebesar 15,75%. Mode berkendara Normal memiliki rata-rata efektivitas 20,72%, dengan efektivitas terbaik 29,51% dan terendah 11,67%. Sementara itu, mode Sport menunjukkan efektivitas terendah dengan rata-rata 14,62%, efektivitas terbaik 26,09%, dan terendah 7,91%. Kemudian melakukan verifikasi error menggunakan thermometer HABOTECH HT650c dan mendapatkan error sebesar 3,4% untuk Eco, 15,1% untuk Normal, dan 32,1% untuk Sport. Penyebab error tersebut dikarenakan perbedaan kalibrasi sensor OBD-II serta fluktuasi suhu yang cepat pada Normal dan Sport. Penelitian ini menyimpulkan bahwa perilaku berkendara Eco sangat direkomendasikan untuk penggunaan harian untuk menjaga umur mesin. Aplikasi dikembangan agar dapat mengurangi risiko overheating dan memantau efektivitas radiator secara real-time.

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This study aims to analyze the relationship between driving behavior and radiator effectiveness in vehicles and to develop an Android-based monitoring application integrated with the Internet of Things (IoT). Using ESP32 and OBD-II, data on coolant temperature and accelerator pedal position were collected, then transmitted and stored on Firebase Cloud Server. The data were subsequently displayed on an Android-based application developed using Android Studio and Flutter. The Steinhart-Hart calculation is used to determine the temperature value from the thermistor, which is utilized to obtain the radiator effectiveness. Heat dissipation is also considered to determine the coolant's ability to absorb engine heat. Testing revealed that driving behavior significantly affects the effectiveness of the radiator. In Eco mode, the average cooling effectiveness reached 25.48%, with a maximum effectiveness of 33.76% and a minimum of 15.75%. Normal mode had an average effectiveness of 20.72%, with a maximum of 29.51% and a minimum of 11.67%. Meanwhile, Sport mode showed the lowest effectiveness, averaging 14.62%, with a maximum of 26.09% and a minimum of 7.91%. Verification of errors was performed using the HABOTECH HT650c thermometer, resulting in errors of 3.4% for Eco, 15.1% for Normal, and 32.1% for Sport. These errors were attributed to differences in sensor calibration between the OBD-II and thermometer, as well as rapid temperature fluctuations in Normal and Sport modes. This study concludes that Eco driving behavior is highly recommended for daily use to help extend engine life. The application was developed to reduce the risk of overheating and to monitor radiator effectiveness in real-time."