Atom Indonesia (E-Journal)
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Seismic Risk Analysis of the Serpong Nuclear Complex and the RSG-GAS Reactor Using Microseismic Methods
No full textThe G.A. Siwabessy research reactor (RSG-GAS), located in the Serpong Nuclear Complex (SNC), is a critical component of Indonesia's nuclear research infrastructure. This study aims to assess the seismic safety of the RSG-GAS reactor and its surrounding complex using microseismic methods, specifically the Horizontal-to-Vertical Spectral Ratio (HVSR) and Floor Spectral Ratio (FSR) techniques. HVSR measurements conducted across the B. J. Habibie Science and Technology Area (KST) revealed an average natural frequency (f₀) of 3.49 Hz (range: 2.84-4.43 Hz), amplification factors (A₀) averaging 2.84 (range: 2.11-4.88), and seismic susceptibility indices (Kg) averaging 2.72 (range: 1.34-4.39). The HK9 site, positioned 124 meters from the reactor, exhibited lower-than-average values, indicating reduced seismic vulnerability in the immediate reactor vicinity. FSR analysis was conducted to evaluate key structural parameters, including the Resonance Index (IR), inter-level deviation (γⱼ), peak ground acceleration (αbⱼ), and Building Vulnerability Index (Ktgⱼ). Most IR values fell within the medium-risk range (20.07 %-22.63 %), while one measurement point recorded 3.98 %, indicating high resonance risk. Inter-level deviations remained within acceptable safety thresholds; however, peak ground acceleration values exceeded critical limits at several levels, most notably at FU8 where 272.63 gal was recorded at -6.5 m elevation-significantly surpassing established safety standards. Several Building Vulnerability Index values also exceeded recommended safety limits. The findings demonstrate that while the RSG-GAS facility generally exhibits low-to-moderate seismic amplification and structural vulnerability, targeted structural reinforcements are essential at critical locations, particularly at the FU8 level. This study provides a comprehensive framework for enhancing seismic resilience of nuclear facilities in seismically active regions and contributes to the long-term safety assessment protocols for Indonesia's nuclear infrastructure
Preliminary Neutronic Studies on RSG-GAS Fuel Element with 4.8 grU/cc and Burnable Poison Wire for Reactivity Reduction
No full textHigh-density fuel can increase the operating cycle of a nuclear reactor. The G.A. Siwabessy Multipurpose Reactor (RSG-GAS) is a research reactor owned by Indonesia that currently uses 19.75 % enriched uranium silicide fuel (U3Si2-Al) with a uranium density of 2.965 grU/cc. Previous studies have shown that high-density fuel, 4.8 grU/cc, can be used in the RSG-GAS core to extend the operating cycle. Previous studies related to high-density fuel conversion scenarios included a temporary conversion process to a density of 3.55 grU/cc before being increased to 4.8 grU/cc. However, the previous conversion process requires the addition of control rods to suppress the excess reactivity of the RSG-GAS. The current study focuses on determining the configuration of burnable poison wire for the standard fuel element of RSG-GAS (FE) made of cadmium and hafnium to suppress the reactivity (k-inf) of the 4.8 grU/cc fuel element so it could have an initial reactivity closer to the 2.965 grU/cc fuel. 5 pairs of 0.4 mm diameter Cd-wire coated with 0.1 mm AlMg2 cladding can suppress the reactivity of the fuel assembly, while 7 pairs of 0.8 mm diameter Hf-wire without cladding could suppress reactivity longer. The temperature coefficient of reactivity for the moderator temperature (MTC) and fuel temperature (FTC) also becomes more negative in high-density FE RSG-GAS while the amount of Pu-239 produced increases in high-density fuel element
Brain Tumor Segmentation in MR Images Using Swin Transformer
No full textBrain tumors are abnormal tissue growths in the brain. These brain tumors can have a negative impact on human health, one of which can interfere with brain functions such as vision, balance, and so on. Therefore, early detection needs to be done, one of which is by using medical imaging modalities, i.e., MRI. However, analyzing MRI scans requires careful observation and a high level of proficiency. Thus, medical image segmentation is required. Segmentation is important in medical image analysis as it allows medical experts to distinguish between abnormal and normal tissues. This study aims to determine the ability of the swin transformer architecture in segmenting brain tumor MR images. The image data used was BraTS 2021 data with a total of 1,250 images. The data were divided into three, i.e., training set, validation set, and testing set with a ratio of 70:15:15. Swin Transformer provided two main concepts, i.e., hierarchical feature maps and attention window shifts. The Swin Transformer initially was divided the image into small patches, which were then converted into vector form. After that, it was passed through W-MSA for local area and SW-MSA for cross window area. Next, multiple patches were merged into one, so that the image resolution gradually decreased, and then restored back to the original resolution. Based on this, the segmentation results were evaluated using a confusion matrix using DSC, IoU, and sensitivity metrics. The results of brain tumors MR image segmentation with Swin Transformer obtained evaluation values, i.e., 0.97313 for DSC, 0.94767 for IoU, and 0.96450 for sensitivity. It can be concluded that the Swin Tranformer can effectively segment brain tumor MR images
Optimizing Quality Assurance in Breast IMRT Treatment Plans: A Comparative Study of Point Dose and 2D Dose Verification
No full textIntensity-Modulated Radiation Therapy (IMRT) requires rigorous dose verification to ensure accurate radiation delivery. This study evaluates point dose verification and 2D dose verification techniques in detecting dose discrepancies due to isocenter shifts in IMRT treatment for post-mastectomy breast cancer cases. Five post-mastectomy breast IMRT plans were retrospectively analyzed, with phantom-based measurements compared against Treatment Planning System (TPS) calculations. The results indicate that point dose verification provides reliable absolute dose measurements, but lacks spatial resolution, whereas 2D verification captures dose variations more effectively. Dose discrepancies remained within acceptable limits for shifts up to ±3 mm, but shifts of ±5 mm or more resulted in clinically significant deviations. Gamma Passing Rates (GPR) decreased substantially beyond ±5 mm shifts, underscoring the importance of precise patient positioning. These findings support the integration of both verification methods to improve IMRT quality assurance, particularly in resource-limited settings. Future advancements in AI-driven dosimetry and real-time in vivo monitoring may further optimize dose verification, enhancing treatment accuracy and patient safety
Brain Tumor Segmentation on MR and CT Images Using Fuzzy C-Means and Active Contour Methods
No full textA brain tumor is a dangerous brain disease that can attack anyone. It can be described as the abnormal growth of cells in or around the brain, leading to impaired brain function. The first step in diagnosing a brain tumor is to perform an MRI (Magnetic Resonance Imaging) scan. The research aims to analyze the segmentation results of brain tumor MRI and CT (Computed Tomography) images using the Fuzzy C-Means and Active Contour methods. The evaluation is based on ROC parameters, including accuracy, dice score, precision, and sensitivity. The methodology involves analyzing data from secondary image sources, using MATLAB for the segmentation process, and evaluating the results of image segmentation by radiologists. Four ROC measurements were used for each method. The segmentation evaluation results for MRI images show that the Fuzzy C-Means method achieved a precision of 0.92; sensitivity of 0.64; dice score of 0.76; and accuracy of 0.61. The Active Contour method, on the other hand, obtained a precision of 0.97; a sensitivity of 0.99; a dice score of 0.98; and an accuracy of 0.96. For CT images, the Fuzzy C-Means method yielded a precision of 0.72; sensitivity of 0.98; dice score of 0.83; and accuracy of 0.71. The Active Contour method obtained a precision of 0.96; a sensitivity of 0.95; a dice score of 0.96; and an accuracy of 0.92. These results indicate that the Active Contour method, especially with MRI images, provides better segmentation performance. In conclusion, the segmentation results from the Active Contour method can be used as additional information for doctors in diagnosing the presence of tumors
Determination of Typical Values for Pediatric Head CT Scan at Universitas Andalas Hospital
No full textThe utilization of X-rays in the Computed Tomography Scaner (CT scan) modality has proliferated for diagnostic purposes. CT scans deliver higher doses than other modalities, consequently protecting patients from excessive radiation doses is necessary by increasing optimization efforts in patients, especially pediatric patients. This research aims to determine the typical value and analyze the correlation of age, body mass, and exposure factor (mAs) to Computed Tomography Dose Index Volume (CTDIVol) and Dose Length Product (DLP). The typical dose value was obtained from the median value (Q2) using data derived from pediatric patients undergoing a head CT scan with a total of 33 patients at Universitas Andalas Hospital, with a correlation determined using a linearity test. The results obtained were the typical value for CTDIVol of 31.1 mGy and DLP of 793.3 mGy.cm. There is a moderate correlation between age and CTDIVol and DLP values, a high correlation between body mass and CTDIVol and DLP values, and a very high correlation between the exposure factor (mAs) and CTDIVol and DLP values
The Dependence of the Rupture Probability on the Mass Number of the Fissionable Nucleus
No full textThe relationship between the mass number of fissionable nuclei and fission yield is generally known through the fission barrier. The deformation energy of the SEMF determines the probability of the formation of fission products. The use of deformation energy is very impractical because it goes through many calculation stages. For this reason, the Neck Rupture Model was introduced, namely a model that shortens the stages of the calculation process through the rupture probability formula. In this paper, a new technique was introduced that adds the dependence of the rupture probability on the mass number of the nucleus that will undergo fission. Apart from this, this technique also obtained better fission yield calculation data compared to the previous technique. The fission yield calculations of Uranium isotopes at an energy of 14 MeV will be shown
Development of a Vietnamese PET/CT Dataset for Machine Learning-Based Analysis of Non-Small Cell Lung Cancer Images
No full textPositron Emission Tomography and Computed Tomography (PET/CT), a key imaging modality in nuclear medicine, Combines Anatomical (CT) and functional (PET) data for cancer diagnosis. Despite advancements in machine learning for automated medical image analysis, publicly available PET/CT datasets remain scarce, limiting Artificial Intelligence (AI) research compared to CT and MRI. This study built a publicly accessible PET/CT Vietnamese dataset for Non-Small Cell Lung Cancer (NSCLC). A total of 416 PET/CT scans were collected from three Vietnamese hospitals, including 300 NSCLC cases. Malignant FDG-sensitive lesions, identified via clinical PET/CT reports, were manually segmented in 3D (slice-by-slice) on PET images and validated by three experienced radiologists. The dataset includes both original and annotated DICOM files, along with clinical patient data. It achieved a dice similarity coefficient of 80.3 % and volume similarity of 81.9 %, demonstrating high segmentation accuracy comparable to other studies. This dataset supports AI-driven NSCLC research and contributes to global efforts in automated PET/CT analysis for nuclear medicine applications
Selection of Bacteria from Mamuju’s NORM as Uranium and Thorium Bioleaching Agents
No full textNatural materials that can cause increased radiation exposure to the surrounding environment are called Naturally Occurring Radioactive Materials (NORM). NORM contains uranium and thorium, critical elements with strategic and economic value. Conventional separation methods include chemical leaching and partial precipitation with strong acids and bases. These methods require large costs and produce waste harmful to the environment. This study explores bioleaching as an efficient and eco-friendly alternative to address these limitations. The indigenous bacteria used in bioleaching were isolated directly from NORM in Mamuju. This study aims to isolate, select, and evaluate bacteria from NORM as potential bioleaching agents. The methodology of this study includes NORM characterization, bacterial isolation and selection, molecular identification, and resistance testing of selected bacteria. The study successfully isolated eight bacterial strains from NORM, among which isolate L0A demonstrated the highest bioleaching potential. After five days of incubation, L0A achieved uranium and thorium concentrations of 2.508 mg/L and 10.5946 mg/L, respectively. Molecular identification revealed that L0A belongs to Bacillus sp. These findings demonstrate the potential of Bacillus sp. L0A is a bioleaching agent, paving the way for developing efficient, sustainable, and environmentally friendly methods for extracting valuable radioactive elements from NORM