The primary objective of this study is to evaluate a systematic design’s effectivity in remediating actual uranium-contaminated soil. The emphasis was placed on practical and engineering aspects, particularly in assessing the capabilities of a zero liquid discharge system in treating wastewater derived from soil washing. The research method involved a purification procedure for both the uranium-contaminated soil and its accompanying wastewater. Notably, the experimental outcomes demonstrated successful uranium separation from the contaminated soil. The treated soil could be self-disposed of, as its uranium concentration fell below 1.0 Bq·g−1, a level endorsed by the International Atomic Energy Agency for radionuclide clearance. The zero liquid discharge system’s significance lay in its distillation process, which not only facilitated the reuse of water from the separated filtrate but also allowed for the self-disposal of high-purity Na2SO4 within the residues of the distilled filtrate. Through a comparative economic analysis involving direct disposal and the application of a remediation process for uranium-contaminated soil, the comprehensive zero liquid discharge system emerged as a practical and viable choice. The successful demonstration of the design and practicality of the proposed zero liquid discharge system for treating wastewater originating from real uranium-contaminated soil is poised to have a lasting impact.

Radioactive waste can be classified according to the concentration level for radionuclides, and the disposal method is different through the level. Gamma analysis is inevitably performed to determine the concentration of radioactive waste, and when a large amount of radioactive waste is generated, such as decommissioning nuclear facilities, it takes a lot of time to analyze samples. The performance of a lot of analysis can cause human errors and workload. In general, gamma analysis is performed using by HPGe detector. Recently, for convenience of analysis, commercial automatic sample changers applicable to the HPGe detectors were developed. The automatic sample changers generate individual analysis reports for each sample. In this study, gamma analysis procedure was improved using the application of the automatic sample changer and the automated data parsing using by Python. The application of automatic sample changers and data parsing technique can solve the problems. The human errors were reduced to 0% compared to the previous method by improving the gamma analysis procedure, and working time were also dramatically reduced. This automation of analysis procedure will contribute to reducing the burden of analysis work and reducing human errors through various improvements.