인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
In response to the difficulty of measuring fluid pH values in high-acidity, high-pressure, hightemperature, and complex ion environments, this paper proposes a predictive model for in-situ pH values in high-acidity environments. The model considers the influences of eleven factors, including ORP potential, temperature, and pressure, and is capable of calculating the pH value of fluids incorporating the following factors: pressure, temperature, Na + ion concentration, K + ion concentration, Ca 2+ ion concentration, Mg 2+ ion concentration, Cl - ion concentration, HCO 3 - ion concentration, H 2 S concentration, CO 2 concentration, and ORP potential. Furthermore, the model is optimized to possess variable adaptability, allowing compatibility with cases involving fewer than eleven influencing factors. Test results demonstrate that the predictive model for in-situ pH values in high-acidity environments exhibits high precision, with a maximum prediction error of 6.32%, a minimum of 1.19%, and an average prediction error of 4%. Compared to other existing models, it considers a more comprehensive set of factors, providing a mathematical approach to pH prediction that holds significance for corrosion control in oil and gas pipeline industries.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.