Luca Bernardini, Mark O. McLinden, Xiaoxian Yang, Markus Richter
{"title":"您的实验数据有多准确?基于 GUM 的不确定性评估方法更易于使用","authors":"Luca Bernardini, Mark O. McLinden, Xiaoxian Yang, Markus Richter","doi":"10.1007/s10765-024-03446-9","DOIUrl":null,"url":null,"abstract":"<div><p>A methodology for evaluating experimental uncertainty is presented. Based on the Guide to the Expression of Uncertainty in Measurement (GUM) in conjunction with a sensitivity analysis, this method readily applies to systems of various degrees of complexity. It consists of three steps: (1) to estimate each uncertainty contribution of the system based on GUM; (2) to determine the sensitivity of the calculated results to variations in each of the input measurands in turn, replacing the partial derivatives of the GUM with a purely numerical approach; and (3) to calculate the overall uncertainty using the error propagation principle. Furthermore, the calculated sensitivity coefficients enable a critical evaluation of the investigated system, allowing the detection of possible targeted improvements. For this reason, the presented method is called “the sensitivity analysis method.” This is applied to three case studies with increasing complexity: a mass calibration procedure, a volume calibration procedure, and a gravimetric densimeter characterized by a multi-parameter nonlinear measuring model. When possible, the results are compared to the GUM uncertainty framework or values available in the literature.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"45 11","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10765-024-03446-9.pdf","citationCount":"0","resultStr":"{\"title\":\"How Accurate are Your Experimental Data? A More Accessible GUM-Based Methodology for Uncertainty Evaluation\",\"authors\":\"Luca Bernardini, Mark O. McLinden, Xiaoxian Yang, Markus Richter\",\"doi\":\"10.1007/s10765-024-03446-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A methodology for evaluating experimental uncertainty is presented. Based on the Guide to the Expression of Uncertainty in Measurement (GUM) in conjunction with a sensitivity analysis, this method readily applies to systems of various degrees of complexity. It consists of three steps: (1) to estimate each uncertainty contribution of the system based on GUM; (2) to determine the sensitivity of the calculated results to variations in each of the input measurands in turn, replacing the partial derivatives of the GUM with a purely numerical approach; and (3) to calculate the overall uncertainty using the error propagation principle. Furthermore, the calculated sensitivity coefficients enable a critical evaluation of the investigated system, allowing the detection of possible targeted improvements. For this reason, the presented method is called “the sensitivity analysis method.” This is applied to three case studies with increasing complexity: a mass calibration procedure, a volume calibration procedure, and a gravimetric densimeter characterized by a multi-parameter nonlinear measuring model. When possible, the results are compared to the GUM uncertainty framework or values available in the literature.</p></div>\",\"PeriodicalId\":598,\"journal\":{\"name\":\"International Journal of Thermophysics\",\"volume\":\"45 11\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10765-024-03446-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Thermophysics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10765-024-03446-9\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Thermophysics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10765-024-03446-9","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
How Accurate are Your Experimental Data? A More Accessible GUM-Based Methodology for Uncertainty Evaluation
A methodology for evaluating experimental uncertainty is presented. Based on the Guide to the Expression of Uncertainty in Measurement (GUM) in conjunction with a sensitivity analysis, this method readily applies to systems of various degrees of complexity. It consists of three steps: (1) to estimate each uncertainty contribution of the system based on GUM; (2) to determine the sensitivity of the calculated results to variations in each of the input measurands in turn, replacing the partial derivatives of the GUM with a purely numerical approach; and (3) to calculate the overall uncertainty using the error propagation principle. Furthermore, the calculated sensitivity coefficients enable a critical evaluation of the investigated system, allowing the detection of possible targeted improvements. For this reason, the presented method is called “the sensitivity analysis method.” This is applied to three case studies with increasing complexity: a mass calibration procedure, a volume calibration procedure, and a gravimetric densimeter characterized by a multi-parameter nonlinear measuring model. When possible, the results are compared to the GUM uncertainty framework or values available in the literature.
期刊介绍:
International Journal of Thermophysics serves as an international medium for the publication of papers in thermophysics, assisting both generators and users of thermophysical properties data. This distinguished journal publishes both experimental and theoretical papers on thermophysical properties of matter in the liquid, gaseous, and solid states (including soft matter, biofluids, and nano- and bio-materials), on instrumentation and techniques leading to their measurement, and on computer studies of model and related systems. Studies in all ranges of temperature, pressure, wavelength, and other relevant variables are included.