A new practical method to evaluate the Joule-Thomson coefficient for natural gases

© 2017, The Author(s). The Joule–Thomson (JT) phenomenon, the study of fluid temperature changes for a given pressure change at constant enthalpy, has great technological and scientific importance for designing, maintenance and prediction of hydrocarbon production. The phenomenon serves vital role in many facets of hydrocarbon production, especially associated with reservoir management such as interpretation of temperature logs of production and injection well, identification of water and gas entry locations in multilayer production scenarios, modelling of thermal response of hydrocarbon reservoirs and prediction of wellbore flowing temperature profile. The purpose of this study is to develop a new method for the evaluation of JT coefficient, as an essential parameter required to account the Joule–Thomson effects while predicting the flowing temperature profile for gas production wells. To do this, a new correction factor, CNM, has been developed through numerical analysis and proposed a practical method to predict CNM which can simplify the prediction of flowing temperature for gas production wells while accounting the Joule–Thomson effect. The developed correlation and methodology were validated through an exhaustive survey which has been conducted with 20 different gas mixture samples. For each sample, the model has been run for a wide range of temperature and pressure conditions, and the model was rigorously verified by comparison of the results estimated throughout the study with the results obtained from HYSYS and Peng–Robinson equation of state. It is observed that model is very simple and robust yet can accurately predict the Joule–Thomson effect

Do Physicians Know When Their Diagnoses Are Correct?

This study explores the alignment between physicians' confidence in their diagnoses and the “correctness” of these diagnoses, as a function of clinical experience, and whether subjects were prone to over-or underconfidence. Design : Prospective, counterbalanced experimental design. Setting : Laboratory study conducted under controlled conditions at three academic medical centers. Participants : Seventy-two senior medical students, 72 senior medical residents, and 72 faculty internists. Intervention : We created highly detailed, 2-to 4-page synopses of 36 diagnostically challenging medical cases, each with a definitive correct diagnosis. Subjects generated a differential diagnosis for each of 9 assigned cases, and indicated their level of confidence in each diagnosis. Measurements And Main Results : A differential was considered “correct” if the clinically true diagnosis was listed in that subject's hypothesis list. To assess confidence, subjects rated the likelihood that they would, at the time they generated the differential, seek assistance in reaching a diagnosis. Subjects' confidence and correctness were “mildly” aligned (Κ=.314 for all subjects, .285 for faculty, .227 for residents, and .349 for students). Residents were overconfident in 41% of cases where their confidence and correctness were not aligned, whereas faculty were overconfident in 36% of such cases and students in 25%. Conclusions : Even experienced clinicians may be unaware of the correctness of their diagnoses at the time they make them. Medical decision support systems, and other interventions designed to reduce medical errors, cannot rely exclusively on clinicians' perceptions of their needs for such support.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74850/1/j.1525-1497.2005.30145.x.pd