The Accuracy Degree of CFD Turbulence Models for Butterfly Valve Flow Coefficient Prediction

Abstract Although engineers are mainly interested in the prediction of mean flow behavior, the turbulence cannot be ignored, because the fluctuations give rise to the extra Reynolds stresses on the mean flow. These extra stresses must be modeled in commercial CFD by selecting convenient turbulence model. The flow inside the control valve is complex and the control valves performance is precisely evaluated by determining the valve coefficient named, flow coefficient. Hence, aim of the present study is to investigate the effect of turbulence model type on the solution accuracy for the valve disk angles 40° and 60° as well as to implement the degree of agreement between experimental and numerical results. The numerical verification has been investigated by FLUENT 6.3 and the valve is meshed by GAMBIT 2. The mesh independent test has been carried out only by standard k-ε to evaluate the mesh effectiveness and attain the best accuracy. Among from these several turbulence models which have been studied here are standard k-ε, realized k-ε, k-ω, and RSM. Butterfly valve, STC model and (DN 50) diameter is chosen to be the test specimen in this research. The results showed that, there is no general turbulent model that can deal successfully with all cases. Numerical and experimental results are in general in good agreement, however are different in details, and showed that, RSM model is the most efficient numerical solver when applied to butterfly valve flow coefficient evaluation. For the future, a significant amount of work still needs to be undertaken in experimental unsteady butterfly valve flow analysis with RSM numerical model

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely