A parametric evaluation of the interplay between geometry and scale on cross-flow turbine performance

Cross-flow turbines harness kinetic energy in wind or moving water. Due to their unsteady fluid dynamics, it can be difficult to predict the interplay between aspects of rotor geometry and turbine performance. This study considers the effects of three geometric parameters: the number of blades, the preset pitch angle, and the chord-to-radius ratio. The relevant fluid dynamics of cross-flow turbines are reviewed, as are prior experimental studies that have investigated these parameters in a more limited manner. Here, 223 unique experiments are conducted across an order of magnitude of diameter-based Reynolds numbers ($\approx 8\!\times\!10^4 - 8\!\times\!10^5$) in which the performance implications of these three geometric parameters are evaluated. In agreement with prior work, maximum performance is generally observed to increase with Reynolds number and decrease with blade count. The broader experimental space identifies new parametric interdependencies; for example, the optimal preset pitch angle is increasingly negative as the chord-to-radius ratio increases. Because these experiments vary both the chord-to-radius ratio and blade count, the performance of different rotor geometries with the same solidity (the ratio of total blade chord to rotor circumference) can also be evaluated. Results demonstrate that while solidity can be a poor predictor of maximum performance, across all scales and tested geometries it is an excellent predictor of the tip-speed ratio corresponding to maximum performance. Overall, these results present a uniquely holistic view of relevant geometric considerations for cross-flow turbine rotor design and provide a rich dataset for validation of numerical simulations and reduced-order models.Comment: SUBMITTED to Renewable and Sustainable Energy Review

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Optimization, Modeling, and Control of Cross-Flow Turbine Arrays

Thesis (Ph.D.)--University of Washington, 2022The ability to understand unsteady fluid flows is foundational to advancing technologies in energy, health, transportation, and defense. This work uses data-driven methods (i.e., machine learning) to interpret and control unsteady fluid flows through experiments. Specifically, these methods are used to control, optimize, and model cross-flow turbines. Cross-flow turbines (i.e. vertical axis turbines), are devices that can be used to convert the kinetic energy in wind to electricity. A key advantage of cross-flow turbines over axial-flow turbines is that they can efficiently operate in close-proximity in arrays. We demonstrate how data-driven methods can be used to efficiently explore, model, and interpret the high-dimensional space cross-flow turbine dynamics occupy through the following three projects. First, robust principal component analysis (RPCA), a method borrowed from robust statistics, is used to improve flow-field data by leveraging global coherent structures to identify and replace spurious data points. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. We demonstrate that more persistent dynamics can be identified when RPCA is utilized in lieu of traditional processing methods. In all cases, both simulated and experimental, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. Second, the performance of a two-turbine array in a recirculating water channel was experimentally optimized across 64 unique array configurations using a hardware-in-the-loop approach. For each configuration, turbine performance was optimized using tip-speed ratio control, where the rotation rate for each turbine is optimized individually, and using coordinated control, where the turbines are optimized to operate at synchronous rotation rates but with a phase difference. For each configuration and control strategy, the consequences of co- and counter-rotation were also evaluated. Arrays with well-considered geometries and control strategies are found to outperform isolated turbines by up to 30%. Third, the performance and wake of a two-turbine array in a fence configuration (side-by-side) are characterized. The turbines are operated under coordinated control. Measurements were made with turbines co-rotating, counter-rotating with the blades advancing upstream at the array midline, and counter-rotating with the blades retreating downstream at the array midline. From the performance and wake data, we found individual turbine and array efficiency to depend significantly on rotation direction and phase difference. Persistent dynamics that exist across all flow fields, as well as differences between cases are identified. Each of these projects demonstrate how data-driven methods can be used to explore, model, and interpret cross-flow turbine dynamics and other fluid systems

Experimental data from "A parametric evaluation of the interplay between geometry and scale on cross-flow turbine performance"

The provided MATLAB file contains data from 223 cross-flow turbine experiments conducted at the University of Washington and University of New Hampshire, which are described in detail in "A parametric evaluation of the interplay between geometry and scale on cross-flow turbine performance" by Hunt et al. The "data" struct in the provided file includes time-average and phase-median performance, rotor geometry specifications, and flow properties for each experiment. The "comments" struct describes each field of the "data" struct in detail. Please contact Aidan Hunt at [email protected] or Brian Polagye at [email protected] if you have questions about the data.This data was collected with support from the U.S. Navy's Naval Facilities Engineering and Systems Command (NAVFAC) under N0002410D6318 / N0002418F8702

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous