Medidas de fração de vazio em escoamentos bifásicos por transmissão e difusão de nêutrons

Foram obtidas curvas de calibração que fornecem valores médios de fração de vazio (a), para misturas bifásicas de agua-vapor, para os regimes de escoamento a bolhas, bolsões ("slug"), anular e anular inverso. As medidas foram realizadas em modelos simulados de lucite-ar, para escoamento estacionário, pelas técnicas da transmissão e difusão de nêutrons térrmicos. As curvas de calibração obtidas foram utilizadas para medidas de fração de vazio em um circuito contendo mistura bifásica de água-ar, em escoamento concorrente ascendente, para os regimes a bolsões (pmax =1,06 bar) e anular (Pmax =1.33 bar), pelas mesmas técnicas anteriores. Em ambos os sistemas, utilizou-se uma seção de testes constituída de tubulação de alumínio (99,9%), com diâmetro interno de 25,25 mm e 2,00 mm de espessura de parede. O feixe de nêutrons foi obtido de uma fonte isotópica do tipo Am-8e, de 5 Cl, termalizados em uma blindagem cilíndrica de parafina de 500 mm de diâmetro (com H/D=l), recoberta com folhas de cadmio de 2 mm, tendo em seu interior um paralelepípedo de polietileno de alta densidade com dimensões de 240 x 240 x 144mm. Os nêutrons escapavam através de um colimador quadrangular paralelo de 53,00 x 25,25 mm, com 273 mm de comprimento, cavado em uma peça de parafina borada (32X de H3BO3). As medidas experimentais apresentaram boa concordância com os modelos teóricos da literatura especializada

Power loss of the chain drive in a race tandem bicycle

Tandem cycling is a paralympic discipline, in which two cyclists ride on one tandem bicycle. Their performance can be improved by minimizing power losses. This study aimed to quantify power loss due to the chain drive of a tandem bicycle and influence of power input, location of power input, and rear chain wheel size. Power loss was determined by the difference between power input applied on the cranks (front or back rider) and power output measured at the rear wheel. Power output values were set from 100 to 400 W, with 50 W increments, and using two gear ratios, 53-11 and 53-13. Power input was generated at the back crank (with only the primary chain—solo bicycle—and with primary and secondary chain attached) and at the front crank (with primary and secondary chain attached). The power loss for the solo bicycle was 2.1% (± 1.5%). A significantly larger power loss was found for the tandem in the back (3.7 ± 2.4%, p &lt; 0.001) and front positions (3.0 ± 1.8%, p &lt; 0.001), with marginal differences between positions at higher power output. Power loss for the tandem was lower with gear 53-13 (2.9% ± 1.7%) compared to 53-11 (4.0 ± 2.8%, p &lt; 0.001, effect size is medium). Therefore, findings suggest that back and front riders experience similar power losses due to the chain drive, but more than on a solo bicycle. Tandem cyclists can reduce their power loss in the chain drive by selecting larger gear ratios. Coaches may consider these findings for selecting and coaching their tandem cyclists.</p

Modeling Match Performance in Elite Volleyball Players: Importance of Jump Load and Strength Training Characteristics

In this study, we investigated the relationships between training load, perceived wellness and match performance in professional volleyball by applying the machine learning techniques XGBoost, random forest regression and subgroup discovery. Physical load data were obtained by manually logging all physical activities and using wearable sensors. Daily wellness of players was monitored using questionnaires. Match performance was derived from annotated actions by a video scout during matches. We identified conditions of predictor variables that related to attack and pass performance (p < 0.05). Better attack performance is related to heavy weights of lower-body strength training exercises in the preceding four weeks. However, worse attack performance is linked to large variations in weights of full-body strength training exercises, excessively heavy upper-body strength training, low jump heights and small variations in the number of high jumps in the four weeks prior to competition. Lower passing performance was associated with small variations in the number of high jumps in the preceding week and an excessive amount of high jumps performed, on average, in the two weeks prior to competition. Differences in findings with respect to passing and attack performance suggest that elite volleyball players can improve their performance if training schedules are adapted to the position of a player

Modeling match performance in elite volleyball players : importance of jump load and strength training characteristics

In this study, we investigated the relationships between training load, perceived wellness and match performance in professional volleyball by applying the machine learning techniques XGBoost, random forest regression and subgroup discovery. Physical load data were obtained by manually logging all physical activities and using wearable sensors. Daily wellness of players was monitored using questionnaires. Match performance was derived from annotated actions by a video scout during matches. We identified conditions of predictor variables that related to attack and pass performance (p < 0.05). Better attack performance is related to heavy weights of lower-body strength training exercises in the preceding four weeks. However, worse attack performance is linked to large variations in weights of full-body strength training exercises, excessively heavy upper-body strength training, low jump heights and small variations in the number of high jumps in the four weeks prior to competition. Lower passing performance was associated with small variations in the number of high jumps in the preceding week and an excessive amount of high jumps performed, on average, in the two weeks prior to competition. Differences in findings with respect to passing and attack performance suggest that elite volleyball players can improve their performance if training schedules are adapted to the position of a player

Validity and Reliability of Facial Rating of Perceived Exertion Scales for Training Load Monitoring

van der Zwaard, S, Hooft Graafland, F, van Middelkoop, C, and Lintmeijer, LL. Validity and reliability of facial rating of perceived exertion scales for training load monitoring. J Strength Cond Res XX(X): 000-000, 2022-Rating of perceived exertion (RPE) is often used by coaches and athletes to indicate exercise intensity, which facilitates training load monitoring and prescription. Although RPE is typically measured using the Borg's category-ratio 10-point scale (CR10), digital sports platforms have recently started to incorporate facial RPE scales, which potentially have a better user experience. The aim of this study was to evaluate the validity and reliability of a 5-point facial RPE scale (FCR5) and a 10-point facial RPE scale (FCR10), using the CR10 as a golden standard and to assess their use for training load monitoring. Forty-nine subjects were grouped into 17 untrained (UT), 19 recreationally trained (RT), and 13 trained (T) individuals Subjects completed 9 randomly ordered home-based workout sessions (3 intensities × 3 RPE scales) on the Fitchannel.com platform. Heart rate was monitored throughout the workouts. Subjects performed 3 additional workouts to assess reliability. Validity and reliability of both facial RPE scales were low in UT subjects (intraclass correlation [ICC] ≤ 0.44, p ≤ 0.06 and ICC ≤ 0.43, p ≥ 0.09). In RT and T subjects, validity was moderate for FCR5 (ICC ≥ 0.72, p < 0.001) and good for FCR10 (ICC ≥ 0.80, p < 0.001). Reliability for these groups was rather poor for FCR5 (ICC = 0.51, p = 0.006) and moderate for FCR10 (ICC = 0.74, p < 0.001), but it was excellent for CR10 (ICC = 0.92, p < 0.001). In RT and T subjects, session RPE scores were also strongly related to Edward's training impulse scores (r ≥ 0.70, p < 0.001). User experience was best supported by the FCR10 scale. In conclusion, researchers, coaches, strength and conditioning professionals, and digital sports platforms are encouraged to incorporate the valid and reliable FCR10 and not FCR5 to assess perceived exertion and internal training load of recreationally trained and trained individuals

Personalized machine learning approach to injury monitoring in elite volleyball players

ABSTRACTWe implemented a machine learning approach to investigate individual indicators of training load and wellness that may predict the emergence or development of overuse injuries in professional volleyball. In this retrospective study, we collected data of 14 elite volleyball players (mean ± SD age: 27 ± 3 years, weight: 90.5 ± 6.3 kg, height: 1.97 ± 0.07 m) during 24 weeks of the 2018 international season. Physical load was tracked by manually logging the performed physical activities and by capturing the jump load using wearable devices. On a daily basis, the athletes answered questions about their wellness, and overuse complaints were monitored via the Oslo Sports Trauma Research Center (OSTRC) questionnaire. Based on training load and wellness indicators, we identified subgroups of days with increased injury risk for each volleyball player using the machine learning technique Subgroup Discovery. For most players and facets of overuse injuries (such as reduced sports participation), we have identified personalized training load and wellness variables that are significantly related to overuse issues. We demonstrate that the emergence and development of overuse injuries can be better understood using daily monitoring, taking into account interactions between training load and wellness indicators, and by applying a personalized approach.Highlights With detailed, athlete-specific monitoring of overuse complaints and training load, practical insights in the development of overuse injuries can be obtained in a player-specific fashion contributing to injury prevention in sports.A multi-dimensional and personalized approach that includes interactions between training load variables significantly increases the understanding of overuse issues on a personal basis.Jump load is an important predictor for overuse injuries in volleyball

Effect of vasti morphology on peak sprint cycling power of a human musculoskeletal simulation model

Fascicle length of m. vastus lateralis in cyclists has been shown to correlate positively with peak sprint cycling power normalized for lean body mass. We investigated whether vasti morphology affects sprint cycling power via force-length and force-velocity relationships. We simulated isokinetic sprint cycling at pedaling rates ranging from 40 to 150 rpm with a forward dynamic model of the human musculoskeletal system actuated by eight leg muscles. Input of the model was muscle stimulation over time, which was optimized to maximize the average power output over a pedal cycle. This was done for a reference model and for models in which the vasti had equal volume but different morphology. It was found that models with longer muscle fibers but a reduced physiological cross-sectional area of the vasti produced a higher sprint cycling power. This was partly explained by better alignment of the peak power-pedaling rate curve of the vasti with the corresponding curves of the other leg muscles. The highest sprint cycling power was achieved in a model in which the increase in muscle fiber length of the vasti was accompanied by a concomitant shift in optimum knee angle. It was concluded that muscle mechanics can partly explain the positive correlations between fascicle length of m. vastus lateralis and normalized peak sprint cycling power. It should be investigated whether muscle fiber length of the vasti and optimum knee angle are suitable training targets for athletes who want to concurrently improve their sprint and endurance cycling performance.NEW & NOTEWORTHY We simulated isokinetic sprint cycling at pedaling rates ranging from 40 to 150 rpm with a forward dynamic model of the human musculoskeletal system actuated by eight leg muscles. We selectively modified vasti morphology: we lengthened the muscle fibers and reduced the physiological cross-sectional area. The modified model was able to produce a higher sprint cycling power