197 resultados para Critical power intensity
em University of Queensland eSpace - Australia
Resumo:
Few studies have focused on the metabolic responses to alternating high- and low-intensity exercise and, specifically, compared these responses to those seen during constant-load exercise performed at the same average power output. This study compared muscle metabolic responses between two patterns of exercise during which the intensity was either constant and just below critical power (CP) or that oscillated above and below CP. Six trained males (mean +/- SD age 23.6 +/- 2.6 y) completed two 30-minute bouts of cycling (alternating and constant) at an average intensity equal to 90% of CR The intensity during alternating exercise varied between 158% CP and 73% CP. Biopsy samples from the vastus lateralis muscle were taken before (PRE), at the midpoint and end (POST) of exercise and analysed for glycogen, lactate, PCr and pH. Although these metabolic variables in muscle changed significantly during both patterns of exercise, there were no significant differences (p > 0.05) between constant and alternating exercise for glycogen (PRE: 418.8 +/- 85 vs. 444.3 +/- 70; POST: 220.5 +/- 59 vs. 259.5 +/- 126mmol.kg(-1) dw), lactate (PRE: 8.5 +/- 7.7 vs. 8.5 +/- 8.3; POST: 49.9 +/- 19.0 vs. 42.6 +/- 26.6 mmol.kg(-1)dw), phosphocreatine (PRE: 77.9 +/- 11.6 vs. 75.7 +/- 16.9; POST: 65.8 +/- 12.1 vs. 61.2 +/- 12.7mmol.kg(-1)dw) or pH (PRE: 6.99 +/- 0.12 vs. 6.99 +/- 0.08; POST: 6.86 +/- 0.13 vs. 6.85 +/- 0.06), respectively. There were also no significant differences in blood lactate responses to the two patterns of exercise. These data suggest that, when the average power output is similar, large variations in exercise intensity exert no significant effect on muscle metabolism.
Resumo:
The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.
Resumo:
The standard critical power test protocol on the cycle prescribes a series of trials to exhaustion, each at a different but constant power setting. Recently the protocol has been modified and applied to a series of trials to exhaustion each at a different ramp incremental rate. This study was undertaken to compare critical power and anaerobic work capacity estimates in the same group of subjects when derived from the two protocols. Ten male subjects of mixed athletic ability cycled to exhaustion on eight occasions in randomized order over a 3-wk period. Four trials were performed at differing constant power settings and four trials on differing ramp incremental rates. Both critical power and anaerobic work capacity were estimated for each subject by curve fitting of the ramp model and of three versions of the constant power model. After adjusting for inter-subject variability, no significant differences were detected between critical power estimates or between anaerobic work capacity estimates from any model formulation or from the two protocols. It is concluded that both the ramp and constant power protocols produce equivalent estimates for critical power and anaerobic work capacity.
Resumo:
This study examined the effects of four high-intensity interval-training (HIT) sessions performed over 2 weeks on peak volume of oxygen uptake (VO2peak), the first and second ventilatory thresholds (UT VT2) and peak power output (PPO) in highly trained cyclists. Fourteen highly trained male cyclists (VO2peak = 67.5 +/- 3.7 ml . kg(-1) . min(-1)) performed a ramped cycle test to determine VO2peak VT1 VT2, and PPO. Subjects were divided equally into a HIT group and a control group. The HIT group performed four HIT sessions (20 x 60 s at PPO, 120 s recovery); the V-02peak test was repeated <I wk after the HIT program. Control subjects maintained their regular training program and were reassessed under the same timeline. There was no change in V0(2peak) for either group; however, the HIT group showed a significantly greater increase in VT1, (+22% vs. -3%), VT2 (+15% vs. -1%), and PPO (+4.3 vs. -.4%) compared to controls (all P <.05). This study has demonstrated that HIT can improve VT1, VT2,, and PPO, following only four HIT sessions in already highly trained cyclists.
Resumo:
Six men were studied during four 30-s all-out exercise bouts on an air-braked cycle ergometer. The first three exercise bouts were separated by 4 min of passive recovery; after the third bout, subjects rested for 4 min, exercised for 30 min at 30-35% peak O-2 consumption, and rested for a further 60 min before completing the fourth exercise bout. Peak power and total work were reduced (P < 0.05) during bout 3 [765 +/- 60 (SE) W; 15.8 +/- 1.0 kJ] compared with bout 1 (1,168 +/- 55 mT, 23.8 +/- 1.2 kJ), but no difference in exercise performance was observed between bouts 1 and 4 (1,094 +/- 64 W, 23.2 +/- 1.4 kJ). Before bout 3, muscle ATP, creatine phosphate (CP), glycogen, pH, and sarcoplasmic reticulum (SR) Ca2+ uptake were reduced, while muscle lactate and inosine 5'-monophosphate were increased. Muscle ATP and glycogen before bout 4 remained lower than values before bout I (P < 0.05), but there were no differences in muscle inosine 5'-monophosphate, lactate, pH, and SR Ca2+ uptake. Muscle CP levels before bout 4 had increased above resting levels. Consistent with the decline in muscle ATP were increases in hypoxanthine and inosine before bouts 3 and 4. The decline in exercise performance does not appear to be related to a reduction in muscle glycogen. Instead, it may be caused by reduced CP availability, increased H+ concentration, impairment in SR function, or some other fatigue-inducing agent.
Resumo:
In order to effectively suppress the noise radiation from large electrical power transformers, both the structure-borne and air-borne sound fields need to be characterised. The characterisation can be made either from theoretical predictions or by in-situ measurements. This paper presents the study of the sound radiation from a large power transformer in a substation. The radiation pattern can be predicted from the measured acceleration distribution and the predicted value is not affected by other noise sources. Alternatively, the farfield sound pressure level can be predicted from the sound pressure level measured at NEMA locations. Both the near- and far-field power radiation can be in-situ measured using the sound intensity technique. It is shown that both the vibration of a transformer tank wall and the radiated noise consist of a series of tonal components mainly at the first few harmonic frequencies of 100 Hz. Also, the neglect of the noise radiation from the transformer (top and bottom) lids does not affects the accuracy of the transformer radiation characterisation. (C) 1998 Elsevier Science Ltd. All rights reserved.
Resumo:
We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.
Resumo:
The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.
Resumo:
Crushing and grinding are the most energy intensive part of the mineral recovery process. A major part of rock size reduction occurs in tumbling mills. Empirical models for the power draw of tumbling mills do not consider the effect of lifters. Discrete element modelling was used to investigate the effect of lifter condition on the power draw of tumbling mill. Results obtained with PFC3D code show that lifter condition will have a significant influence on the power draw and on the mode of energy consumption in the mill. Relatively high lifters will consume less power than low lifters, under otherwise identical conditions. The fraction of the power that will be consumed as friction will increase as the height of the lifters decreases. This will result in less power being used for high intensity comminution caused by the impacts. The fraction of the power that will be used to overcome frictional resistance is determined by the material's coefficient of friction. Based on the modelled results, it appears that the effective coefficient of friction for in situ mill is close to 0.1. (C) 2003 Elsevier Science Ltd. All rights reserved.
Resumo:
The power required to operate large mills is typically 5-10 MW. Hence, optimisation of power consumption will have a significant impact on overall economic performance and environmental impact. Power draw modelling results using the discrete element code PFC3D have been compared with results derived from the widely used empirical Model of Morrell. This is achieved by calculating the power draw for a range of operating conditions for constant mill size and fill factor using two modelling approaches. fThe discrete element modelling results show that, apart from density, selection of the appropriate material damping ratio is critical for the accuracy of modelling of the mill power draw. The relative insensitivity of the power draw to the material stiffness allows selection of moderate stiffness values, which result in acceptable computation time. The results obtained confirm that modelling of the power draw for a vertical slice of the mill, of thickness 20% of the mill length, is a reliable substitute for modelling the full mill. The power draw predictions from PFC3D show good agreement with those obtained using the empirical model. Due to its inherent flexibility, power draw modelling using PFC3D appears to be a viable and attractive alternative to empirical models where necessary code and computer power are available.
Resumo:
The aim of this study was to compare the effects of two high-intensity, treadmill interval-training programs on 3000-m and 5000-m running performance. Maximal oxygen uptake ((V) over dot O-2max), the running speed associated with (V) over dot O-2max (nu (V) over dot O-2max), the time for which nu (V) over dot O-2max can be maintained (T-max), running economy (RE), ventilatory threshold (VT) and 3000-m and 5000-m running times were determined in 27 well-trained runners. Subjects were then randomly assigned to three groups; (1) 60% T-max (2) 70% T-max and (3) control. Subjects in the control group continued their normal training and subjects in the two T-max groups undertook a 4-week treadmill interval-training program with the intensity set at nu (V) over dot O-2max and the interval duration at the assigned T-max. These subjects completed two interval-training sessions per week (60% T-max = six intervals/session, 70% T-max group = five intervals/session). Subjects were re-tested on all parameters at the completion of the training program. There was a significant improvement between pre- and post-training values in 3000-m time trial (TT) performance in the 60% T-max group compared to the 70% T,,a, and control groups [mean (SE); 60% T-max = 17.6 (3.5) s, 70% T-max = 6.3 (4.2) s, control = 0.5 (7.7) s]. There was no significant effect of the training program on 5000-m TT performance [60% T-max = 25.8 (13.8) s, 70% T-max = 3.7 (11.6) s, control = 9.9 (13.1) s]. Although there were no significant improvements in (V) over dot O-2max, nu (V) over dot (2max) and RE between groups, changes in (V) over dot O-2max and RE were significantly correlated with the improvement in the 3000-m TT. Furthermore, VT and T-max were significantly higher in the 60% Tmax group post-compared to pre-training. In conclusion, 3000-m running performance can be significantly improved in a group of well-trained runners, using a 4-week treadmill interval training program at nu (V) over dot O-2max with interval durations of 60% T-max.
Resumo:
The present study aimed to 1) examine the relationship between laboratory-based measures and high-intensity ultraendurance (HIU) performance during an intermittent 24-h relay ultraendurance mountain bike race (similar to20 min cycling, similar to60min recovery), and 2) examine physiological and performance based changes throughout the HIU event. Prior to the HIU event, four highly-trained male cyclists (age = 24.0 +/- 2.1 yr; mass = 75.0 +/- 2.7 kg; (V)over dot O-2peak = 70 +/- 3 ml.kg(-1).min(-1)) performed 1) a progressive exercise test to determine peak Volume of oxygen uptake ((V)over dot O-2peak), peak power output (PPO), and ventilatory threshold (T-vent), 2) time-to-fatigue tests at 100% (TF100) and 150% of PPO (TF150), and 3) a laboratory simulated 40-km time trial (TT40). Blood lactate (Lac(-)), haematocrit and haemoglobin were measured at 6-h intervals throughout the HIU event, while heart rate (HR) was recorded continuously. Intermittent HIU performance, performance HR, recovery HR, and Lac declined (P < 0.05), while plasma volume expanded (P < 0.05) during the HIU event. TF100 was related to the decline in lap time (r = -0.96; P < 0.05), and a trend (P = 0.081) was found between TF150 and average intermittent HIU speed (r = 0.92). However, other measures (V)over dot O-2peak, PPO, T-vent, and TT40) were not related to HIU performance. Measures of high-intensity endurance performance (TF100, TF150) were better predictors of intermittent HIU performance than traditional laboratory-based measures of aerobic capacity.
Resumo:
Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.
Resumo:
The power required to operate large gyratory mills often exceeds 10 MW. Hence, optimisation of the power consumption will have a significant impact on the overall economic performance and environmental impact of the mineral processing plant. In most of the published models of tumbling mills (e.g. [Morrell, S., 1996. Power draw of wet tumbling mills and its relationship to charge dynamics, Part 2: An empirical approach to modelling of mill power draw. Trans. Inst. Mining Metall. (Section C: Mineral Processing Ext. Metall.) 105, C54-C62. Austin, L.G., 1990. A mill power equation for SAG mills. Miner. Metall. Process. 57-62]), the effect of lifter design and its interaction with mill speed and filling are not incorporated. Recent experience suggests that there is an opportunity for improving grinding efficiency by choosing the appropriate combination of these variables. However, it is difficult to experimentally determine the interactions of these variables in a full scale mill. Although some work has recently been published using DEM simulations, it was basically. limited to 2D. The discrete element code, Particle Flow Code 3D (PFC3D), has been used in this work to model the effects of lifter height (525 cm) and mill speed (50-90% of critical) on the power draw and frequency distribution of specific energy (J/kg) of normal impacts in a 5 m diameter autogenous (AG) mill. It was found that the distribution of the impact energy is affected by the number of lifters, lifter height, mill speed and mill filling. Interactions of lifter design, mill speed and mill filling are demonstrated through three dimensional distinct element methods (3D DEM) modelling. The intensity of the induced stresses (shear and normal) on lifters, and hence the lifter wear, is also simulated. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
The power output achieved at peak oxygen consumption (VO2 peak) and the time this power can be maintained (i.e., Tmax) have been used in prescribing high-intensity interval training. In this context, the present study examined temporal aspects of the VO2 response to exercise at the cycling power that output well trained cyclists achieve their VO2 peak (i.e., Pmax). Following a progressive exercise test to determine VO2 peak, 43 well trained male cyclists (M age = 25 years, SD = 6; M mass = 75 kg SD = 7; M VO2 peak = 64.8 ml(.)kg(1.)min(-1), SD = 5.2) performed two Tmax tests 1 week apart.1. Values expressed for each participant are means and standard deviations of these two tests. Participants achieved a mean VO2 peak during the Tmax test after 176 s (SD = 40; = 74% of Tmax, SD = 12) and maintained it for 66 s (SD = 39; M = 26% of Tmax, SD = 12). Additionally they obtained mean 95 % of VO2 peak after 147 s (SD = 31; M = 62 % of Tmax, SD = 8) and maintained it for 95 s (SD = 38; M = 38 % of Tmax, SD = 8). These results suggest that 60-70% of Tmax is an appropriate exercise duration for a population of well trained cyclists to attain VO2 peak during exercise at Pmax. However due to intraparticipant variability in the temporal aspects of the VO2 response to exercise at Pmax, future research is needed to examine whether individual high-intensity interval training programs for well trained endurance athletes might best be prescribed according to an athlete's individual VO2 response to exercise at Pmax.